A Prospective Study of Evaluation of Operative Duration as a Predictor of Mortality in Pediatric Emergency Surgery: Concept of 100 Minutes Laparotomy in Resource-limited Setting

1. A PROSPECTIVE STUDY OF EVALUATION OF
OPERATIVE DURATION AS A PREDICTOR OF
MORTALITY IN PEDIATRIC EMERGENCY
SURGERY: CONCEPT OF 100 MINUTES
LAPAROTOMY IN RESOURCE-LIMITED SETTING
Presenter : Dr Kaushal Deep Singh

2. INTRODUCTION
Operative duration has been found to affect post-
operative mortality rates. [1, 2]
Direct effect of operative duration on mortality has been
studied sparingly.
No study was found during our literature review which
predicted mortality as a function of operative duration in
emergency laparotomies.

3. AIMS AND OBJECTIVES
1. To quantify the effect of duration of emergency
laparotomy in children on mortality.
2. To identify a rough cut-off duration of
laparotomy to serve as a guide so that such a
laparotomy can be planned to optimize pediatric
surgical patient outcome in terms of decreased
mortality.

4. MATERIALS AND METHODS
INCLUSION CRITERIA
All pediatric patients in the age group of 5 to 10 years presenting with
acute abdomen.
 Only those patients who had a PRISM-III (Pediatric Risk of Mortality
III) score [3] (Figure 1) of ≤ 8 at presentation.
Those who were adequately resuscitated (with a minimum resuscitation
period of at least 1 hour) pre-operatively and attained PRISM-III score
within 0 range before shifting to EOT.
Patients who underwent definitive surgery by a single surgeon in the
emergency.
Patients who presented within 72 hours of initial onset of symptoms,
who were operated within 24 hours of initial presentation and who died
in index hospital admission within 30 days.

6. MATERIALS AND METHODS (contd.)
EXCLUSION CRITERIA
Patients who underwent damage control surgery.
Whose PRISM – III score was >9 at any point of time before undergoing
laparotomy
Inability to achieve adequate resuscitation (PRISM-III score >0 before
shifting to EOT) and/or requirement of resuscitation beyond 4 hours of
presentation.
Post-operative Care, Data-recording and Data-analysis
All the patients were shifted to pediatric intensive care unit (PICU) after
the operation.
 Data recording and follow-up progress was done with SURGILOG®
android application.
Data analysis was done with IBM SPSS Statistics software version 24.

7. OBSERVATIONS & RESULTS
Total number of patients –
213
Males – 154 (72%)
Females – 59 (28%)
Study Groups
1. Survived – 176 (83%)
2. Expired – 37 (17%)
Males had a 30-day in-
hospital mortality rate of
15.6% as against 22.0%
among females (p<0.05)
Figure 2: Distribution of Patients by Gender
Figure 3: Distribution of Patients by Final
Outcome
Males,
154, 72%
Females,
59, 28%
Survived,
176, 83%
Expired,
37, 17%

8. OBSERVATIONS & RESULTS
Table 1: Descriptive variables with respect to gender of patients
Sex
Number of
Patients
Mean with Standard
Deviation (Range)
p value
(Mann
Whitney U
test)
Age (years)
Male 154 7.8 ± 0.9
.403 (NS)
Female 59 7.9 ± 0.9
Time to
Presentation
(hours)
Male 154 42.0 ± 14.8 (3-68)
.362 (NS)
Female 59 44.1 ± 15.5 (4-70)
PRISM-III Score
Male 154 4.7 ± 2.0
.706 (NS)
Female 59 4.6 ± 1.9
Duration to
laparotomy
(hours)
Male 154 3.6 ± 2.0 (1.7 – 16.4)
.316 (NS)
Female 59 3.9 ± 3.0 (2 – 21.5)
Operative
Duration
(minutes)
Male 154 108.1 ± 25.0 (54 - 197)
.773 (NS)
Female 59 109.2 ± 23.7 (65 – 174)
NS – Not Significant
Mean = 7.9 years
Mean = 42.6 hours
Mean = 3.7 hours
Mean = 108 minutes

9. OBSERVATIONS & RESULTS
Table 2: Relationship of descriptive variables with outcome
S – Significant; NS – Not Significant
Outcome
Number
of
Patients
Mean with
Standard
Deviation (SD)
p value
(Mann
Whitney U
test)
Binary Logistic
Regression
Significance
Age (years)
Survived 176 7.9 ± 1.0
.964 (NS) .716 (NS)
Expired 37 7.9 ± 0.7
Time to
Presentation
(hours)
Survived 176 42.16 ± 15.2
.309 (NS) .308 (NS)
Expired 37 44.92 ± 13.8
PRISM-III
Score
Survived 176 4.72 ± 2.0
.674 (NS) .681 (NS)
Expired 37 4.57 ± 2.2
Duration to
laparotomy
(hours)
Survived 176 3.580 ± 2.12
.084 (NS) .049 (S)
Expired 37 4.468 ± 2.9
Operative
Duration
(minutes)
Survived 176 102.65 ± 20.7
.000 (S) .000 (S)
Expired 37 135.43 ± 23.8

10. OBSERVATIONS & RESULTS
Figure 5: Kaplan-Meier (K-M) Survival Curve
50%
75%
95%
99 min
106 min 110 min
132 min
146 min

11. OBSERVATIONS & RESULTS
Figure 6: Receiver Operating
Characteristic (ROC) Curve analysis
for operative Duration
The area under curve
(AUC) for operative
duration 0.864.
Youden’s Index
maximized at 123.50
(<0.05) minutes giving -
Sensitivity - 75.7%
Specificity - 82.4%
Mortality rate of 5.8% in
patients with operative
duration <123.5 minutes
as compared to 47.5% in
≥ 123.5 minutes.
AUC = 0.864
0.5

12. INTERPRETATIONS
1. Sex/Gender does not affect postoperative 30-day in-hospital
mortality.
2. Time to laparotomy is a risk factor for forecasting mortality.
3. Operative duration is a significant risk factor in prognosticating
probability of death following surgery in emergency setting.
4. In resource-limited setting like ours, an emergency pediatric
laparotomy should ideally be completed within 100 minutes
(mortality rate - 1-2%).
5. If for some unforeseen circumstances the laparotomy duration is
increasing, mortality rates in acceptable limits (≈5%) could be
obtained at a cut-off operative duration of 123.5 minutes.
6. An emergency pediatric laparotomy must not exceed 135
minutes in any situation as survival function drops rapidly
beyond this point.

13. CONCLUSION
First study which has quantified the effect and impact
of operative duration alone as a function of mortality.
Completion of an emergency laparotomy in children in
100 minutes should be a realistic target for improving
post-operative outcome in government hospitals’
casualty set-up.

14. REFERENCES
1. Cook TM, Day CJ. Hospital mortality after urgent and emergency
laparotomy in patients aged 65 yr and over. Risk and prediction of
risk using multiple logistic regression analysis. Brit J Anaesth.
1998;80(6):776-81.
2. Yamashita S, Haga Y, Nemoto E, Nagai S, Ohta M. E-PASS (The
Estimation of Physiologic Ability and Surgical Stress) Scoring
System Helps the Prediction of Postoperative Morbidity and
Mortality in Thoracic Surgery. Eur Surg Res. 2004;36(4):249-55.
3. Shann F. Are we doing a good job: PRISM, PIM and all that.
Intens Care Med. 2002;28(2):105-7.

15. THANK YOU