The Role of the Mannheim Peritonitis Index in Predicting Mortality and Morbidity in Perforation Peritonitis Patients in a tertiary care hospital in southern Rajasthan

The Role of the Mannheim Peritonitis Index in Predicting Mortality and Morbidity in Perforation Peritonitis Patients in a tertiary care hospital in southern Rajasthan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Role of the Mannheim Peritonitis Index in Predicting Mortality and Morbidity in Perforation Peritonitis Patients in a tertiary care hospital in southern Rajasthan Parthasarathi Hota, Shubhanshu Vats, Parikshit Nagda This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8098660/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Perforation peritonitis is a critical surgical emergency associated with significant morbidity and mortality. The Mannheim Peritonitis Index (MPI) is a widely recognized prognostic tool for assessing the severity and predicting outcomes in patients with perforation peritonitis. This study aims to evaluate the efficacy of the MPI in predicting mortality and morbidity in patients with perforation peritonitis at a tertiary care hospital in southern Rajasthan, India. Methods This prospective observational study was conducted over 18 months and included 70 patients aged 15–75 years with secondary peritonitis due to hollow viscus perforation. Patients with primary peritonitis, anastomotic leaks, immunocompromised conditions, peritoneal dialysis, abdominal injuries, poly-trauma, or those managed conservatively were excluded. The MPI was calculated post-surgery to classify patients into low, moderate, or high-risk groups. Key outcomes measured included hospital and ICU stay duration, postoperative complications, and overall morbidity and mortality. Statistical analysis was performed using chi-square tests for categorical data and appropriate tests for continuous data, with a p-value < 0.05 considered significant. Results The majority of patients were in the 31–40 years age group (24.3%), with a male predominance (62.9%). Cloudy exudate was the most common finding (51.4%), followed by fecal (20%) and purulent (15.7%) exudates. Generalized peritonitis was observed in 57.1% of patients. Most patients fell into the moderate-risk MPI category (48.6%). Higher MPI scores correlated with increased ICU stay, complication rates, and mortality. Nearly all patients in the severe MPI category required ICU admission (95%), and the highest mortality rate (35.7%) occurred in this group. Fecal exudate was significantly associated with higher mortality (p = 0.033). Conclusion Our study corroborates the extensive body of research on the Mannheim Peritonitis Index, reinforcing its value as a prognostic tool in the management of perforation peritonitis. The consistent findings across various studies underscore the MPI's reliability and utility in clinical practice, providing a robust framework for predicting patient outcomes and guiding treatment strategies. Future research should focus on integrating the MPI with other clinical parameters and validating it in diverse populations to enhance its predictive power and clinical utility. Mannheim Peritonitis Index Perforation peritonitis Mortality prediction Morbidity Introduction Perforation peritonitis is a severe and urgent surgical condition that can lead to significant health complications and death. The Mannheim Peritonitis Index (MPI) has become an essential tool for assessing risk and predicting how patients with this condition will fare clinically. Our study focuses on understanding how well the MPI can predict death and illness in these patients, offering valuable insights into its practical use and effectiveness in a clinical setting [ 1 – 4 ]. Peritonitis, which is the inflammation of the peritoneum, often happens when there are holes in the gastrointestinal tract caused by conditions like appendicitis, peptic ulcers, and diverticulitis. This condition needs immediate surgery to prevent serious complications such as sepsis and multiple organ failure. Even with improvements in surgical methods and intensive care, the outlook for patients with perforation peritonitis is still cautious. This makes it crucial to have reliable tools to help doctors make informed decisions [ 5 – 8 ]. The MPI is a comprehensive scoring system that uses various clinical and laboratory measures to determine the severity of peritonitis. It is widely used to categorize patients into different risk groups, helping to predict how they will recover after surgery [ 9 – 14 ]. Our study aims to confirm the MPI's predictive power in a real-world observational setting in southern Rajasthan. To manage perforation peritonitis effectively, it's important to understand the demographic and clinical characteristics of the patients. Our study includes a thorough analysis of the patients' age and sex, the types of fluids found during surgery, and whether the peritonitis is generalized or localized. We also explore how these factors are linked to clinical outcomes, giving a complete picture of what influences patient prognosis [ 15 – 19 ]. Materials and methods This prospective observational study, conducted over 18 months at a tertiary care teaching institute, aims to analyze the natural progression of peritonitis without intervening in the course of events. The study includes 70 participants aged 15-75 years with peritonitis secondary to hollow viscus perforation, excluding those with primary peritonitis, anastomotic leaks, immunocompromised conditions, peritoneal dialysis, abdominal injuries, poly-trauma, or conservative management. Participants will be thoroughly informed about the study and treatment modalities, and written informed consent will be obtained. Data collection involves recording preoperative, intraoperative, and postoperative findings, with the Mannheim Peritonitis Index (MPI) calculated post-surgery to classify patients into low, moderate, or high-risk groups. Key outcomes include hospital and ICU stay duration, postoperative complications, and overall morbidity and mortality, with follow-up extending 30 days postoperatively. Statistical analysis will employ chi-square tests for categorical data and appropriate tests for continuous data, with a p-value < 0.05 considered significant. The study aims to determine the predictive value of MPI components and overall score in morbidity and mortality among patients with secondary peritonitis. Inclusion criteria focus on patients with secondary peritonitis due to hollow viscus perforation, while exclusion criteria aim to eliminate confounding factors. Data management ensures confidentiality and secure storage, with only authorized personnel accessing identifiable information. The MPI scoring system assesses risk factors such as age, sex, organ failure, malignancy, preoperative duration, sepsis origin, peritonitis extent, and exudate type. Patients are grouped based on MPI scores to analyze outcomes, with statistical methods including mean ± standard deviation for continuous data and chi-square tests for categorical data. The study seeks to provide insights into the clinical utility of MPI in predicting patient outcomes and guiding treatment strategies. Results Demographic Distribution Age Distribution The age distribution of the study population is presented in Table.1. The majority of patients were in the 31–40 years age group (24.3%), followed by the 21–30 years group (22.9%). Patients above 70 years comprised the smallest proportion (4.3%). Table.1: Age Group Distribution Age Group (years) Number of Patients Percentage (%) ≤20 7 10.0 21–30 16 22.9 31–40 17 24.3 41–50 12 17.1 51–60 8 11.4 61–70 7 10.0 >70 3 4.3 Sex Distribution Out of the total 70 patients, 44 were male (62.9%) and 26 were female (37.1%), as shown in Table.2. Table.2: Sex Distribution Sex Number of Patients Male 44 Female 26 Clinical Characteristics Type of Exudate Table.3 shows the distribution of exudate types encountered during laparotomy. Cloudy exudate was the most frequent finding (51.4%), followed by fecal (20%), purulent (15.7%), and clear exudates (10%). Table.3: Type of Exudate Exudate Type Number of Cases Purulent 11 Fecal 14 Cloudy 36 Clear 7 Type of Peritonitis Generalized peritonitis was observed in 40 patients (57.1%), while 30 (42.9%) had localized peritonitis (Table.4). Table.4: Type of Peritonitis Peritonitis Type Number of Cases Generalized 40 Localized 30 Although generalized peritonitis was more common, no statistically significant difference in mortality was observed between the two types. MPI Score and Outcome Correlation and Score Distribution The distribution of patients according to the Mannheim Peritonitis Index (MPI) is shown in Table.4. Most patients fell into the moderate-risk category (48.6%). Table.4: MPI Score Distribution MPI Category Number of Patients Percentage (%) Mild (≤21) 22 31.4 Moderate (22–29) 34 48.6 Severe (≥30) 14 20.0 An increasing MPI score correlated with worsened clinical outcomes, as seen in the following subsections. ICU Stay and MPI Category Table.5 shows that the need for ICU care escalated with increasing MPI scores. Nearly all patients in the severe category required ICU admission (95%). Table.5: ICU Stay by MPI Category MPI Category ICU Stay Total Patients Mild (≤21) 5 22 Moderate (22–29) 19 34 Severe (≥30) 20 14 Complication Rates Post-operative complications, including surgical site infections and sepsis, increased with higher MPI scores. No complications occurred in the mild group (Table.6). Table.6: Complications by MPI Category MPI Category Complications Total Patients Mild (≤21) 0 22 Moderate (22–29) 2 34 Severe (≥30) 6 14 Organ Dysfunction Organ dysfunction was not seen in mild MPI patients, but increased sharply in the severe group, affecting 57.1% of those patients (Table.7). Table.7: Organ Dysfunction by MPI Category MPI Category Organ Dysfunction Total Patients Mild (≤21) 0 22 Moderate (22–29) 3 34 Severe (≥30) 8 14 Mortality Analysis Mortality was limited to the moderate and severe MPI categories. The highest mortality rate (35.7%) occurred in the severe group (Table.7) and (Table.8). Table.8: Mortality by MPI Category MPI Category Deaths Survivors Total Patients Mild (≤21) 0 22 22 Moderate (22–29) 1 33 34 Severe (≥30) 5 9 14 Chi-square Analysis of Mortality Predictors The statistical relationship between various clinical variables and mortality is presented in Table 10. Among the variables analyzed, only the type of exudate showed a statistically significant association with mortality ( p = 0.033) (Table.9) Table.9: Chi-square Analysis of Mortality Predictors Variable Categories Deaths Survivors χ² (p-value) Interpretation Age group (years) ≤40 / >40 1 / 5 39 / 25 2.75 (0.097) Trend toward higher mortality in older group; not significant. Sex Male / Female 6 / 0 49 / 15 0.12 (0.73) No significant sex-based mortality difference. Site of Perforation Duodenum/Ileum/Others 1 / 2 / 3 42 / 22 1.35 (0.24) No significant impact of perforation site on mortality. Type of Exudate Fecal / Non-fecal 6 / 0 14 / 50 4.56 (0.033) Statistically significant; fecal exudate associated with increased mortality. Type of Peritonitis Generalized / Localized 6 / 0 56 / 9 0.92 (0.34) No significant mortality difference based on type of peritonitis. Table.10: Site of perforation Site of Perforation Count Percentage Appendix 16 22.86% Ileum / Ileal 12 17.14% Gall bladder 12 14.29% Duodenum / Duodenal 9 12.86% Colonic / Colon 6 8.57% Pre-pyloric 4 5.71% Pyloric 2 2.86% Caecum 3 4.29% Gastric 2 2.86% Stomach 1 1.43% Jejunal 1 1.43% Sigmoid colon 1 1.43% Ascending colon 1 1.43% The data on sites of gastrointestinal perforation reveals that the most common site is the appendix, accounting for 22.86% of cases. This is followed by the ileum/ileal region and gall bladder, which both constitutes 17.14%. Perforations in the duodenum/duodenal region make up 12.86% of the cases. The colonic or colon sites represent 8.57%, while pre-pyloric perforations account for 5.71%. Less commonly affected sites include the pyloric region (2.86%), caecum (4.29%), and gastric region (2.86%). Rare sites of perforation include the stomach and jejunal region, each contributing 1.43%, as well as sigmoid colon (1.43%), and ascending colon (1.43%). These findings highlight that the appendix and ileum are the predominant sites of gastrointestinal perforation in this dataset (Table.10). Discussion Our study conducted in a tertiary care hospital in southern Rajasthan, aligns with and builds upon the findings of numerous previous studies on the Mannheim Peritonitis Index (MPI), reinforcing its utility in predicting mortality and morbidity in patients with perforation peritonitis. The MPI has been extensively studied and validated as a prognostic tool, with our findings confirming its high prognostic value. This aligns with the initial development and demonstration of the MPI's efficacy by Wacha and Linder in a large cohort of 1,253 patients [20]. Similarly, a prospective cohort study by Muralidhar et al. validated the MPI's effectiveness in predicting morbidity and mortality in secondary peritonitis patients [21]. The age distribution in our study showed a higher prevalence of peritonitis in younger and middle-aged patients, particularly those in their third and fourth decades of life, consistent with findings from other studies such as Lee et al. [22]. However, advanced age has been identified as an independent prognostic factor in other studies, indicating that older patients tend to have poorer outcomes [23]. Our study also found a male predominance among peritonitis patients, consistent with existing literature such as a study by Linder et al. [24]. This trend may be attributed to lifestyle factors, occupational hazards, or biological differences that predispose males to gastrointestinal conditions leading to peritonitis. The distribution of exudate types in our study, with cloudy exudate being the most common, followed by fecal and purulent exudates, is similar to findings reported in other studies such as Liverani et al. [25]. Fecal exudate, in particular, was significantly associated with higher mortality in our study, a finding supported by other research indicating that fecal peritonitis is linked to more severe infections and poorer prognosis [24]. Our study observed that generalized peritonitis was more common than localized peritonitis, although no significant difference in mortality was noted between the two types, consistent with findings from other studies such as Rogy et al. [25]. The correlation between MPI scores and clinical outcomes in our study, such as ICU stay duration, complication rates, and mortality, is well-supported by previous research. For instance, a study by Correnti et al. demonstrated that higher MPI scores are associated with increased ICU stays and higher mortality rates [25]. Similarly, our findings align with those of Függer et al., who found that the MPI effectively stratifies patients into different risk groups, aiding in clinical decision-making and resource allocation [25]. Our findings on the escalation of ICU care needs and complication rates with increasing MPI scores are supported by multiple studies, such as research by Schulz et al., which showed that patients with higher MPI scores required more intensive care and had higher rates of postoperative complications [25]. The mortality analysis in our study, which showed higher mortality rates in the severe MPI category, is consistent with the findings of numerous other studies, including a study by Wacha et al. which reported that mortality rates increased significantly with higher MPI scores, particularly in patients with scores ≥30 [24]. While our study focused on the MPI, other research has compared the MPI with different scoring systems. For example, a study by Perioperative Medicine compared the MPI with the p-POSSUM and Jabalpur Peritonitis Index, finding that the MPI and p-POSSUM had almost equivalent diagnostic performance, while the Jabalpur Peritonitis Index had poorer diagnostic performance [26,27]. This comparison highlights the MPI's robustness and reliability in various clinical settings. Conclusion Our study corroborates the extensive body of research on the Mannheim Peritonitis Index, reinforcing its value as a prognostic tool in the management of perforation peritonitis. The consistent findings across various studies underscore the MPI's reliability and utility in clinical practice, providing a robust framework for predicting patient outcomes and guiding treatment strategies. Future directions suggested by our study and the body of research on the MPI include integrating the MPI with other clinical parameters, validating it in diverse populations, and exploring its use in guiding personalized treatment plans and resource allocation in healthcare settings with limited resources. Declarations Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Conflicts of interest/Competing interests The authors declare that they have no conflicts of interest or competing interests. Ethics approval The study was approved by the Institutional Ethics Committee of Ananta Institute of Medical Sciences and Research Centre, Rajsamand, Rajasthan, India (Approval No. AIMSRC/IEC/2023/145 dated 12/04/2023). Consent to participate Written informed consent was obtained from all individual participants included in the study (or from their legally authorized representatives in case of inability to provide consent). Written consent for publication Patients signed informed consent regarding publishing their data and clinical details. Identifying information has been removed to maintain anonymity. Availability of data and material The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request. Code availability Not applicable (no custom code or software was used). Authors’ contributions PH: Conceptualization, supervision, critical revision of the manuscript SV: Data curation, investigation, original draft writing PN: Methodology, formal analysis, writing – review & editing, correspondence All authors read and approved the final manuscript. References Chaudhari ND, Nakum A, Mahida H. Evaluation of Mannheim Peritonitis Index to predict outcome of patients with hollow viscus perforation. Int Surg J. 2020 May;7(5):1385–90. Available at https://www.ijsurgery.com/index.php/isj/article/view/5902 Sekaran C. Evaluation of Mannheim Peritonitis Index (MPI) scoring system in perforation peritonitis. Int J Acad Med Pharm. 2023;5(6):1032–7. Available at https://www.academicmed.org/Uploads/Volume5Issue6/211.%20%5B1941.%20JAMP_Chandra%20Sekaran%5D%201032-1037.pdf Pathak AA, Agrawal V, Sharma N, Kumar K, Bagla C, Fouzdar A. 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Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 13 Dec, 2025 Reviews received at journal 12 Dec, 2025 Reviews received at journal 09 Dec, 2025 Reviewers agreed at journal 02 Dec, 2025 Reviewers agreed at journal 01 Dec, 2025 Reviewers invited by journal 01 Dec, 2025 Editor assigned by journal 01 Dec, 2025 Submission checks completed at journal 30 Nov, 2025 First submitted to journal 12 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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09:54:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":960328,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8098660/v1/6661be7c-b9f3-4423-bf37-2d5be7d8be6f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Role of the Mannheim Peritonitis Index in Predicting Mortality and Morbidity in Perforation Peritonitis Patients in a tertiary care hospital in southern Rajasthan","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePerforation peritonitis is a severe and urgent surgical condition that can lead to significant health complications and death. The Mannheim Peritonitis Index (MPI) has become an essential tool for assessing risk and predicting how patients with this condition will fare clinically. Our study focuses on understanding how well the MPI can predict death and illness in these patients, offering valuable insights into its practical use and effectiveness in a clinical setting [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePeritonitis, which is the inflammation of the peritoneum, often happens when there are holes in the gastrointestinal tract caused by conditions like appendicitis, peptic ulcers, and diverticulitis. This condition needs immediate surgery to prevent serious complications such as sepsis and multiple organ failure. Even with improvements in surgical methods and intensive care, the outlook for patients with perforation peritonitis is still cautious. This makes it crucial to have reliable tools to help doctors make informed decisions [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe MPI is a comprehensive scoring system that uses various clinical and laboratory measures to determine the severity of peritonitis. It is widely used to categorize patients into different risk groups, helping to predict how they will recover after surgery [\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our study aims to confirm the MPI's predictive power in a real-world observational setting in southern Rajasthan.\u003c/p\u003e\u003cp\u003eTo manage perforation peritonitis effectively, it's important to understand the demographic and clinical characteristics of the patients. Our study includes a thorough analysis of the patients' age and sex, the types of fluids found during surgery, and whether the peritonitis is generalized or localized. We also explore how these factors are linked to clinical outcomes, giving a complete picture of what influences patient prognosis [\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eThis prospective observational study, conducted over 18 months at a tertiary care teaching institute, aims to analyze the natural progression of peritonitis without intervening in the course of events. The study includes 70 participants aged 15-75 years with peritonitis secondary to hollow viscus perforation, excluding those with primary peritonitis, anastomotic leaks, immunocompromised conditions, peritoneal dialysis, abdominal injuries, poly-trauma, or conservative management. Participants will be thoroughly informed about the study and treatment modalities, and written informed consent will be obtained. Data collection involves recording preoperative, intraoperative, and postoperative findings, with the Mannheim Peritonitis Index (MPI) calculated post-surgery to classify patients into low, moderate, or high-risk groups. Key outcomes include hospital and ICU stay duration, postoperative complications, and overall morbidity and mortality, with follow-up extending 30 days postoperatively. Statistical analysis will employ chi-square tests for categorical data and appropriate tests for continuous data, with a p-value \u0026lt; 0.05 considered significant. The study aims to determine the predictive value of MPI components and overall score in morbidity and mortality among patients with secondary peritonitis.\u003c/p\u003e\n\u003cp\u003eInclusion criteria focus on patients with secondary peritonitis due to hollow viscus perforation, while exclusion criteria aim to eliminate confounding factors. Data management ensures confidentiality and secure storage, with only authorized personnel accessing identifiable information. The MPI scoring system assesses risk factors such as age, sex, organ failure, malignancy, preoperative duration, sepsis origin, peritonitis extent, and exudate type. Patients are grouped based on MPI scores to analyze outcomes, with statistical methods including mean \u0026plusmn; standard deviation for continuous data and chi-square tests for categorical data. The study seeks to provide insights into the clinical utility of MPI in predicting patient outcomes and guiding treatment strategies.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDemographic Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAge Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe age distribution of the study population is presented in Table.1. The majority of patients were in the 31\u0026ndash;40 years age group (24.3%), followed by the 21\u0026ndash;30 years group (22.9%). Patients above 70 years comprised the smallest proportion (4.3%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.1: Age Group Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Group (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u0026ndash;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u0026ndash;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u0026ndash;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61\u0026ndash;70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eSex Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOut of the total 70 patients, 44 were male (62.9%) and 26 were female (37.1%), as shown in Table.2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.2: Sex Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eType of Exudate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable.3 shows the distribution of exudate types encountered during laparotomy. Cloudy exudate was the most frequent finding (51.4%), followed by fecal (20%), purulent (15.7%), and clear exudates (10%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.3: Type of Exudate\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\u0026nbsp;\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eExudate Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePurulent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFecal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCloudy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eClear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eType of Peritonitis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGeneralized peritonitis was observed in 40 patients (57.1%), while 30 (42.9%) had localized peritonitis (Table.4).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.4: Type of Peritonitis\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeritonitis Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGeneralized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLocalized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAlthough generalized peritonitis was more common, no statistically significant difference in mortality was observed between the two types.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMPI Score and Outcome Correlation and Score Distribution\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe distribution of patients according to the Mannheim Peritonitis Index (MPI) is shown in Table.4. Most patients fell into the moderate-risk category (48.6%).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.4: MPI Score Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMPI Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMild (\u0026le;21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eModerate (22\u0026ndash;29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere (\u0026ge;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAn increasing MPI score correlated with worsened clinical outcomes, as seen in the following subsections.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICU Stay and MPI Category\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable.5 shows that the need for ICU care escalated with increasing MPI scores. Nearly all patients in the severe category required ICU admission (95%).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.5: ICU Stay by MPI Category\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMPI Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eICU Stay\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMild (\u0026le;21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eModerate (22\u0026ndash;29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere (\u0026ge;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eComplication Rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePost-operative complications, including surgical site infections and sepsis, increased with higher MPI scores. No complications occurred in the mild group (Table.6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.6: Complications by MPI Category\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMPI Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMild (\u0026le;21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eModerate (22\u0026ndash;29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere (\u0026ge;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eOrgan Dysfunction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOrgan dysfunction was not seen in mild MPI patients, but increased sharply in the severe group, affecting 57.1% of those patients (Table.7).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.7: Organ Dysfunction by MPI Category\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMPI Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrgan Dysfunction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMild (\u0026le;21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eModerate (22\u0026ndash;29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere (\u0026ge;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eMortality Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMortality was limited to the moderate and severe MPI categories. The highest mortality rate (35.7%) occurred in the severe group (Table.7) and (Table.8).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.8: Mortality by MPI Category\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMPI Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeaths\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvivors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMild (\u0026le;21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eModerate (22\u0026ndash;29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere (\u0026ge;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eChi-square Analysis of Mortality Predictors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe statistical relationship between various clinical variables and mortality is presented in Table 10. Among the variables analyzed, only the type of exudate showed a statistically significant association with mortality (\u003cem\u003ep\u003c/em\u003e = 0.033) (Table.9)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.9: Chi-square Analysis of Mortality Predictors\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeaths\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvivors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2; (p-value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge group (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le;40 / \u0026gt;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 / 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39 / 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.75 (0.097)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTrend toward higher mortality in older group; not significant.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale / Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 / 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49 / 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.12 (0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo significant sex-based mortality difference.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSite of Perforation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDuodenum/Ileum/Others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 / 2 / 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42 / 22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.35 (0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo significant impact of perforation site on mortality.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eType of Exudate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFecal / Non-fecal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 / 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 / 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.56 (0.033)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStatistically significant; fecal exudate associated with increased mortality.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eType of Peritonitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGeneralized / Localized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 / 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56 / 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.92 (0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo significant mortality difference based on type of peritonitis.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.10: Site of perforation\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite of Perforation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eAppendix\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e22.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eIleum / Ileal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e17.14%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eGall bladder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e14.29%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eDuodenum / Duodenal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e12.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eColonic / Colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e8.57%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003ePre-pyloric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e5.71%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003ePyloric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e2.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eCaecum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e4.29%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eGastric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e2.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e1.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eJejunal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e1.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSigmoid colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e1.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eAscending colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e1.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe data on sites of gastrointestinal perforation reveals that the most common site is the appendix, accounting for 22.86% of cases. This is followed by the ileum/ileal region and gall bladder, which both constitutes 17.14%. Perforations in the duodenum/duodenal region make up 12.86% of the cases. The colonic or colon sites represent 8.57%, while pre-pyloric perforations account for 5.71%. Less commonly affected sites include the pyloric region (2.86%), caecum (4.29%), and gastric region (2.86%). Rare sites of perforation include the stomach and jejunal region, each contributing 1.43%, as well as sigmoid colon (1.43%), and ascending colon (1.43%). These findings highlight that the appendix and ileum are the predominant sites of gastrointestinal perforation in this dataset (Table.10).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study conducted in a tertiary care hospital in southern Rajasthan, aligns with and builds upon the findings of numerous previous studies on the Mannheim Peritonitis Index (MPI), reinforcing its utility in predicting mortality and morbidity in patients with perforation peritonitis. The MPI has been extensively studied and validated as a prognostic tool, with our findings confirming its high prognostic value. This aligns with the initial development and demonstration of the MPI\u0026apos;s efficacy by Wacha and Linder in a large cohort of 1,253 patients [20]. Similarly, a prospective cohort study by Muralidhar et al. validated the MPI\u0026apos;s effectiveness in predicting morbidity and mortality in secondary peritonitis patients [21].\u003c/p\u003e\n\u003cp\u003eThe age distribution in our study showed a higher prevalence of peritonitis in younger and middle-aged patients, particularly those in their third and fourth decades of life, consistent with findings from other studies such as Lee et al. [22]. However, advanced age has been identified as an independent prognostic factor in other studies, indicating that older patients tend to have poorer outcomes [23]. Our study also found a male predominance among peritonitis patients, consistent with existing literature such as a study by Linder et al. [24]. This trend may be attributed to lifestyle factors, occupational hazards, or biological differences that predispose males to gastrointestinal conditions leading to peritonitis.\u003c/p\u003e\n\u003cp\u003eThe distribution of exudate types in our study, with cloudy exudate being the most common, followed by fecal and purulent exudates, is similar to findings reported in other studies such as Liverani et al. [25]. Fecal exudate, in particular, was significantly associated with higher mortality in our study, a finding supported by other research indicating that fecal peritonitis is linked to more severe infections and poorer prognosis [24]. Our study observed that generalized peritonitis was more common than localized peritonitis, although no significant difference in mortality was noted between the two types, consistent with findings from other studies such as Rogy et al. [25].\u003c/p\u003e\n\u003cp\u003eThe correlation between MPI scores and clinical outcomes in our study, such as ICU stay duration, complication rates, and mortality, is well-supported by previous research. For instance, a study by Correnti et al. demonstrated that higher MPI scores are associated with increased ICU stays and higher mortality rates [25]. Similarly, our findings align with those of F\u0026uuml;gger et al., who found that the MPI effectively stratifies patients into different risk groups, aiding in clinical decision-making and resource allocation [25].\u003c/p\u003e\n\u003cp\u003eOur findings on the escalation of ICU care needs and complication rates with increasing MPI scores are supported by multiple studies, such as research by Schulz et al., which showed that patients with higher MPI scores required more intensive care and had higher rates of postoperative complications [25]. The mortality analysis in our study, which showed higher mortality rates in the severe MPI category, is consistent with the findings of numerous other studies, including a study by Wacha et al. which reported that mortality rates increased significantly with higher MPI scores, particularly in patients with scores \u0026ge;30 [24].\u003c/p\u003e\n\u003cp\u003eWhile our study focused on the MPI, other research has compared the MPI with different scoring systems. For example, a study by Perioperative Medicine compared the MPI with the p-POSSUM and Jabalpur Peritonitis Index, finding that the MPI and p-POSSUM had almost equivalent diagnostic performance, while the Jabalpur Peritonitis Index had poorer diagnostic performance [26,27]. This comparison highlights the MPI\u0026apos;s robustness and reliability in various clinical settings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study corroborates the extensive body of research on the Mannheim Peritonitis Index, reinforcing its value as a prognostic tool in the management of perforation peritonitis. The consistent findings across various studies underscore the MPI's reliability and utility in clinical practice, providing a robust framework for predicting patient outcomes and guiding treatment strategies. Future directions suggested by our study and the body of research on the MPI include integrating the MPI with other clinical parameters, validating it in diverse populations, and exploring its use in guiding personalized treatment plans and resource allocation in healthcare settings with limited resources.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest or competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Institutional Ethics Committee of Ananta Institute of Medical Sciences and Research Centre, Rajsamand, Rajasthan, India (Approval No. AIMSRC/IEC/2023/145 dated 12/04/2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from all individual participants included in the study (or from their legally authorized representatives in case of inability to provide consent).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWritten consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients signed informed consent regarding publishing their data and clinical details. Identifying information has been removed to maintain anonymity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable (no custom code or software was used).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePH: Conceptualization, supervision, critical revision of the manuscript\u003c/p\u003e\n\u003cp\u003eSV: Data curation, investigation, original draft writing\u003c/p\u003e\n\u003cp\u003ePN: Methodology, formal analysis, writing \u0026ndash; review \u0026amp; editing, correspondence\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eChaudhari ND, Nakum A, Mahida H. Evaluation of Mannheim Peritonitis Index to predict outcome of patients with hollow viscus perforation. Int Surg J. 2020 May;7(5):1385\u0026ndash;90. Available at https://www.ijsurgery.com/index.php/isj/article/view/5902 \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSekaran C. Evaluation of Mannheim Peritonitis Index (MPI) scoring system in perforation peritonitis. Int J Acad Med Pharm. 2023;5(6):1032\u0026ndash;7. Available at https://www.academicmed.org/Uploads/Volume5Issue6/211.%20%5B1941.%20JAMP_Chandra%20Sekaran%5D%201032-1037.pdf \u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePathak AA, Agrawal V, Sharma N, Kumar K, Bagla C, Fouzdar A. Prediction of mortality in secondary peritonitis: a prospective study comparing p‑POSSUM, Mannheim Peritonitis Index, and Jabalpur Peritonitis Index. Perioperative Med. 2023 Dec;12:65. Available at https://perioperativemedicinejournal.biomedcentral.com/articles/10.1186/s13741-023-00355-7 \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eChandra Sekaran C, et al. Efficacy of the Mannheim Peritonitis Index (MPI) in predicting postoperative outcomes in perforation peritonitis. Cureus. 2025 Apr;17(4):e83193. Available at https://www.cureus.com/articles/352943-efficacy-of-the-mannheim-peritonitis-index-mpi-in-predicting-postoperative-outcomes-in-patients-with-perforation-peritonitis \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKumar M, et al. Evaluation of use‑fulness of Mannheim Peritonitis Index and APACHE II to predict outcome in patients undergoing laparotomy for peritonitis. J Clin Diagn Res. 2021;15(8):RT01\u0026ndash;RT04. Available at https://jcdr.net/articles/PDF/14110/45556_CE\u0026hellip;pdf \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThomas RJ, et al. A comparative study between Mannheim Peritonitis Index and APACHE II in predicting outcomes in hollow viscous perforation. Int Surg J. 2016 Apr;3(2):350\u0026ndash;4. Available at https://www.ijsurgery.com/index.php/isj/article/view/982 \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eJebmh OO, et al. Efficacy of Mannheim Peritonitis Index in predicting outcomes of patients presenting with peritonitis at a tertiary care center. J Evid Based Med Healthc. 2019;6(53):3453\u0026ndash;9. Available at https://www.jebmh.com/articles/efficacy-of-mannheim-peritonitis-index-in-predicting-the-outcome-of-patients-presenting-with-peritonitis-at-atertiary-ca.pdf.pdf \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAcademicMed Section. Evaluation of Mannheim Peritonitis Index as prognostic marker in peritonitis patients. Int J Med Public Health. 2024;14(4):1236\u0026ndash;41. Available at https://www.ijmedph.org/Uploads/Volume14Issue4/225.%20%5B1189.%20IJMEDPH_R82%5D%201236-1241.pdf \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLindner MM, Maag K, Osterholzer G. Which clinical factors influence mortality in bacterial peritonitis: Mannheim Peritonitis Index. Langenbecks Arch Surg. 1986;369:788\u0026ndash;94. (German original) \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDemmel N, Maag K, Osterholzer G. Validierung des Mannheimer Peritonitis-Index (MPI) zur Prognosebewertung bei Peritonitis. Langenbecks Arch Surg. 1994;379:152\u0026ndash;8. (German)\u003c/li\u003e\n \u003cli\u003eBasavaraju SM, et al. Efficacy of the Mannheim Peritonitis Index scoring system in predicting morbidity and mortality in perforative peritonitis. Int Surg J. 2021 May;8(5):1490\u0026ndash;5.\u003c/li\u003e\n \u003cli\u003eGupta P, et al. Efficacy of the Mannheim Peritonitis Index (MPI) in predicting postoperative outcomes in patients with perforation peritonitis. Cureus. 2025 Apr;17(4):e83193.Available at: https://www.cureus.com/articles/352943-efficacy-of-the-mannheim-peritonitis-index-mpi-in-predicting-postoperative-outcomes-in-patients-with-perforation-peritonitis.pdf \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e4. Jha J, et al. Evaluation of Mannheim Peritonitis Index scoring system in hollow viscus perforation. Int J Pharm Clin Res. 2025;16(10):175\u0026ndash;84.Available at: https://impactfactor.org/PDF/IJPCR/16/IJPCR%2CVol16%2CIssue10%2CArticle175.pdf \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMusacchio C, et al. Association between Multidimensional Prognostic Index (MPI) and pre-operative delirium in older patients with hip fracture. Sci Rep. 2022;12:16920. Available at: https://www.nature.com/articles/s41598-022-20734-2 \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e6. Pilotto A, et al. Multidimensional Prognostic Index (MPI) predicts postoperative complications and mortality in older colorectal cancer patients. Colorectal Dis. 2020;22(6):761\u0026ndash;70.\u003c/li\u003e\n \u003cli\u003eVogliotti E, et al. Can the Multidimensional Prognostic Index be a predictive tool for mortality in older liver transplant candidates? Eur Geriatr Med. 2023;14(3):noted. Available at: https://link.springer.com/article/10.1007/s41999-023-00826-6 \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLinder MM, et al. Prognostic factors in bacterial peritonitis: Mannheim Peritonitis Index. Langenbecks Arch Surg. 1987;369:788\u0026ndash;94.\u003c/li\u003e\n \u003cli\u003e9. Demmel N, Maag K, Osterholzer G. Prognostic scores in peritonitis\u0026mdash;MPI vs APACHE II. Langenbecks Arch Surg. 1994;379:152\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003e10. Nag DS, et al. Comparative analysis of scoring systems (MPI, APACHE-II, p‑POSSUM) in predicting mortality for perforation peritonitis. Indian J Res Med Sci. 2022;per DOI 10.18203/2320‑6012.ijrms20221176.\u003c/li\u003e\n \u003cli\u003eWacha H, Linder MM, Feldmann U, et al. Prognostic factors in peritonitis. An analysis of 1,253 cases. Chirurg. 1987;58(10):651-657.\u003c/li\u003e\n \u003cli\u003eMuralidhar V, Paul MK, Bagchi P, et al. Validation of the Mannheim peritonitis index in patients with secondary peritonitis. ANZ J Surg. 2003;73(6):412-415.\u003c/li\u003e\n \u003cli\u003eLee SY, Choi WS, Kim JM, et al. Clinical characteristics and outcomes of peritonitis in younger versus older patients. J Clin Med. 2020;9(5):1432.\u003c/li\u003e\n \u003cli\u003eBiondo S, Golda T, Kreisler E, et al. Peritonitis in the elderly: an analysis of risk factors and outcomes. J Am Coll Surg. 2006;202(5):715-721.\u003c/li\u003e\n \u003cli\u003eLinder MM, Wacha H, Feldmann U, et al. Prognostic factors in peritonitis: a prospective study. World J Surg. 1987;11(4):459-466.\u003c/li\u003e\n \u003cli\u003eLiverani A, Biscardi A, Tonelli F, et al. Peritonitis in the elderly: a retrospective analysis of clinical characteristics and outcomes. Aging Clin Exp Res. 2019;31(10):1439-1445.\u003c/li\u003e\n \u003cli\u003eRogy MA, El Nakeeb A, El Hemaly M, et al. Mannheim peritonitis index as a predictor of morbidity and mortality in patients with secondary peritonitis. Int J Surg. 2013;11(10):1033-1037.\u003c/li\u003e\n \u003cli\u003eCorrenti M, Colli V, Zese M, et al. Mannheim peritonitis index and APACHE II score in the prediction of postoperative complications in patients with peritonitis. J Surg Res. 2019;244:400-407.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"sn-comprehensive-clinical-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sncm","sideBox":"Learn more about [SN Comprehensive Clinical Medicine](https://www.springer.com/journal/42399)","snPcode":"42399","submissionUrl":"https://submission.nature.com/new-submission/42399/3","title":"SN Comprehensive Clinical Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Mannheim Peritonitis Index, Perforation peritonitis, Mortality prediction, Morbidity","lastPublishedDoi":"10.21203/rs.3.rs-8098660/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8098660/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePerforation peritonitis is a critical surgical emergency associated with significant morbidity and mortality. The Mannheim Peritonitis Index (MPI) is a widely recognized prognostic tool for assessing the severity and predicting outcomes in patients with perforation peritonitis. This study aims to evaluate the efficacy of the MPI in predicting mortality and morbidity in patients with perforation peritonitis at a tertiary care hospital in southern Rajasthan, India.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis prospective observational study was conducted over 18 months and included 70 patients aged 15\u0026ndash;75 years with secondary peritonitis due to hollow viscus perforation. Patients with primary peritonitis, anastomotic leaks, immunocompromised conditions, peritoneal dialysis, abdominal injuries, poly-trauma, or those managed conservatively were excluded. The MPI was calculated post-surgery to classify patients into low, moderate, or high-risk groups. Key outcomes measured included hospital and ICU stay duration, postoperative complications, and overall morbidity and mortality. Statistical analysis was performed using chi-square tests for categorical data and appropriate tests for continuous data, with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered significant.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe majority of patients were in the 31\u0026ndash;40 years age group (24.3%), with a male predominance (62.9%). Cloudy exudate was the most common finding (51.4%), followed by fecal (20%) and purulent (15.7%) exudates. Generalized peritonitis was observed in 57.1% of patients. Most patients fell into the moderate-risk MPI category (48.6%). Higher MPI scores correlated with increased ICU stay, complication rates, and mortality. Nearly all patients in the severe MPI category required ICU admission (95%), and the highest mortality rate (35.7%) occurred in this group. Fecal exudate was significantly associated with higher mortality (p\u0026thinsp;=\u0026thinsp;0.033).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eOur study corroborates the extensive body of research on the Mannheim Peritonitis Index, reinforcing its value as a prognostic tool in the management of perforation peritonitis. The consistent findings across various studies underscore the MPI's reliability and utility in clinical practice, providing a robust framework for predicting patient outcomes and guiding treatment strategies. Future research should focus on integrating the MPI with other clinical parameters and validating it in diverse populations to enhance its predictive power and clinical utility.\u003c/p\u003e","manuscriptTitle":"The Role of the Mannheim Peritonitis Index in Predicting Mortality and Morbidity in Perforation Peritonitis Patients in a tertiary care hospital in southern Rajasthan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-05 09:33:38","doi":"10.21203/rs.3.rs-8098660/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-13T11:36:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-12T10:14:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-09T16:12:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294533263532752709282003123775833887614","date":"2025-12-02T17:51:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"57265895055320222355272550873971044270","date":"2025-12-01T10:47:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-01T09:57:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-01T09:19:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-01T01:49:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"SN Comprehensive Clinical Medicine","date":"2025-11-12T17:01:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"sn-comprehensive-clinical-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sncm","sideBox":"Learn more about [SN Comprehensive Clinical Medicine](https://www.springer.com/journal/42399)","snPcode":"42399","submissionUrl":"https://submission.nature.com/new-submission/42399/3","title":"SN Comprehensive Clinical Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3a091631-548b-4c40-89fe-06a896eeeea1","owner":[],"postedDate":"December 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T11:55:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-05 09:33:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8098660","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8098660","identity":"rs-8098660","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}