Perforation peritonitis is one of the common emergencies encountered in general surgical practice. It is a life-threatening condition requiring emergency surgical intervention. 

Perforation leads to seeping of gut contents into the peritoneal cavity¹, in turn leading to inflammation and infection, which causes electrolyte disturbances and septic shock, leading to multi-system organ failure and general depression of the immune system. The high mortality rate associated with diffuse suppurative peritonitis persists despite advancements in antimicrobial therapy and supportive care. This underscores the critical need for early intervention to modify the sequence of events leading to increased morbidity. Key to reducing mortality is the early identification of at-risk patients, recognising the severity of their condition, and conducting accurate assessments and classifications of risk. An aggressive surgical approach is essential², especially since the prognosis worsens significantly once multi-organ failure has occurred. Comprehensive clinical, biochemical, and radiological evaluations are vital for improving outcomes and guiding effective management strategies.Scoring systems offer an objective assessment of disease severity based on pathophysiological parameters, facilitating decision-making in managing hollow viscous perforation peritonitis. Various scores, such as APACHE II, PULP, POSSUM, SAPS, SSS, and Ranson, exist for this purpose. However, these systems often require complex laboratory tests and specialised software, making them impractical for many centres with limited resources and manpower³. Utilisation of scoring systems would be of great help in salvaging the priceless life of a patient. This study is undertaken to evaluate the accuracy of two simpler preoperative scoring systems which are easy to perform at the bedside as they incorporate easily obtainable parameters, the Jabalpur scoring system and Mannheims peritonitis index (MPI), to predict mortality among patients of peritonitis secondary to hollow viscus perforation⁴.

AIM

To compare the efficacy of Jabalpur prognostic scoring system with Mannheims peritonitis index in the evaluation of prognosis in patients with perforation peritonitis

The study was a hospital-based comparative observational design conducted at the Department of General Surgery, SMS Medical College, Jaipur. Spanning from April 2023 to April 2024. The study population included patients who met the selection criteria and provided written informed consent for participation. Prior approval was obtained from the institutional ethics committee for conducting the research.

To determine the sample size, a 95% confidence interval was utilised to validate an expected 90% sensitivity of the JPS score for predicting mortality, as reported by Prakash et al. The sample size calculation, considering an expected mortality rate of 13.3% and a relative allowable error of 20%, resulted in a minimum of 81 subjects, which was 

rounded up to 100.

The sample size was calculated using the formula–  

Were,

= Standard normal deviate for 95% confidence interval (taken as 1.96)

      S_n= Expected sensitivity of JPS for predicting mortality (taken as 90% as reported by Prakash et al.)

P = Expected mortality in patients with peritonitis (13.3%, as reported by Prakash et al.)

E = Relative allowable error/precision (taken as 20% of S_n)

Inclusion criteria encompassed all patients diagnosed with perforation peritonitis who were admitted for surgical treatment, aged over 18 years, and willing to provide informed consent. Conversely, exclusion criteria included pregnant females, patients who underwent laparotomy at other facilities, those transferred for continued treatment, cases left against medical advice, and individuals with post-operative or traumatic peritonitis.

Table 1: Age distribution of study subjects

Among the 100 patients included in the study, 21 were aged <30 years, 26 were aged 30-44 years, 25 were aged 45-59 years, 20 were aged 45-59 years, while only 8 were aged 75-89 years.  The mean aged patients were 46.93 ± 18.32 years. 

Graph: Distribution of study subjects according to comorbidities, perforation site, type of exudates and post-op complications

In the study of 100 patients with perforation peritonitis, 16% required pre-operative ICU care, with common comorbidities including tuberculosis (9%) and carcinoma (8%). The predominant perforation site was peptic (49%), and most patients had purulent exudates (66%), with surgical site infection (30%) being the most common postoperative complication; ICU admission was necessary for 28%, while pulmonary complications and burst abdomen occurred in 8% and 5% of cases, respectively.

Table 2: Distribution of study subjects according to JPS score

JPS score was used to categorise the patients with perforation peritonitis. Half (50%) of the patients had a JPS score of 0-4, followed by 32% of cases with a JPS score of 5-9, 15% of cases had a JPS score of 10-14, and only 3% of cases had JPS score of ≥15. 

Table 3: Distribution of study subjects according to MPS score

Patients with perforation peritonitis were also categorised based on the MPS score. The majority (58%) of the patients had an MPS score of <21, followed by 26% of cases with an MPS score of 21-29, and 16% of cases had an MPS score of >29. 

Table 4: Mortality in relation to JPS

The above table shows that mortality among patients with perforation peritonitis was higher in Category-4 JPS score (100%), followed by Category-3 JPS score (80%), category-2 JPS score (3.1%) and was nil in Category-1 JPS score (0%). This difference in mortality rates in relation to the JPS score was found to be statistically significant (p<0.001).

Table 5:  Mortality in relation to MPS

The present table illustrates that mortality among patients with perforation peritonitis was higher in the Category-3 MPS score (68.8%), followed by the Category-2 MPS score (19.2%), and was nil in the Category-1 MPS score (0%). This difference in mortality rates in relation to MPS score was found to be statistically significant (p<0.001). 

Table 6: Post-op complications in relation to JPS

The study found significant differences in postoperative outcomes based on JPS categories, with ICU admission rates at 100% for Category-4 and 93.3% for Category-3, alongside higher surgical site infections and burst abdomen incidences in the higher categories (p<0.001). However, complications like post-operative leaks and DVT showed no statistically significant differences among the JPS categories.

Table 7: Post-op complications in relation to MPS

ICU admission rates were significantly higher in MPS category-3 (87.5%) compared to categories 2 (38.5%) and 1 (6.9%) (p<0.001). Additionally, surgical site infections, burst abdomen incidence, and pulmonary complications were notably greater in higher MPS categories, with statistically significant differences (p<0.001 for SSI and pulmonary complications, p=0.021 for burst abdomen), while post-operative leaks were significant in category-3 (12.5%) but not in categories 2 and 1 (p=0.005). DVT was rare, with only one patient in category-2 affected (p=0.238).

Table 8: ROC Curve for JPS and MPS for predicting mortality

A high area under the ROC curve of 0.977 (95% CI=0.948 – 1.000) indicates that JPS is a good tool for predicting mortality among patients with perforation peritonitis (p<0.001). At a cutoff value of >9, JPS had a sensitivity of 93.75% and a specificity of 96.43%. 

A high area under the ROC curve of 0.917 (95% CI= 0.859 – 0.975) indicates that MPS is a good tool for predicting mortality among patients with perforation peritonitis (p<0.001). At a cutoff value of >23, MPS had a sensitivity of 100% and specificity of 70.24%. 

The mean age of all patients was 46.93 ± 18.32 years, with a range of 14 – 83 years.In our study, the JPS score was used to categorise the patients with perforation peritonitis. Half (50%) of the patients had a JPS score (0-4), followed by 32% of cases with a JPS score of 5-9, 15% of cases had a JPS score of 10-14 and only 3% cases hadJPS score of (≥15). The Jabalpur scoring system was developed by Mishra et al. at Jabalpur district of Madhya Pradesh⁵. This was based on a retrospective analysis of data from 140 patients with peptic perforation peritonitis.Mishra et al. ⁵ reported that no patient with a Jabalpur score of 0 to 4 died, whereas all patients who had a score of >15 died.Similar findings were found in our study. Mortality among patients with perforation peritonitis was higher in the Category-4 JPS score (100%), followed by Category-3 JPS score (80%), Category-2 JPS score (3.1%) and was nil in the Category-1 JPS score (0%). This difference in mortality rates in relation to the JPS score was found to be statistically significant (p<0.001). 

In the present study, post-op morbidity and complications were also found to be significantly associated with the JPS score. Singh S et al^6, in a similar study, reported a significant association of JPS with morbidity and found that patients with a score of <9 and >9 had morbidity of 30% and 80%, respectively. Jabalpur’s prognostic score is simple and user-friendly as it uses only six routinely documented clinical risk factors and doesn’t require intraoperative findings⁷. Past studies have shown an association between all the factors used in the Jabalpur scoring and mortality, and as the score increased, there was an increase in mortality⁸.

In our study, patients with perforation peritonitis were also categorised based on MPS score. The majority (58%) of the patients had an MPS score of <21, followed by 26% of cases with an MPS score of 21-29, and 16% of cases had an MPS score of >29.  Mortality among patients with perforation peritonitis was higher in the Category 3 MPS score (68.8%), followed by the Category 2 MPS score (19.2%), and was nil in the Category 1 MPS score (0%). This difference in mortality rates in relation to MPS score was found to be statistically significant (p<0.001).Billing et al⁹ in 2003 by patients in 7 different centres across three countries and compared their data. They considered patients of perforation or postoperative peritonitis, peritonitis caused by pancreatitis, appendicitis and mesenteric ischemia for study. Each risk factor is given a weightage to produce a score used for prognostic purposes. They found a linear correlation between the mean index score and the mean mortality rate¹⁰. 

In the present study, a high area under the ROC curve of 0.977 (95% CI=0.948 – 1.000) indicates that JPS is a good tool for predicting mortality among patients with perforation peritonitis (p<0.001). At a cutoff value of >9, JPS had a sensitivity of 93.75% and a specificity of 96.43%. This was similar to the original study by Mishra et al⁵, who reported an overall accuracy of 92% at a cutoff value of 9

In our study, a high area under the ROC curve of 0.917 (95% CI= 0.859 – 0.975) indicates that MPS is a good tool for predicting mortality among patients with perforation peritonitis (p<0.001). At a cutoff value of >23, MPS had a sensitivity of 100% and specificity of 70.24%. Another study by Kumar Sonker¹¹ compared the APACHE-II score and MPI score. They found that the APACHE-II score has a sensitivity of 83% and specificity of 94%, whereas the MPI score has a sensitivity of 51% and specificity of 77%. Though MPI didn’t prove to be as good as APACHE II, there is a benefit in using the MPI scores in primary and secondary level hospitals where facilities are less, and investigations such as arterial blood gas analysis may not be available. 

The present study found that the JPS score demonstrated a slightly higher area under the ROC curve compared to the MPS score, suggesting it may be a better prognostic tool, although statistical significance was not established. Supporting this, Prakash et al¹² reported a 96% area under the curve for the JPS versus 95% for the MPI, highlighting that JPS is easier to apply due to its reliance on readily obtainable parameters and initial data collected at admission without needing intraoperative findings.

The findings of the present study conclude that both MPI and JPS showed high accuracy in predicting morbidity and mortality for patients with peritonitis and sepsis syndrome, with JPS showing slightly higher accuracy. Both scores are appropriate in a hospital set up with limited resources as they utilise variables that can be easily calculated with minimum investigations and can be used for predicting the outcome of the patient in terms of mortality and morbidity. The advantage of JPS is that the parameters for the scoring can be calculated at the time of hospital admission itself and don’t require intra-op findings.

1. Pannu HK, Oliphant M. The subperitoneal space and peritoneal cavity: basic concepts. Abdom Imaging. 2015 Oct;40(7):2710-22. doi: 10.1007/s00261015-0429-5. PMID: 26006061; PMCID: PMC4584112.
2. Blackburn SC, Stanton MP. Anatomy and physiology of the peritoneum. Semin Pediatr Surg. 2014 Dec;23(6):326-30. doi: 10.1053/j.sempedsurg. 2014.06.002. Epub 2014 Jun 4. PMID: 25459436.
3. Inderbir Singh's Human Embryology, 13th Edition 2023
4. Standring, S. The Anatomical Basis of Clinical Practice. Gray’s Anatomy, 42nd Edition.. Elsevier, Amsterdam. 2020
5. Mishra A, Sharma D, Raina VK. A simplified prognostic scoring system for peptic ulcer perforation in developing countries. Indian J Gastroenterol. 2003;22:49-53
6. Singh, S., Sharma, S., Hans, S., Singh, N., Gupta, A., Neki, N.S., & Singh Shergill, G. (2017). Prognostication of Perforation Peritonitis Cases Using Jabalpur Peritonitis Index. http://dx.doi.org/10.22192/ijcrms.2017.03.03.004
7. Prakash GV, Vijay Kumar Reddy B, Srihari Rao B, Srikanth Reddy C, Raghuram G, Ajay Babu K et al (2019) Comparison of the efficacy of Jabalpur prognostic scoring system with Mannheims peritonitis index in evaluation of prognosis in patients with perforation peritonitis. Int Surg J 6(7):2390–2394. https://doi.org/10.18203/2349-2902.isj20192961
8. Subangi KG, Aravind N. A Comparative Study Of Pulp Scoring Vs Jabalpur Prognostic Scoring In Predicting Outcome In Patients With Peptic Ulcer Perforation. IOSR J Dental Med Sci. 2018;17(2):45- 53.
9. Billing A, Fröhlich D, Peritonitis Study Group. Prediction of outcome using the Mannheim peritonitis index in 2003 patients. British journal of surgery. 1994 Feb;81(2):209-13.
10. Qureshi AM, Zafar A, Saeed K, Quddus A. Predictive power of Mannheim Peritonitis Index. J Coll Physicians Surg Pak. 2005 Nov;15(11):693-6. PMID: 16300704.
11. Kumar Sonker, S., Nirala, S., & Kumar Dhruv, B. (2022). To Prognosticate the Outcome in Patient with Perforation Peritonitis by Evaluating Mannheim Peritonitis Index & Apache-II Scoring System. Global Journal for Research Analysis.
12. Prakash GV, Vijay Kumar Reddy B, Srihari Rao B, Srikanth Reddy C, Raghuram G, Ajay Babu K et al (2019) Comparison of the efficacy of Jabalpur prognostic scoring system with Mannheims peritonitis index in evaluation of prognosis in patients with perforation peritonitis. Int Surg J 6(7):2390–2394. https://doi.org/10.18203/2349-2902.isj20192961