Utility of the surgical Apgar score in predicting morbidity and mortality: A prospective study
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Department of Surgery, M S Ramaiah Medical College, Rajiv Gandhi University of Medical Sciences, Bangalore, Karnataka, India
Submission date: 2021-02-18
Final revision date: 2021-05-17
Acceptance date: 2021-05-17
Online publication date: 2022-02-25
Corresponding author
Harsha Huliyappa   

Department of Surgery, M S Ramaiah Medical College, Rajiv Gandhi University of Medical Sciences, Bangalore, Karnataka, India. Tel: +91 9450389205. E-mail address:
Pol. Ann. Med. 2022;29(2):89-93
Optimization of postoperative care is often contingent upon the risk stratification tools such as surgical scores that are used to prognosticate potential complications.

This study evaluates the utility of surgical Apgar score (SAS) as a tool to predict morbidity and 30-day mortality among patients post general surgical procedures.

Material and methods:
The study cohort comprised of 400 patients aged between 15 to 75 years, and prospectively undergoing emergency or elective general surgery. SAS of patients were extracted from the anesthesiologist’s records on estimated blood loss, lowest heart rate and lowest mean arterial pressure. Post-operative outcomes such as major complications and mortality within 30 days of surgery were monitored.

Results and Discussion:
Out of the 297 elective procedures, 22 (7.41%) cases had major complications. While among those undergoing emergency surgeries (103), 38 (36.86%) patients developed major complications. The odds of developing major complications in patients with the high-risk SAS scores (31; 51.67%) was 5.42 (CI: 3.03–9.70) times greater than in patients with low-risk SAS scores (29; 48.33%). The odds of expiring after a general surgery was 11.92 times higher in high-risk patients (9; 75%) when contrasted with low-risk patients (3; 25%). The sensitivity and specificity of SAS in predicting major complications is 51.67% and 83.53%, respectively. The sensitivity and specificity of SAS in predicting mortality are 75% and 79.9%, respectively.

SAS serves as a simple and dependable tool to predict morbidity and 30-day mortality in patients undergoing surgical procedures under anesthesia other than local, requiring intensive perioperative monitoring.

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