Skip to main content
Download PDF

Risk factors for postoperative acute kidney injury after cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy: a meta-analysis and systematic review

World Journal of Surgical Oncology volume 23, Article number: 40 (2025) Cite this article

Abstract

Background

Acute kidney injury after CRS + HIPEC is a serious postoperative complication, but only a few studies have reported its postoperative risk factors. In addition, there are large discrepancies in the results of available observational studies.

Methods

We searched The Cochrane Library, Embase, Web of Science,and PubMed to identify observational studies reporting risk factors for AKI after CRS + HIPEC. A meta-analysis was performed to investigate the effect of various preoperative and intraoperative risk factors on AKI after CRS + HIPEC.

Results

A total of 7 studies were included in this study, comprising 1550 patients who developed AKI after CRS + HIPEC. The results of meta-analysis showed that the significant preoperative risk factors were age, sex, BMI, eGFR, Hb, PCI, diabetes mellitus, and hypertension. IO cisplatin, IO SBP < 100 was identified as an intraoperative risk factor, whereas IO mitomycin emerged as a protective factor for postoperative AKI. In addition, the risk of postoperative AKI varied by primary tumor site, with Appendix being less prone to AKI, while mesothelioma and ovarian, two sites with a greatly elevated risk of postoperative AKI.

Conclusions

This meta-analysis identified a number of risk factors for postoperative AKI after CRS + HIPEC. By identifying these risk factors, it is more beneficial for clinicians to perform early preoperative interventions and select the most appropriate treatment strategy for their patients, thus minimizing the risk of postoperative AKI.

Trial registration

PROSPERO CRD42024585269.

Introduction

Peritoneal surface malignancies (PSM) are usually associated with poor prognosis and severe complications in patients [1]. PSM can be either primary tumors of the peritoneum or peritoneal metastases originating from secondary spread of tumors from other organs, including intra-abdominal organs (e.g., gastrointestinal and ovarian tumors) or extra-abdominal organs (e.g., lung, breast, and kidney tumors) [2]. The poor prognosis of PSM patients has always been a challenge for clinicians, despite the adoption of maximal tumor resection combined with preoperative as well as postoperative adjuvant intravenous chemotherapy [3]. Cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) has been used as a first-line treatment option for patients with progressive tumors of PSM and related abdominal organs [4,5,6,7,8,9,10,11]. Maximum resection of the tumor visible to the naked eye by CRS and continuous infusion of chemotherapeutic agents into the peritoneal cavity by means of HIPEC thereby inhibiting or killing microscopic residual cancer cells in the peritoneal cavity [3]. In patients with peritoneal metastases (PM), this is the only treatment that has been proven in studies to significantly improve patients' 5-year survival [12, 13]. According to the results of the study, the 5-year survival rate of colorectal cancer-derived peritoneal metastases increased to 25–51% with CRS combined with HIPEC, while the 5-year survival rate of pseudomucinous tumors was as high as 60–80% [14,15,16]. In addition, encouraging results have been achieved with prophylactic CRS + HIPEC in patients with progressive abdominal tumors at high risk of peritoneal metastases [17, 18]. PSM patients can be treated with CRS + HIPEC to improve survival, but the concern is that this combination is often accompanied by terribly high morbidity and mortality, and not everyone can tolerate this aggressive treatment modality [19,20,21]. On the other hand, patients receiving combination therapy were more likely to experience grade 3 or higher grade adverse events compared to patients receiving CRS alone (34 of 131 patients vs. 20 of 130 patients, p = 0.035) [22].

Acute kidney injury (AKI) is one of the most common complications after CRS + HIPEC, and its incidence has been reported to range from 1 to 48%, especially common in patients who possess a history of cisplatin use [23,24,25]. And AKI as a potentially dangerous complication has been reported in several studies [26, 27]. And the occurrence of AKI is closely associated with considerable morbidity and mortality [28]. The results of several studies have been shown that some risk factors are important predictors of postoperative CRS + HIPEC, including cisplatin use, decreased eGFR, age, gender, obesity, hypertension, and diabetes mellitus [29,30,31,32,33]. However, no studies have systematically summarized and evaluated the association between these risk factors and the occurrence of AKI after CRS + HIPEC.CRS + HIPEC improves the prognosis of patients, but the occurrence of postoperative AKI is often accompanied by prolonged hospitalization with increased mortality [24, 34, 35]. Therefore, we will focus on the effects of preoperative risk factors such as age, gender, body mass index (BMI), peritoneal cancer index (PCI), estimated glomerular filtration rate (eGFR), hemoglobin (Hb), diabetes mellitus, and hypertension, intraoperative risk factors such as intraoperative hypotension, intraoperative fluid management, and chemotherapeutic drug selection on AKI. In addition, the potential impact of different primary tumor sites on AKI risk will be explored. Through these analyses, we aim to provide clinicians with more accurate risk assessment tools and guide them to take targeted preventive measures preoperatively and intraoperatively to reduce the incidence of AKI and improve patient prognosis.

In patients undergoing CRS + HIPEC, AKI is a serious postoperative complication that is closely related to patient prognosis. Although studies have examined the risk factors for AKI, the results vary widely and lack systematic summarization. Therefore, the main objectives of this meta-analysis were (1) to determine the incidence of AKI after CRS + HIPEC. (2) To identify the major risk factors associated with the development of AKI after CRS + HIPEC. (3) To assess the effectiveness of reported prevention strategies and interventions in reducing the incidence and severity of AKI. (4) To identify gaps in existing research and suggest directions for future studies to improve patient outcomes and optimize perioperative management.

Materials and methods

This meta-analysis was conducted using the guidelines reported in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) declarative agreement as the primary guideline [36] and was pre-registered in PROSPERO (CRD42024585269). The PRISMA checklist specific to this meta-analysis can be found in Appendix Table S1.

Search strategy

Two investigators (CDZ and WL) independently conducted a systematic search in the Cochrane Library, Embase, Web of Science, and PubMed databases with the aim of identifying studies up to September 1, 2024 on risk factors for AKI after CRS combined with HIPEC. We used MeSH terms and keywords including CRS, HIPEC, and AKI, connecting synonyms by “OR” and combining different terms by “AND”. We focused on English-language journal articles, excluded unpublished and non-English literature, and reviewed only titles and abstracts to simplify screening. The detailed search strategy is described in the Appendix document.

Inclusion and exclusion criteria

All included literature for this meta-analysis met the inclusion and exclusion criteria.

The inclusion criteria were as follows:

  1. (1)

    The design was a case–control, cohort, or cross-sectional study.

  2. (2)

    Participants were adults (≥ 18 years of age) with primary or metastatic peritoneal tumors treated with CRS + HIPEC.

  3. (3)

    Studies provided definitions of CRS and HIPEC and complete patient baseline data.

  4. (4)

    Risk factors for AKI or the relationship between AKI and prognosis of patients after CRS + HIPEC were reported, and detailed event counts or odds ratios for the AKI and non-AKI groups were provided.

  5. (5)

    AKI diagnosis using KDIGO or AKIN criteria [37, 38].

  6. (6)

    Study quality with a Newcastle–Ottawa Scale (NOS) score ≥ 6.

Exclusion criteria were as follows:

  1. (1)

    reviews, conference reports, letters, case reports, and animal experiments.

  2. (2)

    Studies of poor quality and lacking complete data or results.

  3. (3)

    Articles with inaccessible full text or missing content.

Study selection and data extraction

The study screening process began with de-duplication of all retrieved literature using Endnote 20.0 software. Two authors (CDZ and LLF) then performed an initial screening of the literature by reviewing titles and abstracts to exclude studies that did not meet the predetermined inclusion and exclusion criteria. After the initial screening, the full text was evaluated to identify eligible studies. Any disagreements between the two authors were resolved through discussion with a third researcher who made the final decision. The study screening process is shown in Fig. 1.

Fig. 1
figure 1

PRISMA fow diagram for study selection

Full size image

We extracted the following data from the included studies using a specially designed form:

  1. (1)

    Basic information about the article: first author, year of publication and type of study.

  2. (2)

    Information about the participant population, including sample size, age, sex ratio, and region.

  3. (3)

    Information on risk factors, divided into preoperative risk factors, intraoperative risk factors, and different primary tumor sites, the specific classification can be found in the results section.

  4. (4)

    Study data and results, including event counts in the AKI and non-AKI groups for different risk factors, the magnitude of independent risk factors, and the incidence of potential risk factors in different studies.

Quality assessment and statistical analysis

Quality assessment was performed using the Newcastle–Ottawa Scale (NOS) for case–control and cohort studies and the Cochrane Manual for randomized clinical trials. Two authors (CDZ and WL) independently assessed studies in three domains: selection, comparability, and outcome/exposure. Scoring was done using a checklist containing 8 items, where 1–3 stars indicated low quality, 4–6 stars indicated moderate quality, and 7–9 stars indicated high quality. All included studies were rated as high quality with a score of ≥ 7 stars. See Appendix Table S2 for a detailed rating scale.

We conducted this meta-analysis using Review Manager 5.4 and Stata 17.0 to assess the effect sizes of the risk factors, including the mean difference (MD) and the ratio of ratios (OR) and their 95% confidence intervals. Heterogeneity between studies was assessed using the Cochrane Q-test and I 2 statistic. Where significant heterogeneity was detected (I 2 ≥ 50%), it was analyzed using a random-effects model, and sensitivity analyses were performed to determine the source of heterogeneity. Conversely, if heterogeneity was not significant (I 2 < 50%), a fixed-effects model was used. Publication bias was assessed using funnel plots, Begg's test, and Egger's test to ensure stability of the findings. All tests were two-tailed and P < 0.05 was considered statistically significant.

Results

Literature search results and study characteristics

A total of 63 articles on AKI after CRS + HIPEC were retrieved through the developed search strategy (Fig. 1). All retrieved articles were imported into Endnote 20.0 software, and 16 duplicate articles were excluded using the software de-duplication function. By reading the titles and abstracts, 22 papers that did not meet the inclusion criteria were initially excluded. A total of 25 papers were retained after the initial screening. Among the remaining papers, we performed full-text reading and excluded a total of 18 articles that did not meet the inclusion requirements, including 6 papers that could not extract data, 3 papers with Newcastle–Ottawa Scale (NOS) scores lower than 6, 5 papers describing problems that were not related to the topic, and 4 papers that did not record the target results. In the end, a total of 7 papers were included in this systematic review and meta-analysis, all of which were retrospective studies and all of which described in detail the number of events or specific values of the different risk factors for postoperative AKI in the AKI group versus the Non-AKI group (Table 1).

Table 1 Information on the basic characteristics of the included studies
Full size table

This systematic review and meta-analysis investigated a total of 1550 patients who developed AKI after CRS + HIPEC in seven studies. The included studies were published online from 2017 to 2024. Two of the included studies were from the United States, two from China, two from Germany, and one from Portugal. The largest proportion of all patients were from the United States (34.39%), followed by China (28.39%), Germany (25.48%), and Portugal (11.74%). A total of 28 risk factors as well as 6 different tumor primary sites were involved in the analysis of the impact of postoperative AKI. The risk factors were divided into preoperative and intraoperative for independent analysis, and a summary of the detailed analysis results can be found in Table 2. The main primary sites of the tumors were appendix (39%) and colorectal cancer (21%), followed by gastric (13%),pseudomyxoma peritonei (9%), mesothelioma (6%),ovarian (6%), andothers (4%). detailed distribution can be found in Appendix Figure S1. Detailed characteristics of the seven included studies can be found in Table 1.

Table 2 Results of meta-analysis of risk factors
Full size table

Preoperative risk factors

In the seven studies included in this meta-analysis, we pooled and analyzed a total of 20 potential preoperative risk factors. These included the use of drugs such as ACEI or ARB, Diuretics, and NSAIDs, as well as patient age, gender, BMI, and PCI. We also performed a pooled analysis of patients' preoperative Alb, preoperative Hb, preoperative eGFR, preoperative Urea, and Preoperative creatinine. In addition, the effect of various preoperative underlying diseases of the patients, such as Chronic kidney diseas, Diabetes mellitus, Heart disease, Hypertension, and the patients' preoperative Neoadjuvant therapy and Preoperative chemotherapy on the Postoperative AKI were also included in our analysis.Hospitalization (days) and ICU duration (days) as potential risk factors for postoperative AKI were also explored. All the data related to the above risk factors were collected through specially designed and scientifically based statistical forms, and preoperative risk factors with complete and comparable data were analyzed in a pooled manner, in which eight risk factors such as age, gender, BMI, PCI, eGFR, Hb, Diabetes mellitus, and Hypertension were considered to have a statistically significant (p < 0.05), and the results of meta-analysis of all the above potential risk factors can be found in Table 2.

Age

A total of six studies [23, 24, 30,31,32,33] recorded information on the distribution of age in the AKI group versus the Non-AKI group, and information on age was reported as mean ± standard deviation. The heterogeneity test suggested that there was no heterogeneity between studies (I 2 = 0%, P = 0.50). Therefore, a fixed-effects model was chosen for the analysis and the pooled analysis showed (MD = 2.04, 95% CI: 0.55,3.52, p = 0.007) (Fig. 2A). We therefore conclude that advanced age is one of the preoperative risk factors for AKI after CRS + HIPEC.

Fig. 2
figure 2

Forest plot of preoperative risk factors: A age; B sex; C BMI; D peritoneal cancer index (PCI); E preoperative eGFR; F preoperative Hb; G diabetes mellitus; H hypertension

Full size image

Sex

A total of six studies [23, 24, 29, 31,32,33] described the gender distribution of patients, recorded using dichotomous variables. After performing the test for heterogeneity (I 2 = 21%, P = 0.27), meta-analysis was performed using a fixed-effects model. The results suggested a significant and statistically significant difference between the two groups (OR = 1.53, 95% CI: 1.17,2.00, p = 0.002) (Fig. 2B). Therefore, we conclude that the risk of AKI after CRS + HIPEC is greater in male patients than in female patients. Gender is one of the preoperative risk factors for postoperative AKI.

BMI

A total of five studies [23, 24, 30, 31, 33] reported detailed information on patients' BMI using mean ± standard deviation data recording. The heterogeneity test suggested no heterogeneity between studies (I 2 = 0%, P = 0.65). Analysis using the fixed effect model showed a significant and statistically significant difference between the two groups (MD = 1.22, 95% CI: 0.42,2.03, p = 0.003) (Fig. 2C). Therefore, we can conclude that the risk of postoperative AKI after CRS + HIPEC increases as the value of BMI increases.

Peritoneal cancer index

A total of three studies [24, 31, 32] referred to patients' preoperative Peritoneal cancer index (PCI), and the data were described using mean ± standard deviation recording. By heterogeneity test (I 2 = 0%, P = 0.51), P > 0.1 suggests that there is no heterogeneity between studies, so we used fixed effect model for pooled analysis. The results showed a significant difference between the AKI and Non-AKI groups, and the results were statistically significant (MD = 3.79, 95% CI: 1.49,3.79, p = 0.003) (Fig. 2D). Therefore, we conclude that higher preoperative PCI is one of the significant risk factors for postoperative AKI.

Preoperative eGFR and Hb

A total of three studies [30,31,32] reported details of Preoperative eGFR, recorded as mean ± standard deviation. Pooled analysis of the data using continuous variables and random effects model (I 2 = 0%, p = 0.97) suggested that there was no heterogeneity between the two and there was a significant difference between the two groups (MD = -11.53, 95%CI: -17.89,-5.17, p = 0.0004) (Fig. 2E). Therefore, we conclude that a decrease in Preoperative eGFR leads to an increase in the incidence of AKI after CRS + HIPEC and that Preoperative eGFR is a significant preoperative risk factor.

In addition, a total of 2 studies [30, 32] referred to the Preoperative Hb of patients and recorded detailed data in the form of mean ± standard deviation. Heterogeneity analysis showed no heterogeneity between the two (I 2 = 0%, P = 0.94), which was analyzed using continuous variables and fixed effects model. The results suggested a significant difference between the two groups (MD = -5.87, 95%CI: -10.90,-0.83, p = 0.02) (Fig. 2F) and were statistically significant. In other words, a decrease in preoperative Hb increased the incidence of postoperative AKI.

Diabetes mellitus and hypertension

A total of five studies [23, 29, 30, 32, 33] reported diabetes in 1310 patients, detailing the number of people in the AKI group compared with those in the Non-AKI group. The heterogeneity test suggested that there was no heterogeneity among the studies (I 2 = 6%, P = 0.37), so we used a fixed-effects model for meta-analysis. The results suggested that diabetes mellitus was one of the significant risk factors for AKI after CRS + HIPEC, and the results were statistically significant (OR = 1.78, 95% CI: 1.15,2.75, p = 0.01) (Fig. 2G).

In addition a total of four studies [29, 30, 32, 33] reported information on patients' hypertension, of which the results of Annika et al. versus Bai et al. indicated that preoperative hypertension was a risk factor for postoperative AKI (P > 0.05). On the contrary, the findings of Lu et al. versus Lukas et al. concluded that hypertension does not lead to an increased risk of postoperative AKI. Therefore, we performed a meta-analysis using a random-effects model (I 2 = 59%, p = 0.06), which showed a significant difference between the two groups (OR = 2.43, 95% CI: 1.37,4.31, p = 0.002) (Fig. 2H), and the results were statistically significant. For the high heterogeneity of the pooled analysis, we used a case-by-case exclusion method to explore the source of heterogeneity, and the results showed that the I 2 values stabilized and no significant source of heterogeneity was found.

Other preoperative risk factors

Other preoperative risk factors included the use of drugs such as ACEI or ARB, Diuretics, NSAIDs, laboratory findings such as preoperative Alb, preoperative Urea and Preoperative creatinine. Similarly, we performed a pooled analysis of the above risk factors, but the results suggested that there was no significant difference between the two groups (P > 0.05). Detailed results of heterogeneity analysis and pooled analysis can be found in Table 2.

Intraoperative risk factors

In our seven included articles, we defined a total of eight risk factors as intraoperative risk factors, including the use of chemotherapeutic agents cisplatin and mitomycin in HIPEC, IO fluid, IO SBP < 100, IO transfusion, IO vasopressors, operation time, urine output, and other parameters. We tested the heterogeneity of the above risk factors and selected the appropriate effect model for pooled analysis based on their results to obtain scientific conclusions. The results suggested that the use of chemotherapeutic drugs cisplatin, mitomycin and IO SBP < 100(min) were significantly and statistically different between the two groups. Detailed results are shown in Table 2.

Operative time

A total of three studies [24, 30, 32] reported specific surgical times, using a mean ± standard deviation form of data recording. After testing for heterogeneity (I 2 = 50%, P = 0.14), the pooled data were analyzed using a random effects model. The results showed that the duration of surgery was not significantly different between the two groups (MD = 21.92, 95%CI: -20.25,64.08, p = 0.31) (Fig. 3A) and the results were not statistically significant. In other words, it is not yet possible to consider the duration of surgery as one of the risk factors for AKI after CRS + HIPEC.

Fig. 3
figure 3

Forest plot of intraoperative risk factors: A operative time; B cistplatin; C mitomycin; D IO SBP < 100

Full size image

Chemotherapy regimens

A total of 5 of the 7 included studies in this meta-analysis mentioned and documented the number of events in the AKI group compared with the number of events in the Non-AKI group with different intraoperative chemotherapy regimens. Intraoperative chemotherapy regimens included the use of drugs such as cistplatin, oxilaplatin, and mitomycin, of which the data for cistplatin and mitomycin were comparable, so we analyzed the data for these two drugs separately.

A total of four studies [24, 31,32,33] reported a comparison of the number of events in patients using the chemotherapeutic agent cistplatin in HIPEC, using a dichotomous variable recording format. Heterogeneity analysis was performed and revealed heterogeneity among the studies (I 2 = 79%, p = 0.01), and the results suggested that intraoperative use of cistplatin greatly increased the risk of postoperative AKI (OR = 2.84, 95% CI: 1.27,6.35, p < 0.0001) (Fig. 3B). When we explored the source of heterogeneity using a cull-by-cull approach, we found that I 2 values stabilized (66%-79%) and no source of heterogeneity was identified.

Three studies [23, 29, 31] reported the use of the drug mitomycin between the two groups, and the heterogeneity analysis revealed a large heterogeneity between the studies (I 2 = 70%, P = 0.04), so we used a case-by-case exclusion method to explore the source of heterogeneity. When we excluded the data from Annika et al. [29] study, we found that the heterogeneity disappeared (I 2 = 0%, P = 0.33), and thus we determined that the data from Annika et al.'s study was the source of heterogeneity. After eliminating the source of heterogeneity, we found that the data from the studies of Eduarda [31] et al. and Juan et al. [23] had considerable homogeneity, and by pooling and analyzing the data from both, we found that the use of mitomycin was significantly different between the two groups, and that the use of mitomycin was one of the protective factors given for postoperative AKI, and the results had a statistically significant (OR = 0.41, 95% CI: 0.26,0.63, p < 0.0001) (Fig. 3C).

IO SBP < 100 mmHg(min)

A total of 2 studies [32, 33] recorded the specific time (min) for intraoperative IO SBP < 100 mmHg and described the data as mean ± standard deviation. Pooled analysis of the data from Lu et al. and Lukas et al. using a random-effects model (I 2 = 0%, p = 0.50) revealed a significant difference between the two groups and the results were statistically significant (MD = 10.95, 95%CI:3.15,18.75, p = 0.006) (Fig. 3D). Therefore, we got the conclusion that prolonged duration of intraoperative IO SBP < 100 leads to increased risk of postoperative AKI after CRS + HIPEC and is one of the intraoperative risk factors.

Other intraoperative risk factors

Other intraoperative risk factors included parameters such as IO fluid, IO transfusion, IO vasopressors, and urine output. Detailed results of heterogeneity analysis with meta-analysis can be found in Table 2.

Two studies [24, 32] explored the effect of IO fluid on postoperative AKI, and the results told us that IO fluid was not one of the intraoperative risk factors (MD = 79.20, 95%CI:-135.33,293.72, p = 0.47).

Three studies [23, 32, 33] mentioned detailed data on IO transfusion, analyzed by random effects model (I 2 = 60%, p = 0.08), which suggested that IO transfusion was not significantly different between the two groups (OR = 0.90, 95%CI:0.47,1.72, p = 0.74). Heterogeneity between studies disappeared after excluding data from the study by Lukas et al. (I 2 = 0%, p = 0.79). However, the conclusions did not change (OR = 1.20, 95%CI:0.80,1.79, p = 0.38).

2 studies [32, 33] reported the effect of IO vasopressors on postoperative AKI, and the data were pooled and analyzed using a random-effects model, and the results suggested that the use of intraoperative vasopressors did not increase the risk of AKI.

In addition, a total of 2 studies [32, 33] recorded patients' intraoperative urine output, and complete data were recorded by mean ± standard deviation. We also performed a meta-analysis, and the results suggested that the increase or decrease in intraoperative urine output was not one of the risk factors for postoperative AKI, and the results were not statistically significant (MD = 27.15, 95% CI:-127.21,181.51, p = 0.73).

Primary tumor site

A total of five out of seven included studies reported the comparative number of events and incidence of AKI after CRC + HIPEC for different primary tumor sites. In our dataset, the most common primary site was appendix (39%), followed by colorectal (21%) and gastric (13%), and the other sites and their percentages were pseudomyxoma peritonei (9%), mesothelioma (8%), ovarian (6%), and others (4%), respectively. For different sites of primary tumors, we separately and independently performed heterogeneity tests and selected appropriate models for meta-analysis to investigate whether the primary tumor site was a potential risk factor for postoperative AKI. The detailed results of the heterogeneity analysis and meta-analysis are shown in Table 2.

Among them, a total of five studies [23, 29, 31,32,33] reported the number of events of appendiceal site between the AKI group and Non-AKI group, and the data were pooled and analyzed by using a dichotomous variable with a random-effects model (I 2 = 61%, P = 0.04), and the exclusion of the studies one by one revealed that the I 2 values stabilized, and no source of heterogeneity was found. The results suggested that patients with tumors at the appendix site had a significantly lower risk of postoperative AKI (OR = 0.48, 95%CI:0.24,0.98, p = 0.04) (Fig. 4A).

Fig. 4
figure 4

Forest plot of primary tumor site: A appendix; B mesothelioma; C ovarian

Full size image

In addition, four studies reported the role of primary tumors at mesothelioma [23, 29, 31, 33] and ovarian [29, 31,32,33] sites on postoperative AKI, respectively. Our pooled analysis of the data revealed that the risk of postoperative AKI, regardless of whether the tumor was at mesothelioma (OR = 2.54, 95%CI:1.21,5.30, p = 0.01) (Fig. 4B) or ovarian (OR = 2.31, 95%CI:1.37,3.89, p = 0.002) (Fig. 4C) sites, was substantially increased.

Subgroup analysis

Considering that the populations studied in our inclusion study came from all over the world, we divided them into three regions, including Europe, Asia, and the Americas, and conducted subgroup analyses of the age and gender factors to explore whether regional factors contribute to the creation of greater heterogeneity. The results suggested that in the Asian subgroup (p = 0.74) and the European subgroup (p = 0.09), the age factor was not significantly different between the AKI and Non-AKI groups, and the results were not statistically significant. In contrast, in the Americas subgroup, older patients were more likely to develop AKI after CRS + HIPEC (p = 0.003) (Fig. 5A). Therefore, we conclude that the concept of age as a risk factor for postoperative AKI may be more appropriate for the American population. Subgroup analysis of the gender factor suggested that the results were consistent with the total effect in the American (p = 0.007) and European (p = 0.04) populations. In contrast, the Asian population showed the opposite results (Fig. 5B).

Fig. 5
figure 5

Forest plot of subgroup analysis: A age; B sex(region); C sex(diagnostic criteria); D diabetes mellitus; E appendix; F mesothelioma

Full size image

In addition, since the included studies used two different diagnostic criteria, AKIN and KDIGO, for the definition of AKI, we grouped them with different diagnostic criteria for subgroup analysis. For diabetes mellitus, a preoperative risk factor, the results suggested that diabetes mellitus did not lead to an increased risk of postoperative AKI under the AKIN diagnostic criteria (p = 0.34). And under the KDIGO diagnostic criteria, the results were consistent with the total effect (p = 0.02) (Fig. 5D). In addition, we also performed subgroup analysis for appendix (Fig. 5E) and mesothelioma (Fig. 5F). The results all suggested significant differences between the two groups only under the KDIGO diagnostic criteria. Therefore, we conclude that for part of the meta-analysis results may be more accurate under the KDIGO diagnostic criteria. On the contrary, the subgroup analysis of the gender factor suggested that there was a significant difference between the two groups only under the AKIN diagnostic criteria (Fig. 5C). The results of the detailed subgroup analysis are shown in Table 3.

Table 3 Results of subgroup analysis of risk factors
Full size table

Publication bias

Due to the limited number of included studies, it was not possible to visualize publication bias among studies using funnel plots, so we used the Egger test and Begg test to explore whether there was significant publication bias among the included studies. In addition, we used a sensitivity analysis of the relevant risk factors using round-by-round exclusion hair to ensure the stability of the study results.

We conducted Egger's test and Begg's test for age (Appendix Figure S2A-S2D), gender (Appendix Figure S3A-S3D), BMI (Appendix Figure S4A-S4D), DM (Appendix Figure S5A-S5D), and appendix (Appendix Figure S6A-S6D), respectively, and observed the change of the total effect value after excluding the included literature one by one. The results suggested that the p-values of Egger's test and Begg's test for the risk factors mentioned above were greater than 0.05, suggesting that there was no significant publication bias among the studies. Therefore, we conclude that publication bias has no significant effect on the findings of this meta-analysis, and the results are highly stable. The detailed Egger test and Begg test results are shown in Table 4.

Table 4 Begg’s and Egger’s p value of postoperative risks factors for AKI after CRS + HIPEC
Full size table

Discussion

Patients with peritoneal surface malignancies (PSM) often face severe complications and poor survival prognosis [1, 39]. Currently, cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) has become the primary treatment modality for the treatment of patients with primary or metastatic peritoneal tumors [4,5,6,7,8,9,10,11].CRS + HIPEC significantly improves the survival prognosis of the patients [40, 41], but HIPEC is associated with higher mortality and morbidity along with the improvement in the prognosis [42, 43].CRS + HIPEC has a perioperative mortality rate of approximately 4% and a combined incidence of postoperative related complications of up to 40% [19, 44]. Acute kidney injury (AKI), one of the most serious complications in cancer treatment, significantly increases the length of hospitalization and is strongly associated with high morbidity and mortality [45]. Despite continuous improvement in perioperative management, the incidence of complications after major surgery still exceeds 30% [46], of which AKI accounts for 13%, and patients with these AKIs face more than a six-fold increased risk of death [47,48,49]. Therefore, early identification of risk factors for AKI after CRS + HIPEC and preoperative interventions targeting reversible risk factors are essential to improve patient prognosis. In this study, the combined incidence and risk factors of AKI in PSM patients after CRS + HIPEC were comprehensively analyzed by meta-analysis.

This meta-analysis of the incidence of postoperative AKI after CRS + HIPEC in the seven included articles suggested that the combined incidence of postoperative AKI was approximately 22.9%. In contrast, the incidence of postoperative AKI after CRS + HIPEC ranged from 1 to 48% as reported in previous studies [33]. The large differences in incidence rates among studies may stem from differences in sample size or differences in diagnostic criteria for AKI. In this study, a total of five studies used the most widely recognized KDIGO diagnostic criteria and two studies used the AKIN criteria. The incidence of AKI under different diagnostic criteria was counted separately, resulting in 23.7% for the AKIN criterion and 22.54% for the KDIGO criterion, which were close to each other and within the range of 1–48%.

Our study showed that higher body mass index (BMI) was associated with an increased risk of acute kidney injury (AKI) after CRS + HIPEC (p < 0.05), which is consistent with the findings of Juan et al. However, the studies by Samer et al. and Eduarda et al. did not find a significant association between BMI and AKI. We note that there were differences between the study by Juan et al. using the AKIN diagnostic criteria and other studies using the KDIGO criteria. After excluding the data from Juan et al., there was no significant association between BMI and AKI (p > 0.05), suggesting that BMI as a risk factor for AKI may be applicable only to the AKIN criteria. Obesity is associated with a variety of inflammatory responses and diseases, including heart disease, hypertension, and osteoarthritis [50, 51], and has been linked to the development and progression of cancer [52,53,54]. Obese patients face a higher risk of complications in the perioperative period [55, 56]. Conversely, underweight patients have higher surgical mortality associated with low albumin levels and energy reserves [57, 58]. Therefore, preoperative weight management is crucial for postoperative recovery.

The Peritoneal Cancer Index (PCI) scoring system, proposed by Sugarbaker et al., is widely used to assess peritoneal metastasis of abdominal tumors [59,60,61]. The system divides the abdomen into 13 regions and assesses tumor spread and the feasibility of CRS by scoring tumor size [62].PCI has also been associated with a high risk of death in patients after CRS + HIPEC [63]. Our meta-analysis showed that higher preoperative PCI values were associated with a higher incidence of postoperative AKI. This finding is consistent with the study of Samer et al. but contrary to the studies of Eduarda et al. and Lu et al. It may be related to the different PCI scoring methods and the subjectivity of the scorers.PCI is a powerful tool for assessing patients' preoperative risk and postoperative prognosis, and our study also demonstrated that PCI reliably predicts postoperative AKI.Therefore, PCI scoring should be routinely performed in patients with peritoneal carcinomatosis preoperatively performed to assess tumor load and risk of postoperative complications and to guide treatment selection.

The highly correlated relationship between advanced age and various renal function indices with AKI has been confirmed by several studies [64, 65].People aged 65 years or older are defined as traditionally elderly, and this segment of the population is currently the fastest growing in developed countries [66]. Acute kidney injury (AKI), however, is one of the most common emergencies among elderly patients, and its incidence has been on the rise in recent years. Its main pathogenesis lies in the fact that aging kidneys are often accompanied by structural changes and functional decline. As the kidneys age, the renal blood vessels and glomeruli gradually become sclerotic, leading to a series of functional changes. For example, the decline of eGFR, the decrease of ultrafiltration coefficient, and the decreasing ability of the kidney to regulate itself [67, 68]. The results of our meta-analysis suggest that two factors, advanced age and decline in eGFR, are among the high-risk factors for AKI after CRS + HIPEC. For the elderly aged 65 years or above, we should pay more attention to the changes of preoperative renal function indexes in patients during preoperative evaluation, and timely monitoring and early intervention are particularly important. In addition, for the identification of patients with acute kidney injury, proteinuria and eGFR should be monitored at the same time, which not only improves the identification rate of AKI, but also further evaluates the long-term prognosis of patients [69].

In our study, diabetes mellitus and hypertension were identified as preoperative risk factors for AKI after CRS + HIPEC.DM and hypertension have gained widespread attention as serious global public health problems. And, their high correlation with AKI has been confirmed by several studies [70, 71]. DM-associated AKI, which mainly originates from circulatory disorders and changes in the renal microenvironment caused by metabolic disorders, thus affecting the self-repairing ability of the kidneys, has led to the development of a series of complications [72]. The pathological mechanism of hypertension-related AKI is mainly that the sustained elevation of blood pressure puts the kidneys in a state of hyperperfusion leading to thickening and hardening of the vessel wall, and ultimately the formation of atherosclerosis. In addition, glomerular injury and tubulointerstitial fibrosis are also important causes. Therefore, before CRS + HIPEC is performed in patients with DM and hypertension, the main strategy of treatment should be focused on glycemic control and blood pressure management.

We performed a meta-analysis of a total of eight intraoperative factors and finally identified IO SBP < 100 mmHg(min) as an intraoperative risk factor for AKI. It is also mentioned in the KDIGO guidelines that maintaining stable blood pressure intraoperatively, especially avoiding hypotension, will reduce the risk of kidney injury. Several studies (single and multicenter) exist to demonstrate the association between intraoperative hypotension and postoperative AKI [49, 73, 74]. However, blood pressure was described in the studies as mean arterial pressure (MAP), and in 40% of these patients, MAP was below 65 mmHg (for 10–12 min) during surgery. Therefore, although we confirmed that intraoperative SBP < 100 mmHg increases the risk of developing postoperative AKI, limited by the limited number of studies we included, more future studies are needed to confirm the association between intraoperative hypotension and postoperative AKI after CRS + HIPEC. In addition, the effect of different mean arterial pressure (MAP) gradients on AKI in hypotensive states will be one of our future research directions.

Common chemotherapeutic agents used in HIPEC surgery, including oxaliplatin, cisplatin (CDDP), and mitomycin C (MMC). Our study conducted a meta-analysis of the role of MMC and cisplatin on postoperative AKI. One of the surprises was that MMC appeared to be relatively protective against postoperative AKI. Extant studies have explored various aspects of the use of MMC with oxaliplatin in HIPEC. Among them, the results of van et al. suggested that oxaliplatin not only shortened the time but also had no adverse effect on postoperative complications or short-term survival compared with MMC infusion therapy [75]. In a retrospective study of patients with colon cancer by the American Society for Peritoneal Surface Malignancies (ASPSM), a total of 539 patients who received MMC and oxaliplatin respectively were analyzed for survival [76]. The results suggested that the MMC group appeared to have a better survival prognosis (32.7 months) compared to the OS of the oxaliplatin group (31.4 months). In addition, moreover, the results of a study showed that intraoperative coadministration of cisplatin and MMC was not associated with an increase in the incidence of postoperative AKI [77]. As an alkylating agent, cisplatin is widely used in the treatment of tumors, and is particularly effective in gastrointestinal and gynecological tumors. However, the use of cisplatin is associated with several complications, including nephrotoxicity, ototoxicity, neurotoxicity, and vomiting. The most significant complication is nephrotoxicity. The main pathogenesis of nephrotoxicity is acute or subacute tubular necrosis due to injury of proximal tubules. According to the KDIGO guidelines, we recommend avoiding nephrotoxic drugs and using renoprotective measures such as sodium thiosulfate and amifostine when necessary, especially after cisplatin chemotherapy. Among them, the prevention of nephrotoxicity after HIPEC by sodium thiosulfate has been confirmed by several studies [29, 78, 79]. The effectiveness of the drug has been gradually proved as the studies continue, but for the nephrotoxicity of cisplatin we still need to develop a standardized treatment regimen with the aim of reducing the postoperative AKI caused by nephrotoxicity.In addition, in the KDIGO guidelines, the importance of establishing a multidisciplinary team that includes nephrologists, intensivists, surgeons, and anesthesiologists to work together in the management of patients with AKI is specifically mentioned.

Finally, in this study, we specifically focused on the effect of the dose of chemotherapeutic agents used in HIPEC on postoperative acute kidney injury (AKI). Although we provided detailed information on the doses of chemotherapeutic agents used in different studies, we found it challenging to perform a direct meta-analysis due to the heterogeneity of the data. Our analysis revealed a possible association between the type and dose of chemotherapeutic agents and the risk of AKI, especially when cisplatin (Cisplatin) was used, which was significantly associated with an increased risk of postoperative AKI. In contrast, mitomycin (Mitomycin C) showed a protective effect against postoperative AKI. These findings underscore the importance of optimizing chemotherapeutic drug dosing in HIPEC treatment and the need for further studies to determine the impact of different chemotherapy regimens on AKI risk. Future studies require more standardized data collection and more refined dose–response analyses to better understand the role of chemotherapeutic agents in HIPEC and provide guidance for clinical practice.

Strengths and limitations

This systematic review and meta-analysis provides the first complete search and scientific analysis of the risk factors for AKI after CRS + HIPEC and a comprehensive analysis of the incidence of postoperative AKI in extant. It fills the gap of incomplete data on AKI risk factors and innovatively evaluates the impact of different primary tumor sites on the incidence of postoperative AKI.Although our study provides valuable information about risk factors for AKI after CRS + HIPEC, there are some limitations. All included studies were retrospective cohort studies, which may be subject to selection bias and information bias. In addition, heterogeneity among studies may have affected the interpretation of the results. Although we used random effects models and sensitivity analyses to deal with heterogeneity, the influence of these factors on the overall conclusions cannot be excluded. Our study may also have been affected by publication bias, although Begg's and Egger's tests did not detect significant publication bias. Among the included studies, there were differences in the specific modalities of CRS and HIPEC, the selection and dosage of chemotherapeutic agents, and the diagnostic criteria for AKI. This diversity may have influenced the assessment and comparison of AKI risk factors.In addition, data completeness and reporting bias are potential limitations of our study, as only published studies were included and some unpublished results may be missing. Finally, the results of our study may be limited by geographic and population distribution, with most studies coming from specific regions and may not be fully representative of the global picture.

Future directions

Due to the limited number of included studies, we lacked detailed information on some of the potential risk factors and thus the corresponding analyzed results. For example, Annika et al. [29] found that patients possessing coronary artery disease increased the risk of AKI after CRS + HIPEC. In addition, only one study [31] reported the effect of preoperative antibiotic use on AKI, whereas prophylactic antibiotic use is a very common treatment in laparotomy reduction. In a study by Lu et al. [32], it was mentioned that ascites was also one of the risk factors for AKI, but the amount of ascites was not counted. For malignant tumors in the abdominal cavity, ascites is an unavoidable challenge, and understanding the effect of different gradients of ascites volume on postoperative AKI will also be one of the future research directions.Finally, it is also particularly important to explore the effect of the dose of chemotherapeutic agents during HIPEC on postoperative AKI.

Conclusion

The results of this systematic review and meta-analysis showed that the preoperative risk factors for postoperative AKI after CRS + HIPEC include age, gender, BMI, PCI, eGFR, Hb, Diabetes mellitus, and Hypertension.All of the above factors, except for age, gender, and PCI, are potential risk factors that can be controlled or reversible. Early identification as well as advance intervention in the perioperative period will greatly reduce the incidence of postoperative AKI in patients. For example, preoperative monitoring and management of renal function, Hb, blood glucose, and blood pressure. In addition, IO SBP < 100 mmHg(min) is an intraoperative risk factor for postoperative AKI. Close attention to intraoperative anesthesia management and maintenance of normal range intraoperative blood pressure will reduce the incidence of AKI. Finally, for the selection of intraoperative chemotherapeutic agents, MMC can significantly reduce the risk of postoperative AKI compared with cisplatin. The results of this study may provide clinicians with more epidemiological evidence on the prevention of postoperative AKI after CRS + HIPEC, so as to establish personalized treatment plans and optimize the perioperative management of patients, with a view to improving the prognosis of patients.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

PSM:

Peritoneal surface malignancy

NOS:

Newcastle‒Ottawa scale

AKI:

Acute kidney injury

CRS:

Cytoreductive surgery

HIPEC:

Hyperthermic intraperitoneal chemotherapy

PCI:

Peritoneal cancer index

CRC:

Colorectal cancer

SBP:

Systolic blood pressure

IO:

Intraoperative

DM:

Diabetes mellitus

AKIN:

Acute Kidney Injury Network

KDIGO:

Kidney Disease Improving Global Outcomes

References

  1. Cortés-Guiral D, Hübner M, Alyami M, Bhatt A, Ceelen W, Glehen O, Lordick F, Ramsay R, Sgarbura O, Van Der Speeten K, Turaga KK, Chand M. Primary and metastatic peritoneal surface malignancies. Nat Rev Dis Primers. 2021;7(1):91. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41572-021-00326-6. PMID: 34916522.

    Article  PubMed  Google Scholar 

  2. Kepenekian V, Bhatt A, Péron J, Alyami M, Benzerdjeb N, Bakrin N, Falandry C, Passot G, Rousset P, Glehen O. Advances in the management of peritoneal malignancies. Nat Rev Clin Oncol. 2022;19(11):698–718. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41571-022-00675-5. Epub 2022 Sep 7 PMID: 36071285.

    Article  PubMed  Google Scholar 

  3. van Stein RM, Aalbers AGJ, Sonke GS, van Driel WJ. Hyperthermic intraperitoneal chemotherapy for ovarian and colorectal cancer: a review. JAMA Oncol. 2021;7(8):1231–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1001/jamaoncol.2021.0580. PMID: 33956063.

    Article  PubMed  Google Scholar 

  4. van Driel WJ, Koole SN, Sonke GS, et al. Hyperthermic intraperitoneal chemotherapy in ovarian cancer. N Engl J Med. 2018;378(3):230e40. https://doiorg.publicaciones.saludcastillayleon.es/10.1056/NEJMoa1708618.

    Article  Google Scholar 

  5. Glehen O, Kwiatkowski F, Sugarbaker PH, Elias D, Levine EA, De Simone M, Barone R, Yonemura Y, Cavaliere F, Quenet F, Gutman M, Tentes AA, Lorimier G, Bernard JL, Bereder JM, Porcheron J, Gomez-Portilla A, Shen P, Deraco M, Rat P. Cytoreductive surgery combined with perioperative intraperitoneal chemotherapy for the management of peritoneal carcinomatosis from colorectal cancer: a multi-institutional study. J Clin Oncol. 2004;22(16):3284–92. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/JCO.2004.10.012. PMID: 15310771.

    Article  CAS  PubMed  Google Scholar 

  6. Yan TD, Black D, Savady R, Sugarbaker PH. Systematic review on the efficacy of cytoreductive surgery combined with perioperative intraperitoneal chemotherapy for peritoneal carcinomatosis from colorectal carcinoma. J Clin Oncol. 2006;24(24):4011–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/JCO.2006.07.1142. PMID: 16921055.

    Article  PubMed  Google Scholar 

  7. Yan TD, Deraco M, Baratti D, Kusamura S, Elias D, Glehen O, Gilly FN, Levine EA, Shen P, Mohamed F, Moran BJ, Morris DL, Chua TC, Piso P, Sugarbaker PH. Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy for malignant peritoneal mesothelioma: multi-institutional experience. J Clin Oncol. 2009;27(36):6237–42. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/JCO.2009.23.9640. Epub 2009 Nov 16 PMID: 19917862.

    Article  PubMed  Google Scholar 

  8. Sugarbaker PH. New standard of care for appendiceal epithelial neoplasms and pseudomyxoma peritonei syndrome? Lancet Oncol. 2006;7(1):69–76. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S1470-2045(05)70539-8. PMID: 16389186.

    Article  PubMed  Google Scholar 

  9. Chua TC, Moran BJ, Sugarbaker PH, Levine EA, Glehen O, Gilly FN, Baratti D, Deraco M, Elias D, Sardi A, Liauw W, Yan TD, Barrios P, Gómez Portilla A, de Hingh IH, Ceelen WP, Pelz JO, Piso P, González-Moreno S, Van Der Speeten K, Morris DL. Early- and long-term outcome data of patients with pseudomyxoma peritonei from appendiceal origin treated by a strategy of cytoreductive surgery and hyperthermic intraperitoneal chemotherapy. J Clin Oncol. 2012;30(20):2449–56. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/JCO.2011.39.7166IF:42.1Q1. Epub 2012 May 21 PMID: 22614976.

    Article  PubMed  Google Scholar 

  10. Foster JM, Zhang C, Rehman S, Sharma P, Alexander HR. The contemporary management of peritoneal metastasis: a journey from the cold past of treatment futility to a warm present and a bright future. CA Cancer J Clin. 2023;73(1):49–71. https://doiorg.publicaciones.saludcastillayleon.es/10.3322/caac.21749.

    Article  PubMed  Google Scholar 

  11. Glehen O, Gilly FN, Arvieux C, Cotte E, Boutitie F, Mansvelt B, Bereder JM, Lorimier G, Quenet F, Elias D, Association Française de Chirurgie. Peritoneal carcinomatosis from gastric cancer: a multi-institutional study of 159 patients treated by cytoreductive surgery combined with perioperative intraperitoneal chemotherapy. Ann Surg Oncol. 2010;17(9):2370–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-010-1039-7. Epub 2010 Mar 25 PMID: 20336386.

    Article  PubMed  Google Scholar 

  12. Elias D, Goéré D, Dumont F, et al. Role of hyperthermic intraoperative peritoneal chemotherapy in the management of peritoneal metastases. Eur J Cancer. 2014;50(2):332–40. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejca.2013.09.024.

    Article  CAS  PubMed  Google Scholar 

  13. Helm JH, Miura JT, Glenn JA, et al. Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy for malignant peritoneal mesothelioma: a systematic review and meta-analysis. Ann Surg Oncol. 2015;22(5):1686–93. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-014-3978-x.

    Article  PubMed  Google Scholar 

  14. Ellison LM, Man Y, Stojadinovic A, Xin H, Avital I. Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy in treatment of gastric cancer with peritoneal carcinomatosis. Chin J Cancer Res. 2017;29(1):86–92. https://doiorg.publicaciones.saludcastillayleon.es/10.21147/j.issn.1000-9604.2017.01.10. IF: 7.0 Q1. PMID: 28373757; PMCID: PMC5348479.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Elias D, Blot F, El Otmany A, Antoun S, Lasser P, Boige V, Rougier P, Ducreux M. Curative treatment of peritoneal carcinomatosis arising from colorectal cancer by complete resection and intraperitoneal chemotherapy. Cancer. 2001;92(1):71–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/1097-0142(20010701)92:1%3c71::aid-cncr1293%3e3.0.co;2-9. PMID: 11443611.

    Article  CAS  PubMed  Google Scholar 

  16. Feldman AL, Libutti SK, Pingpank JF, Bartlett DL, Beresnev TH, Mavroukakis SM, Steinberg SM, Liewehr DJ, Kleiner DE, Alexander HR. Analysis of factors associated with outcome in patients with malignant peritoneal mesothelioma undergoing surgical debulking and intraperitoneal chemotherapy. J Clin Oncol. 2003;21(24):4560–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/JCO.2003.04.150. PMID: 14673042.

    Article  CAS  PubMed  Google Scholar 

  17. Sun BJ, Daniel SK, Lee B. The role of prophylactic and adjuvant Hyperthermic Intraperitoneal Chemotherapy (HIPEC) in prevention of peritoneal metastases in advanced colorectal cancer. J Clin Med. 2023;12(20):6443. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/jcm12206443. PMID:37892582;PMCID:PMC10607874.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Dominic JL, Kannan A, Tara A, Hakimmohammed AR, Win M, Khorochkov A, Sultan W, Ahmed A, Kantamaneni K, Syzmanski MW, Singh R, Marquez RA, Asarian A, Thirunavukarasu P, Keckeisen G. Prophylactic hyperthermic intraperitoneal chemotherapy (HIPEC) for the prevention and control of peritoneal metastasis in patients with gastrointestinal malignancies: a systematic review of randomized controlled trials. EXCLI J. 2021;20:1328–45. https://doiorg.publicaciones.saludcastillayleon.es/10.17179/excli2021-4108. PMID: 34650387; PMCID: PMC8495114.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Chua TC, Yan TD, Saxena A, Morris DL. Should the treatment of peritoneal carcinomatosis by cytoreductive surgery and hyperthermic intraperitoneal chemotherapy still be regarded as a highly morbid procedure?: a systematic review of morbidity and mortality. Ann Surg. 2009;249(6):900–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/SLA.0b013e3181a45d86. IF:7.5Q1 PMID: 19474692.

    Article  PubMed  Google Scholar 

  20. Chua TC, Saxena A, Schellekens JF, Liauw W, Yan TD, Fransi S, Zhao J, Morris DL. Morbidity and mortality outcomes of cytoreductive surgery and perioperative intraperitoneal chemotherapy at a single tertiary institution: towards a new perspective of this treatment. Ann Surg. 2010;251(1):101–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/SLA.0b013e3181b5ae43. PMID: 19838105.

    Article  PubMed  Google Scholar 

  21. Yan TD, Edwards G, Alderman R, Marquardt CE, Sugarbaker PH. Morbidity and mortality assessment of cytoreductive surgery and perioperative intraperitoneal chemotherapy for diffuse malignant peritoneal mesothelioma–a prospective study of 70 consecutive cases. Ann Surg Oncol. 2007;14(2):515–25. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-006-9187-5. Epub 2006 Oct 10 PMID: 17031722.

    Article  PubMed  Google Scholar 

  22. Quénet F, Elias D, Roca L, Goéré D, Ghouti L, Pocard M, Facy O, Arvieux C, Lorimier G, Pezet D, Marchal F, Loi V, Meeus P, Juzyna B, de Forges H, Paineau J, Glehen O, UNICANCER-GI Group and BIG Renape Group. Cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy versus cytoreductive surgery alone for colorectal peritoneal metastases (PRODIGE 7): a multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 2021;22(2):256–66. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S1470-2045(20)30599-4. Epub 2021 Jan 18. PMID: 33476595.

    Article  PubMed  Google Scholar 

  23. Cata JP, Zavala AM, Van Meter A, Williams UU, Soliz J, Hernandez M, Owusu-Agyemang P. Identification of risk factors associated with postoperative acute kidney injury after cytoreductive surgery with hyperthermic intraperitoneal chemotherapy: a retrospective study. Int J Hyperthermia. 2018;34(5):538–44. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/02656736.2017.1368096. Epub 2017 Aug 29 PMID: 28812384.

    Article  PubMed  Google Scholar 

  24. Naffouje SA, Tulla KA, Chorley R, Armstrong N, Salti GI. Acute kidney injury increases the rate of major morbidities in cytoreductive surgery and HIPEC. Ann Med Surg (Lond). 2018;26(35):163–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.amsu.2018.09.036. PMID:30310679;PMCID:PMC6178214.

    Article  Google Scholar 

  25. Liesenfeld LF, Quiring E, Al-Saeedi M, Nusshag C, Büchler MW, Schneider M. Extensive peritonectomy is an independent risk factor for cisplatin hipec-induced acute kidney injury. Ann Surg Oncol. 2023;30(5):2646–56. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-022-12661-3. Epub 2022 Dec 10. PMID: 36496489; PMCID: PMC10085927.

    Article  PubMed  Google Scholar 

  26. Thakar CV, Christianson A, Freyberg R, Almenoff P, Render ML. Incidence and outcomes of acute kidney injury in intensive care units: a Veterans Administration study. Crit Care Med. 2009;37(9):2552–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/CCM.0b013e3181a5906f. PMID: 19602973.

    Article  PubMed  Google Scholar 

  27. Chertow GM, Burdick E, Honour M, Bonventre JV, Bates DW. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005;16(11):3365–70. https://doiorg.publicaciones.saludcastillayleon.es/10.1681/ASN.2004090740. Epub 2005 Sep 21 PMID: 16177006.

    Article  PubMed  Google Scholar 

  28. Goren O, Matot I. Perioperative acute kidney injury. Br J Anaesth. 2015;115(Suppl 2):ii3-14. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/bja/aev380. IF: 9.1 Q1 PMID: 26658199.

    Article  PubMed  Google Scholar 

  29. Kurreck A, Gronau F, Alberto Vilchez ME, Abels W, Enghard P, Brandl A, Francis R, Föhre B, Lojewski C, Pratschke J, Thuss-Patience P, Modest D, Rau B, Feldbrügge L. Sodium thiosulfate reduces acute kidney injury in patients undergoing cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy with cisplatin: a single-center observational study. Ann Surg Oncol. 2022;29(1):152–62. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-021-10508-x. Epub 2021 Aug 4. PMID: 34350529; PMCID: PMC8677645.

    Article  PubMed  Google Scholar 

  30. Bai Y, Du Y, Ye P, Luo Y. Acute kidney injury after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy in patients with advanced ovarian cancer. Front Oncol. 2023;25(13):1094410. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fonc.2023.1094410. IF:3.5Q2.PMID:36761938; PMCID:PMC9905615.

    Article  CAS  Google Scholar 

  31. Carias E, Ferreira H, Chuva T, Paiva A, Maximino J. Acute kidney injury after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy in a portuguese population. World J Oncol. 2022;13(6):370–8. https://doiorg.publicaciones.saludcastillayleon.es/10.14740/wjon1540. Epub 2022 Dec 24. PMID: 36660215; PMCID: PMC9822680.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Lu Y, Xiao Z, Zhao X, Ye Y, Li S, Guo F, Xue H, Zhu F. Incidence, risk factors, and outcomes of the transition of HIPEC-induced acute kidney injury to acute kidney disease: a retrospective study. Ren Fail. 2024;46(1):2338482. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/0886022X.2024.2338482. Epub 2024 Apr 11. PMID: 38604946; PMCID: PMC11011229.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Liesenfeld LF, Wagner B, Hillebrecht HC, Brune M, Eckert C, Klose J, Schmidt T, Büchler MW, Schneider M. HIPEC-induced acute kidney injury: a retrospective clinical study and preclinical model. Ann Surg Oncol. 2022;29(1):139–51. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-021-10376-5. IF: 3.4 Q1 . Epub 2021 Jul 14. PMID: 34260006; PMCID: PMC8677640.

    Article  PubMed  Google Scholar 

  34. Arjona-Sánchez A, Cadenas-Febres A, Cabrera-Bermon J, Muñoz-Casares FC, Casado-Adam A, Sánchez-Hidalgo JM, López-Andreu M, Briceño-Delgado J, Rufián-Peña S. Assessment of RIFLE and AKIN criteria to define acute renal dysfunction for HIPEC procedures for ovarian and non ovarian peritoneal malignances. Eur J Surg Oncol. 2016;42(6):869–76. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejso.2015.12.016. Epub 2016 Feb 11 PMID: 26898841.

    Article  PubMed  Google Scholar 

  35. Chen CY, Chang HY, Lu CH, Chen MC, Huang TH, Lee WL, Liao YS, Chen VC, Huang WS, Ou YC, Lung FC, Wang TY. Risk factors of acute renal impairment after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy. Int J Hyperthermia. 2020;37(1):1279–86. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/02656736.2020.1846793. PMID: 33198563.

    Article  CAS  PubMed  Google Scholar 

  36. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pmed.1000097. Epub 2009 Jul 21. PMID: 19621072; PMCID: PMC2707599.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Stevens PE, Levin A, Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members. Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Ann Intern Med. 2013;158(11):825–30. https://doiorg.publicaciones.saludcastillayleon.es/10.7326/0003-4819-158-11-201306040-00007. PMID: 23732715.

    Article  PubMed  Google Scholar 

  38. Mehta RL, Kellum JA, Shah SV, Molitoris BA, Ronco C, Warnock DG, Levin A, Acute Kidney Injury Network. Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury. Crit Care. 2007;11(2):31. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/cc5713. IF: 8.8 Q1 . PMID: 17331245; PMCID: PMC2206446.

    Article  Google Scholar 

  39. Franko J, Shi Q, Goldman CD, Pockaj BA, Nelson GD, Goldberg RM, Pitot HC, Grothey A, Alberts SR, Sargent DJ. Treatment of colorectal peritoneal carcinomatosis with systemic chemotherapy: a pooled analysis of north central cancer treatment group phase III trials N9741 and N9841. J Clin Oncol. 2012;30(3):263–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/JCO.2011.37.1039. Epub 2011 Dec 12. PMID: 22162570; PMCID: PMC3269953.

    Article  PubMed  Google Scholar 

  40. Moran B, Cecil T, Chandrakumaran K, et al. The results of cytoreductive surgery and hyperthermic intraperitoneal chemotherapy in 1200 patients with peritoneal malignancy. Colorectal Dis. 2015;17:772–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/codi.12975.

    Article  CAS  PubMed  Google Scholar 

  41. Jian C, Mou H, Zhang Y, Fan Q, Ou Y. Survival and complications of cytoreductive surgery with hyperthermic intraperitoneal chemotherapy in patients with intra-abdominal malignancies: a meta-analysis of randomized controlled trials. Front Pharmacol. 2023;9(14):1094834. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fphar.2023.1094834. PMID:36969856; PMCID:PMC10036049.

    Article  Google Scholar 

  42. Foster JM, Sleightholm R, Patel A, Shostrom V, Hall B, Neilsen B, Bartlett D, Smith L. Morbidity and mortality rates following cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy compared with other high-risk surgical oncology procedures. JAMA Netw Open. 2019;2(1):e186847. https://doiorg.publicaciones.saludcastillayleon.es/10.1001/jamanetworkopen.2018.6847. IF:10.5Q1.PMID:30646202;PMCID:PMC6484874.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Esquivel J, Averbach A, Chua TC. Laparoscopic cytoreductive surgery and hyperthermic intraperitoneal chemotherapy in patients with limited peritoneal surface malignancies: feasibility, morbidity and outcome in an early experience. Ann Surg. 2011;253(4):764–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/SLA.0b013e31820784df. PMID: 21475017.

    Article  PubMed  Google Scholar 

  44. Hendrix RJ, Damle A, Williams C, Harris A, Spanakis S, Lambert DH, Lambert LA. Restrictive Intraoperative fluid therapy is associated with decreased morbidity and length of stay following hyperthermic intraperitoneal chemoperfusion. Ann Surg Oncol. 2019;26(2):490–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-018-07092-y. Epub 2018 Dec 4 PMID: 30515670.

    Article  PubMed  Google Scholar 

  45. Romagnoli S, Ricci Z. Postoperative acute kidney injury. Minerva Anestesiol. 2015;81(6):684–96 Epub 2014 Jul 24 PMID: 25057935.

    CAS  PubMed  Google Scholar 

  46. Ghaferi AA, Birkmeyer JD, Dimick JB. Complications, failure to rescue, and mortality with major inpatient surgery in medicare patients. Ann Surg. 2009;250(6):1029–34. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/sla.0b013e3181bef697. IF:7.5Q1 PMID: 19953723.

    Article  PubMed  Google Scholar 

  47. Garg AX, Kurz A, Sessler DI, Cuerden M, Robinson A, Mrkobrada M, Parikh CR, Mizera R, Jones PM, Tiboni M, Font A, Cegarra V, Gomez MF, Meyhoff CS, VanHelder T, Chan MT, Torres D, Parlow J, ClanchetMde N, Amir M, Bidgoli SJ, Pasin L, Martinsen K, Malaga G, Myles P, Acedillo R, Roshanov PS, Walsh M, Dresser G, Kumar P, Fleischmann E, Villar JC, Painter T, Biccard B, Bergese S, Srinathan S, Cata JP, Chan V, Mehra B, Wijeysundera DN, Leslie K, Forget P, Whitlock R, Yusuf S, Devereaux PJ, POISE-2 Investigators. Perioperative aspirin and clonidine and risk of acute kidney injury: a randomized clinical trial. JAMA. 2014;312(21):2254–64. https://doiorg.publicaciones.saludcastillayleon.es/10.1001/jama.2014.15284. PMID: 25399007.

    Article  CAS  PubMed  Google Scholar 

  48. Biteker M, Dayan A, Tekkeşin Aİ, Can MM, Taycı İ, İlhan E, Şahin G. Incidence, risk factors, and outcomes of perioperative acute kidney injury in noncardiac and nonvascular surgery. Am J Surg. 2014;207(1):53–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.amjsurg.2013.04.006. Epub 2013 Sep 17 PMID: 24050540.

    Article  PubMed  Google Scholar 

  49. Mathis MR, Naik BI, Freundlich RE, Shanks AM, Heung M, Kim M, Burns ML, Colquhoun DA, Rangrass G, Janda A, Engoren MC, Saager L, Tremper KK, Kheterpal S, Aziz MF, Coffman T, Durieux ME, Levy WJ, Schonberger RB, Soto R, Wilczak J, Berman MF, Berris J, Biggs DA, Coles P, Craft RM, Cummings KC, Ellis TA 2nd, Fleishut PM, Helsten DL, Jameson LC, van Klei WA, Kooij F, LaGorio J, Lins S, Miller SA, Molina S, Nair B, Paganelli WC, Peterson W, Tom S, Wanderer JP, Wedeven C, Multicenter Perioperative Outcomes Group Investigators. Preoperative risk and the association between hypotension and postoperative acute kidney injury. Anesthesiology. 2020;132(3):461–75. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/ALN.0000000000003063. Erratum. In: Anesthesiology. 2020 Apr; 132(4):937. 10.1097/ALN.0000000000003144. PMID: 31794513; PMCID: PMC7015776.

    Article  PubMed  Google Scholar 

  50. Strasser B, Arvandi M, Siebert U. Resistance training, visceral obesity and inflammatory response: a review of the evidence. Obes Rev. 2012;13(7):578–91. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1467-789X.2012.00988x. IF: 8.0 Q1 . Epub 2012 Mar 2. PMID: 22385646IF: 8.0 Q1.

    Article  CAS  PubMed  Google Scholar 

  51. Ortiz VE, Kwo J. Obesity: physiologic changes and implications for preoperative management. BMC Anesthesiol. 2015;4(15):97. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12871-015-0079-8. PMID:26141622;PMCID:PMC4491231.

    Article  Google Scholar 

  52. Sun M, da Silva M, Bjørge T, Fritz J, Mboya IB, Jerkeman M, Stattin P, Wahlström J, Michaëlsson K, van Guelpen B, Magnusson PKE, Sandin S, Yin W, Lagerros YT, Ye W, Nwaru B, Kankaanranta H, Lönnberg L, Chabok A, Isaksson K, Pedersen NL, Elmståhl S, Lind L, Hedman L, Häggström C, Stocks T. Body mass index and risk of over 100 cancer forms and subtypes in 4.1 million individuals in Sweden: the Obesity and Disease Development Sweden (ODDS) pooled cohort study. Lancet Reg Health Eur. 2024;20(45):101034. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.lanepe.2024.101034. PMID: 39253735; PMCID: PMC11381908.

    Article  Google Scholar 

  53. Ghimire J, Collins ME, Snarski P, King AN, Ruiz E, Iftikhar R, Penrose HM, Moroz K, Rorison T, Baddoo M, Naeem MA, Zea AH, Magness ST, Flemington EF, Crawford SE, Savkovic SD. Obesity facilitated colon cancer progression is mediated by increased diacylglycerol o-acyltransferases 1 and 2 (DGAT1/2) levels. Gastroenterology. 2024;S0016–5085(24):05464–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1053/j.gastro.2024.09.011. Epub ahead of print. PMID: 39299402.

    Article  CAS  Google Scholar 

  54. Lysaght J, Conroy MJ. The multifactorial effect of obesity on the effectiveness and outcomes of cancer therapies. Nat Rev Endocrinol. 2024. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41574-024-01032-5. Epub ahead of print. PMID: 39313571.

  55. Mullen JT, Davenport DL, Hutter MM, Hosokawa PW, Henderson WG, Khuri SF, Moorman DW. Impact of body mass index on perioperative outcomes in patients undergoing major intra-abdominal cancer surgery. Ann Surg Oncol. 2008;15(8):2164–72. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-008-9990-2. Epub 2008 Jun 12 PMID: 18548313.

    Article  PubMed  Google Scholar 

  56. Hirano Y, Kaneko H, Konishi T, Itoh H, Matsuda S, Kawakubo H, Uda K, Matsui H, Fushimi K, Itano O, Yasunaga H, Kitagawa Y. Impact of body mass index on major complications, multiple complications, in-hospital mortality, and failure to rescue after esophagectomy for esophageal cancer: a nationwide inpatient database study in Japan. Ann Surg. 2023;277(4):e785–92. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/SLA.0000000000005321. IF: 7.5 Q1 . Epub 2021 Nov 23. PMID: 35129484IF: 7.5 Q1.

    Article  PubMed  Google Scholar 

  57. Veterans Affairs Total Parenteral Nutrition Cooperative Study Group. Perioperative total parenteral nutrition in surgical patients. N Engl J Med. 1991;325(8):525–32. https://doiorg.publicaciones.saludcastillayleon.es/10.1056/NEJM199108223250801. PMID: 1906987.

    Article  Google Scholar 

  58. Palma S, Cosano A, Mariscal M, Martínez-Gallego G, Medina-Cuadros M, Delgado-Rodríguez M. Cholesterol and serum albumin as risk factors for death in patients undergoing general surgery. Br J Surg. 2007;94(3):369–75. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/bjs.5626. PMID: 17279492.

    Article  CAS  PubMed  Google Scholar 

  59. Jacquet P, Sugarbaker PH. Clinical research methodologies in diagnosis and staging of patients with peritoneal carcinomatosis. Cancer Treat Res. 1996;82:359–74. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/978-1-4613-1247-5_23. PMID: 8849962.

    Article  CAS  PubMed  Google Scholar 

  60. Swellengrebel HA, Zoetmulder FA, Smeenk RM, Antonini N, Verwaal VJ. Quantitative intra-operative assessment of peritoneal carcinomatosis - a comparison of three prognostic tools. Eur J Surg Oncol. 2009;35(10):1078–84. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejso.2009.02.010. Epub 2009 Mar 13 PMID: 19285828.

    Article  CAS  PubMed  Google Scholar 

  61. Gilly FN, Cotte E, Brigand C, Monneuse O, Beaujard AC, Freyer G, Glehen O. Quantitative prognostic indices in peritoneal carcinomatosis. Eur J Surg Oncol. 2006;32(6):597–601. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejso.2006.03.002. Epub 2006 Apr 17 PMID: 16617003.

    Article  CAS  PubMed  Google Scholar 

  62. Portilla AG, Shigeki K, Dario B, Marcello D. The intraoperative staging systems in the management of peritoneal surface malignancy. J Surg Oncol. 2008;98(4):228–31. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/jso.21068. PMID: 18726882.

    Article  PubMed  Google Scholar 

  63. Narasimhan V, Tan S, Kong J, Pham T, Michael M, Ramsay R, Warrier S, Heriot A. Prognostic factors influencing survival in patients undergoing cytoreductive surgery with hyperthermic intraperitoneal chemotherapy for isolated colorectal peritoneal metastases: a systematic review and meta-analysis. Colorectal Dis. 2020;22(11):1482–95. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/codi.15003. IF:2.9Q1 Epub 2020 Feb 27 PMID: 32027455.

    Article  CAS  PubMed  Google Scholar 

  64. Grams ME, Sang Y, Ballew SH, Gansevoort RT, Kimm H, Kovesdy CP, Naimark D, Oien C, Smith DH, Coresh J, Sarnak MJ, Stengel B, Tonelli M, CKD Prognosis Consortium. A meta-analysis of the association of estimated gfr, albuminuria, age, race, and sex with acute kidney injury. Am J Kidney Dis. 2015;66(4):591–601. https://doiorg.publicaciones.saludcastillayleon.es/10.1053/j.ajkd.2015.02.337. IF: 9.4 Q1 . Epub 2015 May 2. PMID: 25943717; PMCID: PMC4584180.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Privratsky JR, Fuller M, Raghunathan K, Ohnuma T, Bartz RR, Schroeder R, Price TM, Martinez MR, Sigurdsson MI, Mathis MR, Naik B, Krishnamoorthy V. Postoperative acute kidney injury by age and sex: a retrospective cohort association study. Anesthesiology. 2023;138(2):184–94. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/ALN.0000000000004436. IF:9.1Q1.PMID:36512724;PMCID:PMC10439699.

    Article  CAS  PubMed  Google Scholar 

  66. Anderson S, Eldadah B, Halter JB, Hazzard WR, Himmelfarb J, Horne FM, Kimmel PL, Molitoris BA, Murthy M, O’Hare AM, Schmader KE, High KP. Acute kidney injury in older adults. J Am Soc Nephrol. 2011;22(1):28–38. https://doiorg.publicaciones.saludcastillayleon.es/10.1681/ASN.2010090934. PMID: 21209252.

    Article  PubMed  Google Scholar 

  67. Hoang K, Tan JC, Derby G, Blouch KL, Masek M, Ma I, Lemley KV, Myers BD. Determinants of glomerular hypofiltration in aging humans. Kidney Int. 2003;64(4):1417–24. https://doiorg.publicaciones.saludcastillayleon.es/10.1046/j.1523-1755.2003.00207.x. PMID: 12969161.

    Article  PubMed  Google Scholar 

  68. Fuiano G, Sund S, Mazza G, Rosa M, Caglioti A, Gallo G, Natale G, Andreucci M, Memoli B, De Nicola L, Conte G. Renal hemodynamic response to maximal vasodilating stimulus in healthy older subjects. Kidney Int. 2001;59(3):1052–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1046/j.1523-1755.2001.0590031052.x. IF:14.8Q1 PMID: 11231360.

    Article  CAS  PubMed  Google Scholar 

  69. James MT, Hemmelgarn BR, Wiebe N, Pannu N, Manns BJ, Klarenbach SW, Tonelli M, Alberta Kidney Disease Network. Glomerular filtration rate, proteinuria, and the incidence and consequences of acute kidney injury: a cohort study. Lancet. 2010;376(9758):2096–103. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0140-6736(10)61271-8. Epub 2010 Nov 20. PMID: 21094997.

    Article  PubMed  Google Scholar 

  70. James MT, Grams ME, Woodward M, Elley CR, Green JA, Wheeler DC, de Jong P, Gansevoort RT, Levey AS, Warnock DG, Sarnak MJ, CKD Prognosis Consortium. A Meta-analysis of the Association of Estimated GFR, Albuminuria, Diabetes Mellitus, and Hypertension With Acute Kidney Injury. Am J Kidney Dis. 2015;66(4):602–12. https://doiorg.publicaciones.saludcastillayleon.es/10.1053/j.ajkd.2015.02.338. IF: 9.4 Q1 . Epub 2015 May 11. PMID: 25975964; PMCID: PMC4594211.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Gui Y, Palanza Z, Fu H, Zhou D. Acute kidney injury in diabetes mellitus: epidemiology, diagnostic, and therapeutic concepts. FASEB J. 2023;37(4):e22884. https://doiorg.publicaciones.saludcastillayleon.es/10.1096/fj.202201340RR. PMID:36943403;PMCID:PMC10602403.

    Article  CAS  PubMed  Google Scholar 

  72. Liu S, Gui Y, Wang MS, Zhang L, Xu T, Pan Y, Zhang K, Yu Y, Xiao L, Qiao Y, Bonin C, Hargis G, Huan T, Yu Y, Tao J, Zhang R, Kreutzer DL, Zhou Y, Tian XJ, Wang Y, Fu H, An X, Liu S, Zhou D. Serum integrative omics reveals the landscape of human diabetic kidney disease. Mol Metab. 2021;54:101367. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.molmet.2021.101367. Epub 2021 Nov 1. PMID: 34737094; PMCID: PMC8609166.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Salmasi V, Maheshwari K, Yang D, Mascha EJ, Singh A, Sessler DI, Kurz A. Relationship between Intraoperative hypotension, defined by either reduction from baseline or absolute thresholds, and acute kidney and myocardial injury after noncardiac surgery: a retrospective cohort analysis. Anesthesiology. 2017;126(1):47–65. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/ALN.0000000000001432. PMID: 27792044.

    Article  PubMed  Google Scholar 

  74. Walsh M, Devereaux PJ, Garg AX, Kurz A, Turan A, Rodseth RN, Cywinski J, Thabane L, Sessler DI. Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery: toward an empirical definition of hypotension. Anesthesiology. 2013;119(3):507–15. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/ALN.0b013e3182a10e26. PMID: 23835589.

    Article  PubMed  Google Scholar 

  75. van Eden WJ, Kok NFM, Woensdregt K, Huitema ADR, Boot H, Aalbers AGJ. Safety of intraperitoneal Mitomycin C versus intraperitoneal oxaliplatin in patients with peritoneal carcinomatosis of colorectal cancer undergoing cytoreductive surgery and HIPEC. Eur J Surg Oncol. 2018;44(2):220–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejso.2017.10.216. Epub 2017 Nov 15 PMID: 29258720.

    Article  PubMed  Google Scholar 

  76. Prada-Villaverde A, Esquivel J, Lowy AM, Markman M, Chua T, Pelz J, Baratti D, Baumgartner JM, Berri R, Bretcha-Boix P, Deraco M, Flores-Ayala G, Glehen O, Gomez-Portilla A, González-Moreno S, Goodman M, Halkia E, Kusamura S, Moller M, Passot G, Pocard M, Salti G, Sardi A, Senthil M, Spiliotis J, Torres-Melero J, Turaga K, Trout R. The American Society of Peritoneal Surface Malignancies evaluation of HIPEC with Mitomycin C versus Oxaliplatin in 539 patients with colon cancer undergoing a complete cytoreductive surgery. J Surg Oncol. 2014;110(7):779–85. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/jso.23728. Epub 2014 Aug 2 PMID: 25088304.

    Article  CAS  PubMed  Google Scholar 

  77. Kapoor R, Robinson KA, Cata JP, Owusu-Agyemang P, Soliz JM, Hernandez M, Mansfield P, Badgwell B. Assessment of nephrotoxicity associated with combined cisplatin and mitomycin C usage in laparoscopic hyperthermic intraperitoneal chemotherapy. Int J Hyperthermia. 2019;36(1):493–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/02656736.2019.1597175. Epub 2019 Apr 1 PMID: 30935256.

    Article  CAS  PubMed  Google Scholar 

  78. Vachez E, Kefleyesus A, Bakrin N, Ranchon F, Rioufol C, Vassal O, Al-Hadeedi O, Kepenekian V, Glehen O. Eliminating the need for preoperative intravenous hyperhydration: Sodium thiosulfate as nephrotoxicity prevention in HIPEC-treated patients - A retrospective analysis. Eur J Surg Oncol. 2024;50(2):107955. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejso.2024.107955. Epub 2024 Jan 6. PMID: 38219699.

    Article  PubMed  Google Scholar 

  79. Senguttuvan RN, Santiago NL, Han ES, Lee B, Lee S, Lin WC, Kebria M, Hakim A, Lin JF, Wakabayashi MT, Ruel N, Tinsley R, Eng M, Stewart DB, Wang EW, Paz BI, Wu X, Cho H, Liang WS, Rodriguez-Rodriguez L, Cristea MC, Raoof M, Dellinger TH. Impact of sodium thiosulfate on prevention of nephrotoxicities in HIPEC: an ancillary evaluation of cisplatin-induced toxicities in ovarian cancer. Ann Surg Oncol. 2023;30(13):8144–55. https://doiorg.publicaciones.saludcastillayleon.es/10.1245/s10434-023-14216-6. Epub 2023 Sep 14. PMID: 37710139; PMCID: PMC10625947.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We sincerely thank all the researchers who contributed to our research.

Funding

This work was supported by the Leading Innovation Specialist Support Program of Guangdong Province, the Science and Technology Planning Project of Ganzhou (No. 202101074816), the National Key Clinical Specialty Construction Project (2021–2024, No. 2022YW030009), the Science and Technology Plan of Guangzhou, Guangdong Province, China (No. 202201011416), the Ganzhou Zhanggong District Major Projects (2022–23-6) and the National Natural Science Foundation of China (No. 82260501).

Author information

Authors and Affiliations

  1. Gannan Medical University, Ganzhou, China

    Dengzhuo Chen, Jinghui Li, Liang Wen, Linfeng Liu & Xueqing Yao

  2. Ganzhou Hospital of Guangdong Provincial People’s Hospital, Ganzhou Municipal Hospital, Ganzhou, China

    Dengzhuo Chen, Yongli Ma, Jinghui Li, Liang Wen, Linfeng Liu, Guosheng Zhang, Hongkai Hu & Xueqing Yao

  3. Department of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China

    Dengzhuo Chen, Yongli Ma, Jinghui Li, Liang Wen, Linfeng Liu, Chengzhi Huang & Xueqing Yao

Authors
  1. Dengzhuo Chen
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Yongli Ma
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Jinghui Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Liang Wen
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Linfeng Liu
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Guosheng Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Hongkai Hu
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Chengzhi Huang
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Xueqing Yao
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Conception/design: CDZ, JL, CH,HK, WL, and XY. Provision of study material or patients: CDZ, JL, YM,LF, WL, and GZ. Data collection and/or assembly: JL, YM, WL,HK, and GZ. Data analysis and interpretation: CDZ, JL, YM, WL, GZ, CH, HK, and YX. Manuscript writing: CDZ, JL, YM,LL, WL, GZ, CH, JW, and YX. Final approval of the manuscript: CDZ, JL, YM, WL, GZ,HK, CH, WL, and YX.

Corresponding authors

Correspondence to Hongkai Hu, Chengzhi Huang or Xueqing Yao.

Ethics declarations

Ethics approval and consent to participate

Our study does not require approval since it is a meta-analysis.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, D., Ma, Y., Li, J. et al. Risk factors for postoperative acute kidney injury after cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy: a meta-analysis and systematic review. World J Surg Onc 23, 40 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12957-025-03657-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12957-025-03657-w

Keywords

World Journal of Surgical Oncology

ISSN: 1477-7819

Contact us