ArticlePDF Available

Risk adjustment for audit of low risk general surgical patients by Jabalpur-POSSUM score

Authors:

Abstract and Figures

INTRODUCTION: Physiological and Operative Severity Score for enUmeration of Mortality and morbidity (POSSUM) and its Portsmouth modification (P-POSSUM) were developed to provide risk-adjusted analysis in patients undergoing surgery; but have not been validated in low-risk patients. The aim of this study was to assess POSSUM and P-POSSUM in general surgical patients in a developing country. MATERIALS AND METHODS: Seven hundred and eighty-eight consecutive general surgical patients were studied prospectively with POSSUM and P-POSSUM scoring systems using linear and exponential analysis. The ratio of observed to predicted death and morbidity (0: E) was calculated for each analysis and frequency tables were compared for statistical significance by means of chi square test. In the second part of this study prospective evaluation of Modified POSSUM was performed on the next 908 patients. RESULTS: POSSUM was found to be a good predictor of mortality and morbidity with exponential analysis but not with linear analysis. P-POSSUM predicted the mortality accurately with the help of linear analysis. Both overpredicted the outcome in the low-risk group (predicted risk of mortality < 10% and predicted risk of morbidity < 40%); therefore POSSUM needs to be modified for audit in the low-risk group. Such a modification, Jabalpur-POSSUM (J-POSSUM: a modification of POSSUM for low-risk group) revealed good fitness with observed mortality (O: E = 1.00) and morbidity (O: E = 1.04). On prospective evaluation of J-POSSUM, this finding was confirmed for the low-risk group vis-à-vis observed mortality (O: E = 1.16) and morbidity (O: E = 0.83). CONCLUSION: POSSUM is not a good predictor of low-risk patients and needs risk adjustment with the help of correcting factor for accurately predicting the mortality and morbidity. Such a correction factor was identified with the help of multiple logistic regression analysis and prospectively validated. Jabalpur-POSSUM can successfully predict the outcome in low-risk patients.
Content may be subject to copyright.
Indian J Surgery | February 2005 | Volume 67 | Issue 1
38
INTRODUCTION
Surgical audit, in some form or the other, has
been practised since long, but it has been
accepted in regular practice only recently.
Surgical audit consists of critical assessment
of surgical outcome and results. There are
Risk adjustment for audit of low risk generalRisk adjustment for audit of low risk general
Risk adjustment for audit of low risk generalRisk adjustment for audit of low risk general
Risk adjustment for audit of low risk general
surgical patients by Jabalpur-POSSUM scoresurgical patients by Jabalpur-POSSUM score
surgical patients by Jabalpur-POSSUM scoresurgical patients by Jabalpur-POSSUM score
surgical patients by Jabalpur-POSSUM score
Vijay Parihar, Dhananjaya Sharma, Romesh Kohli, D. B. Sharma
G. I. Surgery Unit, Department of Surgery, NSCB Government Medical College, Jabalpur - 482 003, India
For correspondence:
Dr. Dhananjaya Sharma, Professor in Surgery and Incharge GI Surgery Unit, P-10, Medical Campus, Government NSCB Medical
College, Jabalpur - 482003, MP, India. E-mail: dhanshar@hotmail.com
ABSTRACT
Introduction: Physiological and Operative Severity Score for enUmeration of Mortality and morbidity
(POSSUM) and its Portsmouth modification (P-POSSUM) were developed to provide risk-adjusted analysis
in patients undergoing surgery; but have not been validated in low-risk patients. The aim of this study
was to assess POSSUM and P-POSSUM in general surgical patients in a developing country. Materials
and Methods: Seven hundred and eighty-eight consecutive general surgical patients were studied
prospectively with POSSUM and P-POSSUM scoring systems using linear and exponential analysis. The
ratio of observed to predicted death and morbidity (0: E) was calculated for each analysis and frequency
tables were compared for statistical significance by means of chi square test. In the second part of this
study prospective evaluation of Modified POSSUM was performed on the next 908 patients. Results:
POSSUM was found to be a good predictor of mortality and morbidity with exponential analysis but not
with linear analysis. P-POSSUM predicted the mortality accurately with the help of linear analysis. Both
overpredicted the outcome in the low-risk group (predicted risk of mortality < 10% and predicted risk
of morbidity < 40%); therefore POSSUM needs to be modified for audit in the low-risk group. Such a
modification, Jabalpur-POSSUM (J-POSSUM: a modification of POSSUM for low-risk group) revealed
good fitness with observed mortality (O: E = 1.00) and morbidity (O: E = 1.04). On prospective
evaluation of J-POSSUM, this finding was confirmed for the low-risk group vis-à-vis observed mortality
(O: E = 1.16) and morbidity (O: E = 0.83). Conclusion: POSSUM is not a good predictor of low-risk
patients and needs risk adjustment with the help of correcting factor for accurately predicting the
mortality and morbidity. Such a correction factor was identified with the help of multiple logistic regression
analysis and prospectively validated. Jabalpur-POSSUM can successfully predict the outcome in low-
risk patients.
Key Words: Surgical audit, POSSUM, morbidity, mortality, risk-adjusted analysis
Hot to cite this article:
Parihar V, Sharma D, Kohli R, Sharma DB. Risk adjustment for audit of low risk general surgical patients by Jabalpur-POSSUM score.
Indian J Surg 2005;67:38-42.
Original Article
Paper Received: December 2004. Paper Accepted: January
2005. Source of Support: Nil.
Free full text available from http://www.indianjsurg.com
many varieties of audits but all require critical
assessment of surgical outcome.[1] If the risk of an
adverse outcome is known for a group of patients, the
actual outcome can be compared with the predicted
outcome, and comparison can be made between groups
in different surgical units for the purposes of audit or
research. The pressing need to develop measures of
health outcome for use in surgical audit was recognized
and resulted in the development of POSSUM, a
Physiological and Operative Severity Score for the
enUmeration of Mortality and morbidity, a scoring
Indian J Surgery | February 2005 | Volume 67 | Issue 1
39
system which assesses perioperative surgical risks.[2]
This scoring system produced assessments for
morbidity and mortality rates, which did not
significantly differ from observed rates and has been
acknowledged as the most appropriate of the currently
available scores for general surgical practice.[3]
Although POSSUM and its Portsmouth modification
(P-POSSUM)[4] have been successfully validated in
many different patient subsets, they have never been
validated in low-risk patients in a developing country.
The aim of the present study was to prospectively
examine the value of POSSUM and P-POSSUM in
predicting mortality and morbidity in general surgical
patients in a developing country, failing which to
develop a modification which works best for this group
of patients.
MATERIALS AND METHODS
The first part of this prospective study was carried out in
the Department of Surgery, NSCB Government Medical
College, Jabalpur (MP), INDIA during October 2000 to
September 2001 on 788 consecutive adult general surgical
patients undergoing elective or emergency surgery and
requiring in-patient care of at least 24 hours after operation.
POSSUM score [consisting of two categories of assessment
to assess the risk of surgery: a 12-factor (age, cardiac status,
pulse rate, systolic blood pressure, respiratory status,
Glasgow Coma Score, serum concentration of urea,
potassium and sodium, haemoglobin concentration, white
cell count and findings on electrocardiography) and 4-grade
physiological score (PS) combined with a 6-factor (type of
surgical procedure, number of procedures, blood loss,
peritoneal soiling, presence of malignancy and mode of
surgery) and 4-grade operative severity score (OSS).] was
calculated and morbidity and mortality were recorded as
defined by Copeland et al.[2] Complications were assessed
by clinical observation. Routine bacteriological screening
and postoperative radiological scanning were not carried out
but confirmatory bacteriological and radiological tests were
carried out where clinical doubts existed.
Using outcome (dead/alive or complicated/uncomplicated)
as a dichotomous dependent variable, multiple logistic
regression equation derived by POSSUM was applied to all
patients vis-à-vis both morbidity and mortality.[2] Equation
for morbidity was:
In log(R/1-R) = - 5.91 + (0.16 x physiological score) + (0.19
x operative severity score)
For mortality the equation used was:
In log (R/1-R) = -7.04 + (0.13 x physiological score) + 0.16
x operative severity score)
[Where R is the predicted risk]
Additionally, P-POSSUM equation[4] was applied for
mortality as follows:
In log (R/I-R) = -9.37 + (0.19 x physiological score) + 0.15 x
operative severity score)
POSSUM and P-POSSUM equations were applied to all
patients and tested for goodness of fit. Linear analysis was
done by calculating patient’s predicted risk of death using
the respective equation and then dividing the patients into
groups according to their predicted risk of death. For each
version of POSSUM, the number of patients falling into each
mortality group was multiplied by the average risk of death
to give the predicted number of deaths in that group.
Exponential analysis was done by considering a cut-off risk
of death in each stage of the calculation, then grouping
together all patients whose predicted risk fell above the cut-
off point. The ratio of observed to predicted death (0: E) was
calculated for each analysis and frequency tables were
compared for statistical significance by means of chi square
test. The same method was applied for complications.
The second part of this study consisted of prospective
evaluation of Modified POSSUM (derived by the first part
of this study). This was done during October 2001 to
September 2002 on 908 consecutive adult general surgical
patients undergoing elective or emergency surgery and
requiring in-patient care of at least 24 hours after operation.
The ratio of observed to predicted death (0: E) was calculated
for low-risk patients and compared for statistical significance
by means of chi square test. The same method was applied
for complications.
RESULTS
Seven hundred and eighty-eight patients underwent
elective or emergency surgery during the first half of
the study period, which required in-patient care for at
least 24 hours, 594 were male and 194 female. Three
hundred and ninety-one patients were operated as
elective surgery while 397 patients were operated as
emergency surgery. The types of surgical procedure
performed were as follows: gastrointestinal 355,
hepatobiliary 25, urological 68, hernia 77, breast 69 and
miscellaneous 194. The overall mortality rate was 6.72%
and the overall morbidity rate was 19.41%. The range
of physiological scores obtained is shown in Figure 1
and that of operative severity scores in Figure 2.
12 15 18 21 24 27 30 33 36 39 42 45
Physiological score
No. of patients
300
250
200
150
100
50
0
Figure 1: Range of the physiological score of patients seen in the
first half of the present study
Surgical patients by Jabalpur-POSSUM score
Indian J Surgery | February 2005 | Volume 67 | Issue 1
40
There were a total of 53 deaths. Using linear analysis,
POSSUM overpredicted the mortality as compared to
observed mortality, while using exponential analysis,
the predicted and observed mortality rates were similar
(Table 1). The mortality rate predicted by P-POSSUM,
using linear analysis was as observed but when
exponential analysis was used it was significantly
higher than observed mortality (Table 1). Postoperative
complications seen were haemorrhage (wound: n =
21, deep: n = 5, others: n = 1), infection (respiratory
tract: n = 85, wound: n = 140, urinary tract: n = 38,
deep: n = 30, septicaemia: n = 46, and others: n =
31), wound dehiscence (superficial: n = 85, and deep:
n = 68), anastomotic leak (n = 33), thrombosis (deep
vein thrombosis: n = 6, pulmonary embolism: n = 3,
cerebrovascular accident: n = 1, myocardial infarction:
n = 5, and others: n = 4), cardiac failure (n = 13),
hypotension (n = 42), respiratory failure (n = 18), renal
failure (n = 25) and others (n = 22). The morbidity
rate predicted by POSSUM by linear analysis was
significantly higher than observed morbidity while in
exponential analysis it was as predicted (Table 1).
When POSSUM analysis was done on patients
undergoing emergency surgery (n = 397), the O: E ratio
was found to be 0.78 for mortality (X2 = 2.81, 1d.f,
P>0.05) and 0.86 for morbidity (X2 = 3.02, 1d.f,
P>0.05) revealing a good fitness.
In the present study nearly 70% patients (529 out of
788) were in the low-risk group (predicted risk of
mortality <10% and predicted risk of morbidity
<40%). This group showed very poor fit, with O:E ratio
of 0.27 for mortality and 0.65 for morbidity by
POSSUM analysis and 0.54 for mortality by P-POSSUM
analysis (Table 1). Given this poor fit, the need for a
correction factor was identified and multiple logistic
regression analysis was done. A correction factor of
0.257 for mortality and 0.619 for morbidity for
POSSUM risk group was obtained as correlation co-
efficient. After applying this correction factor, Jabalpur
POSSUM score (J-POSSUM) for low-risk general
surgical patients was obtained.
J-POSSUM = POSSUM X Correction Factor for
mortality if risk <10%.
J POSSUM = POSSUM X Correction Factor for
morbidity if risk <40%.
J-POSSUM score correlated well with O: E ratio of 1.00
for mortality and 1.04 for morbidity showing no
evidence of lack of fit (Table 1). The results of the first
half of this study are summarized in Table 1.
J-POSSUM was prospectively validated in the next 908
consecutive patients who underwent elective or
emergency surgery during the second half of the study
period, which required in-patient care for at least 24
hours. Of these, 689 were male and 219 female. Four
hundred and six patients were operated as elective
surgery while 502 patients were operated as emergency
surgery. The types of surgical procedures performed
were as follows: gastrointestinal 408, hepatobiliary 22,
urological 127, hernia 76, breast 40 and miscellaneous
235. The overall mortality rate was 7.38% and the
overall morbidity rate was 18.50%. The range of
physiological scores and operative severity score was
similar to that shown in Figures 1 and 2. J-POSSUM
610141822263034384246
Operative severity score
No. of patients
500
400
300
200
100
0
Figure 2: Range of the operative severity score of patients seen in
the first half of the present study
Table 1: Risk adjusted analysis (Summary of first half of study)
Type of analysis Risk group No. of patients Mean risk O E* O:E ratio Level of significance
Overall mortality
POSSUM Linear 0-100 788 10.37 53 82 0.86 X2=32.38, 9d.f. P<0.001
POSSUM Exponential 0-100 788 10.37 53 82 0.94 X2=16.22, 9d.f. P>0.05
P-POSSUM Linear 0-100 788 4.69 53 37 1.525 X2=15.55, 9d.f. P>0.05
P-POSSUM Exponential 0-100 788 4.69 53 37 1.42 X2=27.46, 9d.f. P<0.05
Morbidity
POSSUM Linear 0-100 788 34.64 153 273 0.55 X2=68.69, 9d.f. P<0.000
Exponential 0-100 788 7.92 153 175 0.87 X2=17.84, 9d.f. P>0.05
Low risk group (mortality)
POSSUM Linear 0-10 529 3.36 5 18 0.27 X2=9.38 1d.f. P<0.05
P-POSSUM Linear 0-10 714 2.76 12 22 0.54 X2=4.55 1d.f. P<0.05
J-POSSUM Linear 0-10 529 0.87 5 5 1.00 P>0.000
Low risk Group (morbidity)
POSSUM Linear 0-40 437 8.00 23 35 0.65 X2=4.14, 1d.f. P<0.05
J-POSSUM Linear 0-40 437 4.95 23 22 1.04 X2=0.04, 1d.f. P>0.05
O=Observed, E=Expected, *Rounded to nearest whole number.
Parihar V, et al.
Indian J Surgery | February 2005 | Volume 67 | Issue 1
41
score, when applied to low-risk group, correlated well
with O: E ratio of 1.16 for mortality and 0.83 for
morbidity showing no evidence of lack of fit (Table 2).
DISCUSSION
Audit is definitely much more than only data
collection, it is complementary to research, education,
a commitment to improvement in care by stimulating
further analyses, ensuring that practice is recorded,
reviewed and made accountable, thereby resulting in
improved practice habits.[5-9] POSSUM, a popular
system of surgical audit has been widely used for
comparative audit, comparisons between surgeons, and
units, disease groups, and between two scores.[10-20] P-
POSSUM, a modification of POSSUM was developed
following reports that POSSUM tends to overestimate
the mortality, the P-POSSUM equation producing a
very close fit with the observed in-hospital mortality.[4,
21] P-POSSUM, although applied successfully in
vascular and gastrointestinal surgery patients,[19,22-24]
does not estimate morbidity.
In a developing country like India these risk-adjusted
evaluations have not been done, perhaps, because of
difficulty in the collection of accurate data, differences
in patient presentation, follow-up difficulties, and
limited financial resources. Testing for goodness of fit
with the data, to which it is being applied, is a must
for any prognostic scoring system. Geographical
variation in the different patient subsets makes such
testing and validation mandatory. Since each surgical
unit serves a different patient population, each score
system must be calibrated in the individual hospital
to ensure that the model is applicable for the patient
material involved, before the scoring system is accepted
as quality standard. This prompted us to attempt the
prospective validation of POSSUM and P-POSSUM in
our patients.
In our study POSSUM performed well vis-à-vis
mortality and morbidity only when exponential
analysis was used; the use of linear analysis resulted
in overprediction of mortality and morbidity. P-
POSSUM predicted the mortality well when linear
analysis was used but failed to do so when exponential
analysis was used. Wijesinghe et al have tried to explain
the propensity of POSSUM to overpredict mortality
when inappropriate analysis is used, the O:E ratios for
POSSUM being close to unity when the appropriate
analysis is performed i.e. exponential analysis.[22]
Exponential analysis is not convenient because it has
to be stopped and restarted at a new level if the
predicted number of death falls below that calculated
at a higher cut-off. The point at which the recalculation
has to be performed may vary between populations
depending on their spread of predicted risk of death.
It is unclear how subgroup analysis can be performed
by exponential analysis. A further difficulty with
exponential analysis is its need to count and recount
patients in the risk band. A patient in the 90-100%
band is counted not only in this band but also in the
80-100%, 70-100%, 60-100%, 50-100%, 40-100%, 30-
100%, 20-100% and 10-100% bands; whereas a patient
whose risk of death is 5% is counted only once, i.e. in
0-100% band. The prediction of death in individual
patients may therefore be inaccurate. Notwithstanding
these drawbacks the present data show that POSSUM
when used with exponential analysis provides a
reasonably accurate prediction of death and
complications in the whole population studied.
Analysis of morbidity and mortality in the low-risk
group revealed that both could not be predicted
accurately. POSSUM and P-POSSUM, both
overpredicted the mortality in low-risk group, which
forms the majority of our patients (Table 1). This is the
most important group for audit purposes since it
contains the majority of surgical patients and is
composed of fit patients undergoing minor surgery.[4]
In non-specialist, general surgical units in developing
countries with a broad case mix, a reasonable standard
of care and practice produces very low mortality and
an acceptable morbidity rate.[5] Since death is a
relatively rare health outcome in these patients, the
development of a more acceptable measure, e.g.
morbidity, must be a priority.[25] Any audit system will
not be complete without including these patients and
their morbidity—an important point against the use
of P-POSSUM. The use of multiple logistic regression
analysis made it possible to identify the correlation
co-efficient, which when used as a correction factor
with traditional POSSUM equation, gave an accurate
estimate of mortality and morbidity; giving rise to J-
POSSUM (Tables 1 and 2).
A key feature of any audit system has to be the capacity
both for local audit within hospitals and for global audit
between hospitals.[26] POSSUM fulfils the criteria for
the most appropriate audit system as it accurately
assesses both, morbidity and mortality rates but
requires modification by a correction factor for risk
adjustment in the low-risk general surgical patients.
Such a correction factor was identified with the help
of multiple logistic regression analysis, and modified
POSSUM (J-POSSUM) can, then, successfully predict
the outcome in low-risk patients. Since it can be argued
that J-POSSUM was developed by applying a correction
Table 2: Prospective Analysis of low-risk general
surgical patients with J-POSSUM (Summary of the
second half of the study)
Type of Risk No. of Observed Expected O:E
Score group Patients (n) (n) ratio
Mortality 0-<10 636 7 6 1.16
Morbidity 0-<40 585 52 63 0.83
Surgical patients by Jabalpur-POSSUM score
Indian J Surgery | February 2005 | Volume 67 | Issue 1
42
factor based on the results of one particular set of
patients and is therefore bound to reveal perfect fitness
when applied to this set of data, a prospective
evaluation of J-POSSUM was done in a new set of
patients. This prospective evaluation has also validated
the success of J-POSSUM (Table 2), thereby showing
that Jabalpur-POSSUM can successfully predict the
outcome in low-risk patients.
REFERENCES
1. Wright JE. The history of surgical audit. J Qual Clin Pract
1995;15:81-8.
2. Copeland GP, Jones D, Walters M. POSSUM: A scoring system
for surgical audit. Br J Surg 1991;78:355-60.
3. Jones HJ, de Cossart L. Risk scoring in surgical patients. Br J
Surg 1999;86:149-57.
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.
5. Davies MG, Shine MF, Lennon F. Surgical audit under
scrutiny—a prospective study. Ir J Med Sci 1991;160:299-302.
6. Dunn DC, Fowler S. Comparative audit: An experimental study
of 147,882 general surgical admissions during 1990. Br J Surg
1992;79:1073-6.
7. Meredith P, Wood C. The development of The Royal College of
Surgeons of England’s patient satisfaction audit service. J Qual
Clin Pract 1995;15:67-74.
8. Williams O. What is clinical audit? Ann R Coll Surg Engl
1996;78:406-11.
9. Aitken RJ, Nixon SJ, Ruckley CV. Lothian surgical audit: A 15-
year experience of improvement in surgical practice through
regional computerised audit. Lancet 1997;350:800-4.
10. Jones DR, Copeland GP, de Cossart L. Comparison of POSSUM
with APACHE II for prediction of outcome from a surgical high-
dependency unit. Br J Surg 1992;79:1293-6.
11. Copeland GP, Jones DR, Wilcox A, Harris PL. Comparative
vascular audit using the POSSUM scoring system. Ann R Coll
Surg Engl 1993;75:175-7.
12. Copeland GP. Comparative audit: Fact versus fantasy. Br J Surg
1993;80:1424-5.
13. Sagar PM, Harley MN, Mancey-Jones B, Sedman PC, May J,
Macfie J. Comparative audit of colorectal resection with the
POSSUM scoring system. Br J Sug 1994;81:1492-4.
14. Copeland GP, Sagar P, Brennan J, Roberts G, Ward J, Cornford
P, et al. Risk-adjusted analysis of surgeon performance: A l-
year study. Br J Surg 1995;82:408-11.
15. Sagar PM, Hartley NN, 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.
16. Brunelli A, Fianchini A, Xiume F, Gesuita R, Mattei A, Carle F.
Evaluation of the POSSUM scoring system in lung surgery.
Physiological and Operative Severity Score for the
enUmeration of Mortality and Morbidity. Thorac Cardiovasc
Surg 1998;46:141-6.
17. Curran JE, Grounds RM. Ward versus intensive care
management of high risk surgical patients. Br J Surg
1998:85:956-61.
18. Cagigas JC, Escalante CF, Ingelmo A, Hernandez-Estefania R,
Hernanz F, Castillo J, et al. Application of the POSSUM system
in bariatric surgery. Obes Surg 1999;9:279-81.
19. 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.
20. Sommer F, Ehsan A, Klotz T, Haupt G, Caspers HP, Engelmann
U. Comparison of individual urologists’ performance. Eur Urol
2001;39:369-74.
21. 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 morbitiy. Br J Surg 1998;85:1217-
20.
22. Wijesinghe LD, Mahmood T, Scott DJA, Berrodge DC, Kent PJ,
Kester FC. POSSUM and the Portsmouth predictor equation
for predicting death following vascular surgery Br J Surg
1998;85:209-12.
23. 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.
24. Prytherch DR, Suttor BL, Boyel JR. Portsmouth POSSUM model
for abdominal aortic aneurysm surgery. Br J Surg 2001;88:958-
63.
25. Kind P. Outcome measurement using hospital activity data:
Deaths after surgical procedures. Br J Surg 1990;77:1399-402.
26. Black N. A regional computerised surgical audit project. Qual
Assur Health Care 1990;2:263-70.
Parihar V, et al.
... [3] P-POSSUM, a modification of POSSUM, has been proposed as a better scoring system as it better correlates with the observed mortality rate, [7,9] but P-POSSUM has to be correlated to the general condition of the local population for it to be effective. [7][8][9][10][11][12] This is especially true in patients in developing countries such as India where the general health of the population is poor; malnutrition is a common problem and presentation frequently delayed. [12,13] Fair comparison of surgical result must take into account the difference in the case mix. ...
... [7][8][9][10][11][12] This is especially true in patients in developing countries such as India where the general health of the population is poor; malnutrition is a common problem and presentation frequently delayed. [12,13] Fair comparison of surgical result must take into account the difference in the case mix. POSSUM was developed as a surgical auditing tool for assessment of the quality of surgical care. ...
... A total of 100 cases of emergency laparotomies were studied in patient admitted in general surgery department from April 2017 to December 2017. [12] Physiological parameter, operative parameter, and 30-day mortality were collected. Predicted mortality and morbidity for each patient were calculated using POSSUM and P-POSSUM equations. ...
Article
Full-text available
Background: Comparison of operative morbidity rates after emergency laparotomy between units may be misleading because it does not take into account the physiological variables of patients' conditions. Surgical risk scores have been created, and the most commonly used is the Physiological and Operative Severity Score for the enumeration of Mortality (POSSUM) or one of its modifications, the Portsmouth-POSSUM (P-POSSUM), usually requires intraoperative information. Objective: The objective of this study is to evaluate the POSSUM and P-POSSUM scores in predicting postoperative morbidity and mortality in patients undergoing emergency laparotomy. Methodology: This is a prospective, cross-sectional, and hospital-based study that was conducted at J.L.N. Medical College and Hospital, Ajmer, Rajasthan, India, from April 2017 to December 2017. Adult patients who presented at the causality and underwent emergency laparotomy were included in the study. Observed and predicted mortality and morbidity were calculated using POSSUM and P-POSSUM equations, and statistical significance was calculated using Chi-square test. Results: A total of 100 patients were included in this study, with a mean age of 42.83 ± 18.21 years. The observed (O) mortality was 12 (12.0%), while POSSUM predicted 40 (40%) and P-POSSUM 27 (27%). The O/E ratio for POSSUM was 0.29 and for P-POSSUM was 0.44, and this means that they both overestimate mortality. When the results were tested by Chi-square test, the P value was found to be 0.55 and 0.85 for POSSUM and P-POSSUM, respectively, which showed no significant correlation for observed and expected mortality. The observed morbidity was 69 (69%), while POSSUM expected morbidity was 79 (79%), O/E ratio is 0.87, and this again overestimates the morbidity. POSSUM is overpredicting the rate of morbidity, and test of correlation showed no significance with P = 0.75. Conclusion: POSSUM and P-POSSUM were found to overestimate mortality and morbidity in our patient's population.
... [14] Later P-POSSUM, a modification of POSSUM, was proposed, as it correlates better with the observed mortality rate. [13,15] But POSSUM must be correlated to the general condition of the local population for it to be effective. [2,12] This is important for patients in developing countries like India where the general health of the population is variable and presentation frequently variable and delayed. ...
Article
Background: Assessment of morbidity and mortality risk in emergency gastrointestinal surgeries is a fairly difficult challenge. To have a better scientific, reliable, and reproducible method of assessment POSSUM and its modified version P�POSSUM scores have been devised. In this study, we tried to evaluate the P-POSSUM Scores in patients undergoing emergency GI surgical procedures. Methods: This study was done in the Department of General Surgery, PIMS a tertiary care hospital. Consecutive emergency surgical procedures following inclusion and exclusion criteria were selected for the study. A total of n=50 cases were included in the study. P-POSSUM scores were derived for each of the cases and analysis of the predicted morbidity and mortality was compared. Results: The range of 9.9% risk was done to categorize into 10 different groups with increasing order of scores. The highest frequency was observed in 20.1 – 30.0% which was 22% lower frequency scores were observed in higher extremes. The morbidity risk scores show the highest frequency in 32% in the range of > 90.0 cases followed by 80.1 – 90.0 having cases of 28%. Conclusion: P-POSSUM is an accurate and reliable scoring method for assessing morbidity and mortality in emergency Gastrointestinal surgeries. However, it was found to overestimate mortality and morbidity in our patient population. P-POSSUM over-estimates risk for morbidity in low�risk groups while it accurately predicts the risk in higher-risk groups
... variations in mortality scores have been demonstrated by comparative studies in different geographical regions. 14,15 in fact, guerrero and colleagues 16 demonstrated a fourfold difference in mortality in major surgical procedures in uK and uS patients. in another study conducted in Malayasia, P-PoSSuM scoring was found applicable for risk adjusted patients. ...
Article
Full-text available
Background: There are different preoperative scoring systems which aim to classify the patient's risk before the surgery and decide the best treatment option for a specific patient. P-PoSSuM score has been used in clinical practice for few years. The objective of this study was to find out whether there is any difference between predicted mortality from P-POSSUM score and observed mortality in Saudi patients.
... A correction factor of 0.257 for mortality and 0.619 for morbidity for P-POSSUM was obtained as correlation coefficient for low risk group. 10 But on comparing patients who were resuscitated successfully before surgery with those who were not able to be resuscitated we found that patients who were resuscitated successfully had better prognosis than patients who were not able to be resuscitated with mortality rate of 5.7% and 44% respectively and morbidity rate of 59% and 87%. ...
Article
Full-text available
Background: Continuous audit of surgical practice is essential in enhancing patient care and lowering health care cost. This prospective study aimed to assess the validity of the Portsmouth- physiologic and operative severity score for the enumeration of mortality and morbidity (P-POSSUM) score in predicting the risk of morbidity and mortality and to identify the risk factors for poor outcome at a tertiary care teaching hospital in India.Methods: A prospective study of 100 patients (70 emergency and 30 elective) undergoing exploratory laparotomy admitted in Department of General Surgery over a 10 months period at Rabindranath Tagore Medical College, Udaipur, Rajasthan, were included in the study group. The risks of mortality and morbidity were calculated by using P-POSSUM equation. The predicted risks were compared with the observed risks of mortality and morbidity and statistically analysed.Results: The overall mortality rate of 11% with (O:E=0.85, p=0.59) and morbidity rate of 41% with (O:E=0.78, p=0.089). Higher percentage of mortality and morbidity were found with patients not able to be resuscitated successfully before surgery. Chest infections (18%), pyrexia (15%) and wound infections (14%) are areas requiring prompt care to minimize mortality rate.Conclusions: Even though P-POSSUM over predicted mortality it was not statistically significant as concluded by other studies. With P-POSSUM outcome of the patient and operative risk can be predicted and pre-operative counselling, optimization, implementing resuscitative measures and adequate care in specific high risk groups can be given with targeted interventions; improving quality of care and cost reduction.
... [14][15][16][17][18][19][20][21][22][23][24] Factors influencing operative outcome in developing countries are distinct from those affecting clinical and recovery parameters due to variance in physiological, economic and socio-cultural aspects. 25,26 Keeping this in mind, Portsmouth-POSSUM (P-POSSUM) includes both physiological and operative finding parameters. It is widely used guide for better utilization of health care resources for postoperative patients. ...
Article
Full-text available
Introduction: Emergency laparotomy, though lifesaving, may result in significant morbidity and mortality. In an attempt to clinically evaluate patients undergoing emergency laparotomy and predict their mortality using the worldwide accepted Portsmouth Predictor equation for mortality (P POSSUM), the present study was undertaken in the Surgery department of a tertiary care hospital in eastern India. Material and methods: This observational cross-sectional study included 60 patients aged between 15 to 75 years, undergoing emergency laparotomy during the specified study period of one and half years. Results: It was observed that out of 60 patients, 63.3% were male, and mean age was 40.60 (16.67) years. Peptic perforation was the most common indication for laparotomy. Mean P POSSUM predicted mortality risk was 40.617% (Range-0.8 to 99.7). Twenty-four patients died during hospital stay. ROC curve analysis of P POSSUM scores revealed that if a cut off value of P POSSUM score of 42.45% was selected, mortality could be predicted with a sensitivity of 70.80% and a specificity of 83.30%. Conclusion: Thus, P POSSUM might be a useful tool in predicting risk of short-term mortality following emergency laparotomy.
... [14] In Indian scenario where problems like delayed presentation and limited resources can affect the outcome even with adequate quality care, hence, there is a need to validate POSSUM scoring system in our setup. [15][16][17] This study was undertaken to assess the validity of POSSUM scoring system in patients undergoing Section: Surgery emergency midline laparotomy in our setup, and to analyse the outcome and compare the observed and expected values. ...
... This calls for simplifying scoring systems and surgical audit systems for use in developing countries with limited resources. [31][32][33][34][35] Burn patients are prone to develop infections; prompting the rationale of use of inflammatory response/pre-sepsis/ sepsis biomarkers like serum lactate, procalcitonin, plasma TNF-α, and interleukin 8/10, etc. [5,6,36] These can help in prognostication as they are found to be associated with burn injury severity. Presence of early systemic inflammatory response syndrome, and its biochemical clues have been recently shown to have adverse relationship with survival. ...
Article
Full-text available
Background: Several complex prognostic scoring systems are available for burn patients incorporating sophisticated investigations and use of global scales involved in the management of patients in intensive care unit. We constructed and validated a simplified scoring system for burn patients, which can be easily used in developing countries. Materials and Methods: One hundred and eighty-two consecutive patients with burns undergoing treatment at a teaching hospital in Central India were studied prospectively. Multiple logistic regressions were used to assess the predictive power of each prognostic variable. A simple scoring system was constructed using the four most powerful, but easy to calculate, prognostic factors. This system was then prospectively validated in the next 122 consecutive patients. Results: On multivariate analysis, total body surface area, percentage full thickness burn area, presence of inhalation burn, and serum creatinine were found significant predictors of mortality. Score was constructed using logit model using these four factors, which ranged from 4 to 20. Score correlated well with mortality; which increased with rising score. The mean score in survivors was significantly less than that in non-survivors (9.44 vs. 15.75; P < 0.0001). Cut off value of score ≥12 was associated with significantly higher mortality. The predicted and observed outcomes matched well. Conclusion: The Jabalpur prognostic scoring system for burns is effective for prognostication in selected group of patients with burn injuries. It is simple and user-friendly because it uses only four routinely documented clinical risk factors.
Article
Full-text available
29 M.E.J. ANESTH 28 (1), 2021Original CliniCal researChCliNiCAl EffiCACy of iSobAriC ropivACAiNE AloNE ANd wiTH dExMEdEToMidiNE iN SpiNAl ANESTHESiA for AbdoMiNAl HySTErECToMy: A proSpECTivE rANdoMiSEd doublE bliNd STudyDevenDra verma1 mD, ravinDra Kr. Gehlot1* mD, Basant Kr. DinDor1 mD, BaBulal Jat1 mD, manoJ ChauDhary1 mBBs, Dinesh DiDwania1 mDabstractBackground: Ropivacaine is a levo-isomer of bupivacaine, with better safety profile. Data are sparse for use of ropivacaine in spinal anesthesia for abdominal hysterectomy and effect of adding dexmedetomidine to it is also not much reported. This study was designed to assess the clinical efficacy of isobaric ropivacaine 30 mg in spinal anesthesia for abdominal hysterectomy and the effect of adding 5 μg of dexmedetomidine to ropivacaine was also evaluated.Methods: in this prospective, randomised double blind, comparative study, 90 patients of American Society of Anesthesiologists(ASA) grade I-II, aged between 30-60 years, weight 40-80 kg and height >140cm, posted for elective abdominal hysterectomy in spinal anesthesia were randomly divided into two groups; Group R(n=45): patients received 4 ml of 0.75% ropivacaine (30 mg) and Group RD(n=45): patients received 4ml of 0.75% ropivacaine (30 mg) + Dexmedetomidine(5 μg). The sensory–motor block characteristics, hemodynamic profile, postoperative analgesia and adverse effects were recorded and compared.results: both groups were statistically comparable regarding vital parameters. Time to sensory block regression to S1 was significantly longer in group RD (285.03±39.03 min) as compared to group R(238.49±32.909min) (p<0.001). Time to first rescue analgesic was significantly longer in group RD (278.71±38.48min) as compared to group R(224.97±42.43min) (p<0.001). Duration of motor block (time to regression to B0) was significantly longer in group RD (295.42±39.60 min) as compared to group R (252.68±33.69 min) (p<0.001).Conclusion: Addition of 5μg of dexmedetomidine to 4ml of 0.75% Ropivacaine administered intrathecally to patients undergoing total abdominal hysterectomy results in a prolongation of sensory block, motor block and duration of analgesia when compared to Ropivacaine alone. The addition of dexmedetomidine 5μg does not result in any increase in adverse effect. (PDF) MEJA No 28 2021. Available from: https://www.researchgate.net/publication/358243448_MEJA_No_28_2021 [accessed Jan 31 2022].
Article
Surgical Innovations are central to surgical progress, and have led to exponential growth in various fields of Surgery. Surgical Innovations in Lower and Middle Income Countries are the result of creativity of frontline health workers in search of simple, safe and ethical solutions for their unique challenges. The key lies in: 'simplifying the idea/technique/device' to find patients' needs-driven low-cost innovative surgical solutions; which can be used on a wider scale to achieve health equity for underserved populations. Local surgeons understand the difficulties and nuances of various problems and can provide local-evidence-based customized solutions for their patients' health problems. We developed a Surgical Innovation Ecosystem allowing us to see difficulties as opportunities, learn from everyone and conduct research on what is 'important' rather than what is 'interesting'. Barriers to Surgical Innovations in Lower and Middle Income Countries are well known; however, a roadmap to overcome these barriers is now available. The right balance has to be found between encouraging creativity and innovation while maintaining ethical awareness and responsibility to patients. Introduction and adoption of Surgical Innovations are governed by evidence-based principles and have to undergo a rigorous and scientific evaluation. Science of Surgical Innovations has finally come of age and is getting its due recognition and the pioneering innovators are receiving the much needed appreciation and support.
Article
An observational study was conducted in a tertiary care hospital to assess the efficacy of the Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity (POSSUM) scoring system to predict mortality, morbidity in patients undergoing laparotomy for perforative peritonitis from January 2016 to December 2017. 50 patients meeting the inclusion criteria were included in the study and the results were evaluated using chi-square test, P-value. Several scoring systems (eg, APACHE II, SIRS, multiple organ dysfunction syndrome [MODS], Mannheim peritonitis index) have been developed to assess the clinical prognosis of patients with peritonitis. Most of these scores rely on certain host criteria, systemic signs of sepsis, and complications related to organ failure. Although valuable for comparing patient cohorts and institutions, these scores have limited value in the specific day-today clinical decision-making process for any given patient. In our study, age group, sex ratio, presenting complaints, finding on examination, radiological finding, co-morbidities, peritoneal soiling, site of perforation, procedure performed, complications, co-relation between site of complication and perforation, morbidity and mortality rates were taken into consideration and the efficacy of POSSUM was evaluated and was compared with the predicted morbidity and mortality rates. We concluded that POSSUM scoring is effective in predicting the risk of morbidity & mortality in patients undergoing laparotomy for perforative peritonitis.
Article
Background: A large number of scoring systems for assessing a patient's risk of complications or death has been developed over recent years. This is a review of those that are of relevance to general surgeons. Methods: A Medline literature search was performed to identify all articles concerning 'severity of illness', 'morbidity', 'mortality' and 'postoperative complications' in the field of surgery from 1966 to 1997. Further searches were performed to find papers about specific identified scoring systems, and relevant articles from the reference lists of these were also sought. Results and conclusion: The advantages of an accurate assessment of a patient's risk include, on an individual level, the opportunity to give a more accurate prognosis and choose the most appropriate treatment. If the risk of an adverse outcome is known for a group of patients, the actual outcome can be compared with the predicted outcome, and comparison can be made between groups in different surgical units for the purposes of audit or research. The Physiological and Operative Severity Score for enUmeration of Mortality and morbidity (POSSUM) is the most appropriate of the currently available scores for general surgical practice.
Article
In 1991,1025 general surgical Fellows of The Royal College of Surgeons of England were circulated with a pro forma and asked to submit local audit results for admissions during 1990 to a confidential comparative audit service. The individual topics of cholecystectomy and colorectal resection were studied. Data returned by 160 surgeons concerned 147882 admissions including 122620 operations. Overall mortality rates ranged from 0 to 5 per cent and morbidity rates from 0 to 22 per cent. Laparoscopic cholecystectomy was associated with one-quarter of the mortality rate and two-thirds the morbidity rate of open cholecystectomy. Of the 33 surgeons who responded to a survey after the presentation of results, all wished to continue the exercise in future years; 39 per cent had been stimulated to perform further analyses and 15 per cent had changed practice habits as a result. Comparative audit involving large numbers of patients and surgeons is feasible and seems beneficial to participants.
Article
The Physiological and Operative Severity Score for enUmeration of Mortality and morbidity (POSSUM) scoring system has been proposed as an accurate predictor of death which takes account of case mix. It appears to overpredict death, and may have drawbacks which prevent accurate individual or subgroup analysis. An alternative system, the Portsmouth predictor equation for mortality (P-POSSUM) may have overcome these problems, but its apparent advantage could be related to inappropriate analysis of POSSUM predictions. Some 312 patients having arterial procedures were studied. POSSUM and P-POSSUM scores were used to predict death and compared with actual outcomes. The observed:predicted (O:E) mortality ratios were calculated by two methods for each of the scoring systems. First the analysis devised by the inventors of POSSUM was used and second the method devised for P-POSSUM. The O:E ratio for POSSUM using its recommended 'exponential' method of analysis was 1.14, but it was 0.59 if the P-POSSUM 'linear' analysis was used. The O:E ratio for P-POSSUM using its correct method of analysis was 0.89, but it was 0.67 if the method of analysis devised for POSSUM was used. The O:E ratios for POSSUM and P-POSSUM were close to unity when the appropriate analysis was performed. Both POSSUM and P-POSSUM overpredicted death if the incorrect analysis was used.
Article
POSSUM and APACHE II scores from 117 consecutive admissions to a high-dependency unit after major surgery were correlated with 30-day morbidity and mortality rates. Thirteen patients (11 per cent) died and 59 (50 per cent) developed a postoperative complication. Receiver-operating characteristic curve analysis showed POSSUM to have good predictive value for mortality (area under curve 0.75) and morbidity (area under curve 0.82). APACHE II scores had a significantly inferior predictive value for mortality (area under curve 0.54) (P < 0.002). POSSUM was superior to APACHE II in prediction of mortality in patients admitted to a high-dependency unit after general surgery. Prediction of postoperative complications by POSSUM is accurate and may be useful for audit.
Article
Surgical audit must be shown to improve clinical practice and patient outcome if its widespread introduction is to be enthusiastically embraced by surgeons. Retrospective studies on hospital activity by their nature are often incomplete and unreliable. A 12-month prospective review (July 1990-June 1991) of the activity, morbidity and mortality that occurred within a district general surgical unit is analysed. During the study period, 3,927 patients were admitted to the unit, of whom 1,649 were elective and 2,278 (58%) were emergency cases. 48 patients (1.2%) were transferred to external specialist centres. 41% of the admissions did not require surgery. There were 2,335 in-patient and 765 out-patient operations performed. Using the BUPA classification (n = 3100), there were 388 major (12.5%), 802 intermediate (25.9%) and 1910 minor (61.6%) procedures. There were 15 perioperative and 38 non-operative (27 metastatic carcinoma) deaths. 80% of the perioperative deaths were high risk, elderly patients with acute abdominal pathology. 369 complications (39 in non-operative cases) were recorded among both in- and out-patients: 212 systemic, 133 local/wound and 24 major/life threatening. The perioperative mortality rate was 0.6%. The operative morbidity rate was 9.0% and the procedure-related morbidity 4.7%. The wound infection rate was 2%. In a non-specialist, general surgical unit with a broad case mix, it is possible to provide a standard of care and practice that produces very low mortality and an acceptable morbidity rate.
Article
This paper describes a computerised surgical audit project which has been developed in the North West Thames region of the British National Health Service. The need for such a project and the reasons for the approach adopted are explained. The key feature is the capacity both for local audit within hospitals and for global audit between hospitals. Progress with implementing the project is reported. The uses of global audit are described and possible future developments outlined.
Article
POSSUM, a Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity, is described. This system has been devised from both a retrospective and prospective analysis and the present paper attempts to validate it prospectively. Logistic regression analysis yielded statistically significant equations for both mortality and morbidity (P less than 0.001). When displayed graphically zones of increasing morbidity and mortality rates could be defined which could be of value in surgical audit. The scoring system produced assessments for morbidity and mortality rates which did not significantly differ from observed rates.
Article
There is a pressing need to develop measures of health outcome for use in medical audit and in shaping decisions on the allocation of resources. Such measurement is not normally performed except in specific research settings. Routine information collected on hospital inpatients contains very crude data on two health outcomes, namely whether such patients were alive or dead at the end of their hospital stay. This paper analyses hospital activity data with particular reference to those patients who had undergone a surgical procedure. The results are broadly consistent with the earlier findings of the Confidential Enquiry into Perioperative Deaths and reveal a crude mortality rate of under 15 deaths per 1000 surgical admissions. Rates as high as 280 per 1000 admissions were found for certain procedures. Since death is a relatively rare health outcome it is argued that the development of a more acceptable measure must be a priority to provide information on the vast majority of surgical patients with non-fatal outcomes.