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 Table of Contents  
ORIGINAL ARTICLE
Year : 2013  |  Volume : 27  |  Issue : 2  |  Page : 119-123

Portsmouth physiological and operative severity score for the enumeration of mortality and morbidity scoring system in general surgical practice and identifying risk factors for low outcome


Department of General Surgery, Regional Institute of Medical Sciences, Imphal, Manipur, India

Date of Web Publication19-Nov-2013

Correspondence Address:
T Arun Kumar Singh
Department of General Surgery, Regional Institute of Medical Sciences, Imphal - 795 004, Manipur
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0972-4958.121582

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  Abstract 

Background and Objectives: Scoring system in all areas of medicine is receiving close attention because of the need to evaluate and monitor healthcare delivery and outcomes. The main application is in comparative surgical audit to monitor quality of care provided to the patient with a risk adjusted scoring system rather than using crude morbidity and mortality rates. In this prospective study, the validity of P-POSSUM is tested in patients undergoing major surgery and risk factors for low outcome were noted. Materials and Methods: A total of 277 major general surgical procedures as defined by the POSSUM scoring system criteria were included in the study during the period from September 2010 to February 2012, and final analysis was done. Results: The observed mortality rate was compared with the P-POSSUM predicted mortality rate. On using P-POSSUM the predicted mortality was 37 deaths. An O: P ratio of 0.91 was obtained. There was found to be no statistically significant difference between the observed and predicted mortality rates (χ2 = 7.859, DF = 5, P -value = 0.164). On analysing risk-factors we found that out of the 17 factors considered 10 are found to have significant rate of increment, whereas remaining 7 don't have significant change statistically. Conclusion: This study therefore, validates P-POSSUM as a valid means of assessing adequacy of care provided to the patient.

Keywords: Mortality, Portsmouth physiological and operative severity score for the enumeration of mortality and morbidity, Surgical scoring


How to cite this article:
Raut NR, Maibam C, Singh J, Devi S R, Singh T 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 low outcome. J Med Soc 2013;27:119-23

How to cite this URL:
Raut NR, Maibam C, Singh J, Devi S R, Singh T 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 low outcome. J Med Soc [serial online] 2013 [cited 2019 Dec 14];27:119-23. Available from: http://www.jmedsoc.org/text.asp?2013/27/2/119/121582


  Introduction Top


In the culture of increased scrutiny, surgeons must be able to clearly and accurately demonstrate how they perform, through comparative audit of their surgical outcomes. [1] Copeland in 1991, described physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM). The POSSUM score comprises 12 variables forming the physiological assessment [Table 1] and 6 variables forming the operative severity assessment [Table 2]. [2],[3] According to many studies, the POSSUM system over predicts the mortality significantly especially in low risk group patients. [4],[5],[6],[7] A new risk model Portsmouth POSSUM (P-POSSUM) was suggested by Whitely et al. incorporating the same variables and grading system, but a different equation. [4],[5]
Table 1: Physiological scoring

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Table 2: Operative scoring

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This study was undertaken to assess the validity of P-POSSUM scoring system in predicting the mortality rate in patients undergoing major surgeries in our setup and to try to analyze the causes for low outcome.


  Materials and Methods Top


This prospective study was carried out in the Department of Surgery, Regional Institute of Medical Sciences, Imphal, Manipur, from September 2010 to February 2012. A total of 277 patients admitted under General Surgery, who were scheduled to undergo major surgical procedures, as defined by the POSSUM scoring system criteria were included in the study with the approval of the Institutional Ethics Committee.

Inclusion Criteria

Patients more than 12 years of age undergoing any of the following major surgical procedures as defined by the POSSUM scoring system:

  1. Any laparotomy
  2. Bowel resection
  3. Major amputation
  4. Non aortic vascular surgery
  5. Common bile duct exploration
  6. Total thyroidectomy.


Exclusion Criteria

  1. Age less than or equal to 12 years
  2. Day care surgery
  3. Follow-up period criteria not met.
  4. All minor, medium, major + surgeries as defined by POSSUM scoring system.


Physiological scoring was performed just before surgery and operative scoring was carried out intra-operatively. Patients were followed-up for the first 30 days post-operative period for any complications and the outcome was noted. The observed mortality rate was compared with the P-POSSUM predicted mortality rate.

P-POSSUM scores were calculated based on physiological score and operative severity score as defined by POSSUM scoring system. Using outcome (dead or alive) as a dichotomous dependent variable, multiple logistic regression equation derived by P-POSSUM, was adopted for predicting mortality rate. The equation is given below:

In log (R/1 − R) = (0.1692 × Physiological score) + (0.155 × Operative score) − 9.065,

where R = predictive mortality rate.

Chi-square test (χ2 ) test was advocated for significance test between predicted (P) and observed (O) deaths, whilst comparison means for each physiological and operative score between alive and dead were calculated by independent sample t-test. The P < 0.05 was used as the cut-off value for statistical significance.


  Results and Observation Top


The study sample consists of 59 elective cases (6.77%) and 218 emergency cases (13.76%) and male to female sex ratio of around 1.9: 1. As shown in [Table 3], out of the 10 indications in the present study sample, ileal perforation has the highest percentage (20.9%) while obstructed hernia has the lowest with the percentage of 2.2 only.
Table 3: Indication-wise distribution

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There are four major surgical procedures during the study period as shown in [Table 4]. Laparotomy (70%) was the most common surgical procedure performed in our study, followed by bowel resection (21.7%), which is followed by common bile duct exploration (7.9%) and total thyroidectomy (0.4%) was found to be the least procedure. 34 patients died in our study with mortality rates of 6.77% (elective) and 13.76% (emergency), the total crude mortality rate being 12.27%.
Table 4: Procedure-wise distribution

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It may be observed from [Table 5] that overall mean predicted risk of mortality is 13.33%, through, which 37 deaths were predicted (P) out of 277 patients operated as against 34 observed (O) deaths. Thus, an O: P ratio of 0.91 was obtained. There was found to be no statistically significant difference between the observed and predicted mortality rates (χ2 = 7.859, DF = 5, P = 0.164).
Table 5: Comparison of observed (O) and predicted (P) number of deaths according to shorter range of predicted rate

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When a comparison of observed (O) and predicted (P) number of deaths was set forth according to indications, the overall P value is found to be exactly one (P = 0.929), which entails that the system is good and reliable one when classification is made in terms of indication. When comparison was made between the observed (O) and predicted (P) number of deaths according to surgical procedure, it is evident that the P value is 0.350, which is greater than 0.005, which is not significant.

[Table 6] shows the relationship of risk-factors and outcome (mortality) in terms of their correlation coefficient " r" values and also depicts rate of mortality increment per score of each risk-factor considered, which is estimated through multiple linear regression model. On analyzing risk-factors, we found that out of the 17 factors considered 10 are found to have significant rate of increment, whereas remaining 7 don't have a significant change statistically. The significant risk factors are cardiovascular system signs (P = 0.006), blood pressure (P = 0.000), pulse rate (P = 0.038), hemoglobin (P = 0.000), white blood cell count (P = 0.040), blood urea nitrogen (P = 0.004), serum sodium (P = 0.000), serum potassium (P = 0.000), electrocardiogram (P = 0.041) and peritoneal contamination (P = 0.023).
Table 6: Association between risks factors and outcome

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Wound infection (35.7%) was found to be the most common complication, which is followed by the chest infection (21.3%), hypotension (17.7%), urinary tract infection (8.7%), superficial wound dehiscence (7.6%), impaired renal function (6.5%), deep wound dehiscence (5.8%), respiratory failure (3.9%), septicemia (3.9%) and anastomotic leak (3.2%) was found to be the least reported complication.


  Discussion Top


Surgical audit with crude mortality rates is exceedingly misleading. There is need of a perfect risk adjusted scoring system for this purpose, which should predict the mortality accurately, is easy to use and has similar results reproduced in a variety of centers. [8]

POSSUM system of surgical audit is found to be valid not only in general surgery, [9] but also tested in vascular, [10],[11] colorectal, [12],[13],[14] esophageal, [15] orthopedics [16] and laparoscopic [17] procedures. Empirical evidence suggests that, in some cases POSSUM over-predicts risk of death by up to six-fold.

The P-POSSUM is a modification of the POSSUM scoring system, incorporating the same variables and grading system, but a different equation. P-POSSUM equation requires a different method of analysis known as the linear method, which is easier to use. The over prediction phenomenon was decreased to a great extent with this equation.

In our study, we assessed the validity of P-POSSUM in 277 major general surgical procedures. The study sample consists of 277 cases, out of which 65.3% were male as against 34.7% female with a sex ratio of around 1.9: 1. Similar findings (male to female ratio of around 2:1) were observed in a study did by Lamb et al. [18]

In our study, 34 patients died with mortality rates of 6.77% (elective) and 13.76% (emergency), the total crude mortality rate being 12.27%. Tekkis et al. [13] obtained similar results (elective = 3.9%, emergency = 25% and overall mortality rate of 11.1%).

On using P-POSSUM, the predicted mortality rate was 37 deaths. On analysis, overall mean predicted risk of mortality was 13.33%, through which 37 deaths were estimated out of the 277 patients operated. There was found to be no statistically significant difference between the observed and predicted mortality rates (χ2 = 7.859, DF = 5, P Value = 0.164). An O: P ratio of 0.91 was obtained, which is less than 1.00. It indicates that the scoring system over-predicts deaths, but the difference of deaths between the observed and predicted is akin as evident by the insignificant P value (P = 0.703).

Poon et al. [19] also reported the observed and predicted mortality rate of 11.3% and 15% respectively. Mohil et al. [20] (O: E = 0.66, χ2 = 5.33, DF = 9, P = 0.619). Mahesh et al. [21] also reported that P-POSSUM predicts death accurately in general surgical patients.

The significant risk factors known to affect the adverse outcome comprise cardiovascular system signs, blood pressure, pulse rate, hemoglobin, white blood cell count, blood urea nitrogen, serum sodium, serum potassium, electrocardiogram and peritoneal contamination. Therefore, adequate and prompt correction can definitely be expected to cause a decrease in an adverse outcome rates.

Wound infection (35.7%) was found to be the most common complication, followed by the chest infection (21.3%). Similar results were obtained by Mohil et al. [20] (35% and 20% respectively). Wound infections could be attributed to the large number of patients who had gross peritoneal contamination resulting from hollow visceral perforation resulting in local contamination of the incision site.

Although POSSUM and P-POSSUM have been validated in different countries and studies, both have their own limitations. Most notably it persistently over predicts mortality in low risk patients. [4],[22] It does not include patients who are managed conservatively and these patients make a considerable proportion of patients admitted to a surgical ward. Mistakes can occur in both data collection and analysis using POSSUM and P-POSSUM. POSSUM physiology score may change with time. The operative severity score is not available until the operation has been undertaken, thus POSSUM cannot be used to prevent a patient from undergoing a potentially curative procedure.

Overall this study only looks at the outcome of patients who have undergone major surgical procedures under the care of a general surgeon. It excludes patients who have undergone urological, neurosurgical and plastic surgical procedures. Thus, there may be a difference when comparison is made to the other studies.


  Conclusion Top


This study therefore validates P-POSSUM as a valid means of assessing the adequacy of care provided to the patient. This scoring system can also be used for risk adjusted audit in general surgery department to assess and improve the quality of surgical care provided and result in a better outcome to the patient.

 
  References Top

1.Yadav K, Singh M, Griwan M, Mishra TS, Kumar N, Kumar H. Evaluation of POSSUM and P-POSSUM as a tool for prediction of surgical outcomes in the Indian population. Australas Med J 2011;4:366-73.  Back to cited text no. 1
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2.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. 2
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3.Copeland GP. Comparative audit: Fact versus fantasy. Br J Surg 1993;80:1424-5.  Back to cited text no. 3
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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. 4
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5.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. 5
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6.Midwinter MJ, Tytherleigh M, Ashley S. Estimation of mortality and morbidity risk in vascular surgery using POSSUM and the Portsmouth predictor equation. Br J Surg 1999;86:471-4.  Back to cited text no. 6
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7.Ramanathan TS, Moppett IK, Wenn R, Moran CG. POSSUM scoring for patients with fractured neck of femur. Br J Anaesth 2005;94:430-3.  Back to cited text no. 7
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8.Jones HJ, de Cossart L. Risk scoring in surgical patients. Br J Surg 1999;86:149-57.  Back to cited text no. 8
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9.Bennett-Guerrero E, Hyam JA, Shaefi S, Prytherch DR, Sutton GL, Weaver PC, et al. Comparison of P-POSSUM risk-adjusted mortality rates after surgery between patients in the USA and the UK. Br J Surg 2003;90:1593-8.  Back to cited text no. 9
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10.Wijesinghe LD, Mahmood T, Scott DJ, Berridge DC, Kent PJ, Kester RC. Comparison of POSSUM and the Portsmouth predictor equation for predicting death following vascular surgery. Br J Surg 1998;85:209-12.  Back to cited text no. 10
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11.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. 11
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12.Sagar PM, Hartley MN, MacFie J, Taylor BA, Copeland GP. Comparison of individual surgeon's performance. Risk-adjusted analysis with POSSUM scoring system. Dis Colon Rectum 1996;39:654-8.  Back to cited text no. 12
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13.Tekkis PP, Kocher HM, Bentley AJ, Cullen PT, South LM, Trotter GA, et al. Operative mortality rates among surgeons: Comparison of POSSUM and P-POSSUM scoring systems in gastrointestinal surgery. Dis Colon Rectum 2000;43:1528-32, 1532.  Back to cited text no. 13
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14.Tekkis PP, Kessaris N, Kocher HM, Poloniecki JD, Lyttle J, Windsor AC. Evaluation of POSSUM and P-POSSUM scoring systems in patients undergoing colorectal surgery. Br J Surg 2003;90:340-5.  Back to cited text no. 14
    
15.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. 15
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16.Mohamed K, Copeland GP, Boot DA, Casserley HC, Shackleford IM, Sherry PG, et al. An assessment of the POSSUM system in orthopaedic surgery. J Bone Joint Surg Br 2002;84:735-9.  Back to cited text no. 16
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17.Tambyraja AL, Kumar S, Nixon SJ. POSSUM scoring for laparoscopic cholecystectomy in the elderly. ANZ J Surg 2005;75:550-2.  Back to cited text no. 17
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18.Lamb P, Sivashanmugam T, White M, Irving M, Wayman J, Raimes S. Gastric cancer surgery - A balance of risk and radicality. Ann R Coll Surg Engl 2008;90:235-42.  Back to cited text no. 18
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19.Poon JT, Chan B, Law WL. Evaluation of P-POSSUM in surgery for obstructing colorectal cancer and correlation of the predicted mortality with different surgical options. Dis Colon Rectum 2005;48:493-8.  Back to cited text no. 19
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20.Mohil RS, Bhatnagar D, Bahadur L, Rajneesh, Dev DK, Magan M. POSSUM and P-POSSUM for risk-adjusted audit of patients undergoing emergency laparotomy. Br J Surg 2004;91:500-3.  Back to cited text no. 20
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21.Mahesh G, Gabriel R, Sunil K. Evaluation of P-POSSUM mortality predictor equation and its use as a tool in surgical audit. Int J Surg 2003;5.  Back to cited text no. 21
    
22.Akbar NA, Asghar N, Tayyab M, Mohsin MJ, Abbas MA. Evaluation of POSSUM and P-POSSUM in patients undergoing emergency laparotomy. Pak J Surg 2011;27:261-4.  Back to cited text no. 22
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]


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