Table of Contents    
Year : 2017  |  Volume : 8  |  Issue : 1  |  Page : 22-25  

Portsmouth physiological and operative severity score for the Enumeration of Mortality and morbidity scoring system in general surgical practice and identifying risk factors for poor outcome

1 Department of Surgery, Saraswathi Institute of Medical Sciences, Hapur, Uttar Pradesh, India
2 Department of Surgery, GGS Medical College, Faridkot, Punjab, India
3 Department of ENT, Saraswathi Institute of Medical Sciences, Hapur, Uttar Pradesh, India

Date of Web Publication13-Jan-2017

Correspondence Address:
Nitin Nagpal
79, Medical Campus, Sadiq Road, Faridkot, Punjab
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0976-9668.198342

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Background: Estimation of the outcome is paramount in disease stratification and subsequent management in severely ill surgical patients. Risk scoring helps us quantify the prospects of adverse outcome in a patient. Portsmouth-Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (P-POSSUM) the world over has proved itself as a worthy scoring system and the present study was done to evaluate the feasibility of P-POSSUM as a risk scoring system as a tool in efficacious prediction of mortality and morbidity in our demographic profile. Materials and Methods: Validity of P-POSSUM was assessed prospectively in fifty major general surgeries performed at our hospital from May 2011 to October 2012. Data were collected to obtain P-POSSUM score, and statistical analysis was performed. Results: Majority (72%) of patients was male and mean age was 40.24 ± 18.6 years. Seventy-eight percentage procedures were emergency laparotomies commonly performed for perforation peritonitis. Mean physiological score was 17.56 ± 7.6, and operative score was 17.76 ± 4.5 (total score = 35.3 ± 10.4). The ratio of observed to expected mortality rate was 0.86 and morbidity rate was 0.78. Discussion: P-POSSUM accurately predicted both mortality and morbidity in patients who underwent major surgical procedures in our setup. Thus, it helped us in identifying patients who required preferential attention and aggressive management. Widespread application of this tool can result in better distribution of care among high-risk surgical patients.

Keywords: Portsmouth-Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity, risk scoring, surgical audit

How to cite this article:
Tyagi A, Nagpal N, Sidhu D S, Singh A, Tyagi A. Portsmouth physiological and operative severity score for the Enumeration of Mortality and morbidity scoring system in general surgical practice and identifying risk factors for poor outcome. J Nat Sc Biol Med 2017;8:22-5

How to cite this URL:
Tyagi A, Nagpal N, Sidhu D S, Singh A, Tyagi A. Portsmouth physiological and operative severity score for the Enumeration of Mortality and morbidity scoring system in general surgical practice and identifying risk factors for poor outcome. J Nat Sc Biol Med [serial online] 2017 [cited 2021 Jun 19];8:22-5. Available from:

   Introduction Top

Each surgical procedure brings forth inherent risks, and surgical safety is of foremost concern. Using only crude mortality rates to say surgeon A is better than surgeon B, can be extremely misleading as other factors such as patient factors, facilities in surgical setup, and pre- and post-operative care also play a role.[1] Thence arise the need of risk scoring which may help in the accurate prediction of outcome. An ideal risk scoring system should accurately quantify a patient's risk of adverse outcome early, should be easy to use, fast, and comparable across different patient groups. The simplest and oldest classification being used is the American Society of Anaesthesiologists Physical Status (ASA-PS) classification but has limitations in describing individual risk of complication in postoperative period.[2],[3] Various other scoring system is available but fail to incorporate surgical factors. Copeland et al. developed Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM) scoring system in hope of providing a retrospective and prospective analysis of surgical mortality and morbidity.[1] They initially analyzed 62 parameters and ultimately improvised to the final set of 12 physiological and six operative factors. The score derived was subjected to multivariate discriminate analysis to get outcome.[1],[4] Whitely MS from Portsmouth University demonstrated an over prediction of by a factor of two and suggested use of linear regression analysis to derive a better equation.[5] Thus, Portsmouth-POSSUM (P-POSSUM) is a modification of the POSSUM, which uses same variable and grading system, but a different equation to provide better results. In our center where, malnourishment is a common problem, presentation frequently delayed, and resources limited. This study was carried out to assess the validity of P-POSSUM scoring in our hospital.

   Materials and Methods Top

After getting approval from institutional ethical and research committee this study was conducted prospectively on the patients undergoing elective and emergency major surgery as defined by POSSUM scoring system. Data were collected prospectively between May 2011 to October 2012 to include fifty consecutive patients excluding those who did not meet the 30 days follow-up criteria or were aged <12 years.

Detailed history, investigations as deemed necessary for the standard procedure were recorded in Performa. Each parameter was given a 4 grade exponential score (1, 2, 4, 8). Findings of clinical examination, biochemical and hematologic tests, and an electrocardiographic assessment were studied obtain score for each of the 12 physiologic parameters (age, cardiac signs including chest radiograph findings, respiratory history, blood pressure, pulse, Glasgow coma score, hemoglobin, white cell count, blood urea, serum sodium, serum potassium, and findings on electrocardiogram) and sum of score of 12 parameters was done to obtain physiologic score (PS). Similarly, six operative parameters (operative severity, multiple procedures, total blood loss, peritoneal soiling, the presence of malignancy, and mode of surgery) were recorded at the time of completion of surgery to obtain an operative score (OS). The two parameters thus obtained were entered into following logistic regression equation to derive percentage risk of mortality and morbidity.

For mortality it is,

Loge [R/1 − R] = (0.1692 × PS) + (0.155 × OS) − 9.065.

Where R = Risk of mortality.

For morbidity it is,

Loge [R/1 − R] = −5.91+ (0.16 × physiological score) + (0.19 × operative score).

Where R = risk of morbidity.

The expected mortality rate was compared with observed and observed: Expected ratio was calculated. Using SPSS 17 (IBM) Chi-square test was then applied to obtain the P value to note any significant difference between the predicted mortality rate and the actual outcome. Individual parameters were analyzed for morbidity and mortality and Chi-square test was applied to obtain P value to see statistical correlation between mortality and different risk factors.

   Results Top

A total of 50 patients admitted for emergency/elective major surgery in surgical ward were studied. Mean age was 40.24 ± 18.6 years. 72% of patients were male and M:F ratio was 2.57:1. Majority (78%) procedures were emergency surgeries while 22% elective. Perforation peritonitis was the most common indication for surgery and per operatively most common site of perforation found was in Ileum followed by duodenum, appendix, and cecum. Other indications included intestinal obstruction, penetrating abdominal trauma. Among elective procedures, indications were gastrointestinal malignancy, common bile duct calculi, and others. Various indications of surgery are represented in [Table 1].
Table 1: Indication for surgery

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The mean physiological score was 17.56 ± 7.6 with a range of 12–42 while mean operative score was 17.76 ± 4.5 with a range from 9 to 26. Total P-POSSUM score was in the range of 21–61 with mean of 35.3 ± 10.4 of the fifty procedures six were associated with death, thus crude mortality rate was 12.00%. Based on P-POSSUM expected mortality rate of 14% was obtained in this study. The ratio of observed to expected mortality rate was 0.86 (× 2 = 00.258, 4 df, P = 0.992). Comparison of observed and P-POSSUM predicted mortality rates was done using linear analysis as in [Table 2] across various risk bands. Postoperative complications encountered during the 30 days follow-up period following the surgery are listed in [Table 3]. Based on P-POSSUM expected morbidity rate of 54% was obtained in the present study while observed morbidity was 42%. The ratio of observed to expected morbidity rate was 0.78. The comparison is illustrated in [Table 4]. On analysis of individual risk factors nine of the 18 risk factors were found to have significant association with mortality namely cardiorespiratory status (P = 0.00), Pulse rate (P = 0.01), Glasgow Coma Scale (P = 0.03), hemoglobin (P = 0.05), electrocardiograph changes (P = 0.00), blood urea (P = 0.00), serum sodium (P = 0.03), serum potassium (P = 0.02), blood loss (P = 0.02), while P value for other nine risk factors was >0.05.
Table 2: Comparison of observed mortality with predicted mortality

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Table 3: Postoperative complications

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Table 4: Comparison of observed morbidity with predicted morbidity

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   Discussion Top

Despite advancement in surgical technique and critical care facilities, high-risk surgical procedures are associated with substantial mortality.[3] As per WHO global estimates, approximately 1–5 million postoperative deaths occur per year, and postoperative morbidity is expected to be 5–10 times this rate.[6] Herein comes role of surgical audit as it is only by comparing the occurrence of an adverse outcome we can assess the safety and efficacy of a particular procedure.[7] Risk scoring measurement can help in standardization and evolution of more effective treatment regimens. Simple scoring system using fewer variables and simple equation often compromises accuracy, whereas a complex system with many variables and complex equation, may achieve precision but compromises ease of use. Thus, in an ideal system, there should balance between ease of use and accuracy. Numerous scoring systems are available such as ASA-PS,[8] goldman's index,[9] charlson's score,[10] acute physiology and chronic health evaluation, surgical risk scoring [11] but each has its own pros and cons.

POSSUM, in essence, is a surgeons scoring system as it includes parameters accounting for operative severity. Use of exponential analysis in POSSUM was criticized.[12] Since inception numerous modifications have been proposed and the most significant being P-POSSUM. It helped counter the shortcoming of POSSUM in overestimating mortality, especially in low-risk patients.[13] In this study, finding of an observed to expected mortality of 0.87 and morbidity of 0.78, validated P-POSSUM in our setup. Prytherch et al.[14] observed over prediction of the mortality rate by a factor of two by POSSUM, rectified it by application of P-POSSUM. Menon et al.[15] evaluated P-POSSUM in patients with or without methicillin-resistant Staphylococcus aureus infection, suggested P-POSSUM as means of standardizing patient data among a diverse group of patients. The worthiness of P-POSSUM has been proven across surgical setups, in various geographical locations like Midwinter et al. and Treharne et al.[16] patients undergoing vascular surgery, Yii and Ng [17] general surgery in Malaysia, Zafirellis et al.[18] undergoing esophagectomy. Stonelake et al.[19] observed high efficacy of P-POSSUM as compared to other scoring systems. Ying et al.[20] suggested some drawbacks of POSSUM like different definitions of postoperative complications result in different settings, issue of missing data, difficulty in establishing the classification of electrocardiography abnormalities and the exact operative blood loss. Furthermore, noninclusion of liver function, blood glucose, nutritional status which are often detrimental in outcome after surgery.[21]

   Conclusion Top

P-POSSUM has shown tremendous efficacy in the prediction of 30 days mortality and morbidity following major surgery at in our setup and authors recommend their routine use in high-risk patients. Small sample size was a limitation. Both POSSUM and P-POSSUM are available as online calculators and have dedicated applications in android and iOS platform their availability on smartphone's or tablets can speed up the calculation process making them extremely easy to use, can encourage further widespread application. P-POSSUM risk scoring system helps in appropriate clinical decision making and a useful audit tool for surgical procedures to improve the quality of surgical care.

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Conflicts of interest

There are no conflicts of interest.

   References Top

Copeland GP, Jones D, Walters M. POSSUM: A scoring system for surgical audit. Br J Surg 1991;78:355-60.  Back to cited text no. 1
Rix TE, Bates T. Pre-operative risk scores for the prediction of outcome in elderly people who require emergency surgery. World J Emerg Surg 2007;2:16.  Back to cited text no. 2
Scott S, Lund JN, Gold S, Elliott R, Vater M, Chakrabarty MP, et al. An evaluation of POSSUM and P-POSSUM scoring in predicting post-operative mortality in a level 1 critical care setting. BMC Anesthesiol 2014;14:104.  Back to cited text no. 3
Copeland GP. Comparative audit: Fact versus fantasy. Br J Surg 1993;80:1424-5.  Back to cited text no. 4
Whiteley MS, Prytherch DR, Higgins B, Weaver PC, Prout WG. An evaluation of the POSSUM surgical scoring system. Br J Surg 1996;83:812-5.  Back to cited text no. 5
Birkmeyer JD, Siewers AE, Finlayson EV, Stukel TA, Lucas FL, Batista I, et al. Hospital volume and surgical mortality in the United States. N Engl J Med 2002;346:1128-37.  Back to cited text no. 6
Barnett S, Moonesinghe SR. Clinical risk scores to guide perioperative management. Postgrad Med J 2011;87:535-41.  Back to cited text no. 7
Saklad M. Grading of patients for surgical procedures. Anesthesiology 1941;2:281-4.  Back to cited text no. 8
Goldman L, Caldera DL, Nussbaum SR, Southwick FS, Krogstad D, Murray B, et al. Multifactorial index of cardiac risk in noncardiac surgical procedures. N Engl J Med 1977;297:845-50.  Back to cited text no. 9
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987;40:373-83.  Back to cited text no. 10
Sutton R, Bann S, Brooks M, Sarin S. The surgical risk scale as an improved tool for risk-adjusted analysis in comparative surgical audit. Br J Surg 2002;89:763-8.  Back to cited text no. 11
Neary WD, Heather BP, Earnshaw JJ. The physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM). Br J Surg 2003;90:157-65.  Back to cited text no. 12
Kim SH, Kil HK, Kim HJ, Koo BN. Risk assessment of mortality following intraoperative cardiac arrest using POSSUM and P-POSSUM in adults undergoing non-cardiac surgery. Yonsei Med J 2015;56:1401-7.  Back to cited text no. 13
Prytherch DR, Whiteley MS, Higgins B, Weaver PC, Prout WG, Powell SJ. POSSUM and Portsmouth POSSUM for predicting mortality. Physiological and operative severity score for the enumeration of mortality and morbidity. Br J Surg 1998;85:1217-20.  Back to cited text no. 14
Menon KV, Whiteley MS, Burden P, Galland RB. Surgical patients with methicillin resistant Staphylococcus aureus infection: An analysis of outcome using P-POSSUM. J R Coll Surg Edinb 1999;44:161-3.  Back to cited text no. 15
Treharne GD, Thompson MM, Whiteley MS, Bell PR. Physiological comparison of open and endovascular aneurysm repair. Br J Surg 1999;86:760-4.  Back to cited text no. 16
Yii MK, Ng KJ. Risk-adjusted surgical audit with the POSSUM scoring system in a developing country. Physiological and operative severity score for the enumeration of mortality and morbidity. Br J Surg 2002;89:110-3.  Back to cited text no. 17
Zafirellis KD, Fountoulakis A, Dolan K, Dexter SP, Martin IG, Sue-Ling HM. Evaluation of POSSUM in patients with oesophageal cancer undergoing resection. Br J Surg 2002;89:1150-5.  Back to cited text no. 18
Stonelake S, Thomson P, Suggett N. Identification of the high risk emergency surgical patient: Which risk prediction model should be used? Ann Med Surg (Lond) 2015;4:240-7.  Back to cited text no. 19
Ying L, Bo B, Huo-Yan W, Hong Z. Evaluation of a modified POSSUM scoring system for predicting the morbidity in patients undergoing lumbar surgery. Indian J Surg 2014;76:212-6.  Back to cited text no. 20
de Castro SM, Houwert JT, Lagarde SM, Reitsma JB, Busch OR, van Gulik TM, et al. Evaluation of POSSUM for patients undergoing pancreatoduodenectomy. World J Surg 2009;33:1481-7.  Back to cited text no. 21


  [Table 1], [Table 2], [Table 3], [Table 4]


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