Background: Various scoring systems help in classifying the patient's risk preoperatively and hence to decide the best available treatment option. ACS-NSQIP score has been introduced in clinical practice for few years. This study was done to find out whether there is any difference between predicted mortality from ACS-NSQIP score and observed mortality in Saudi population. Methods: This prospective observational study was conducted at Security Forces Hospital, Riyadh, Kingdom of Saudi Arabia. We included patients undergoing elective and emergency surgical procedures in our hospital. Thirty days mortality data was collected and then observed to expected (O/E) mortality ratio was calculated. The sample size for our study was nine hundred and three (903) patients. Results: The mean ACS-NSQIP mortality risk score (%) for the study was 0.49. Expected number of mortalities was 4.42 while observed mortalities were 11, yielding an O/E ratio of 2.48 (p-value 0.000). We did not find a significant difference between expected and observed mortalities except for ASA class 3 and 4 patients where expected numbers of mortalities were lower than observed (p-value < 0.05). Conclusion: ACS-NSQIP can be reliably used for postoperative mortality prediction especially in lower risk groups. Copyright:
Background: Various scoring systems help in classifying the patient's risk preoperatively and hence to decide the best available treatment option. ACS-NSQIP score has been introduced in clinical practice for few years. This study was done to find out whether there is any difference between predicted mortality from ACS-NSQIP score and observed mortality in Saudi population. Methods: This prospective observational study was conducted at Security Forces Hospital, Riyadh, Kingdom of Saudi Arabia. We included patients undergoing elective and emergency surgical procedures in our hospital. Thirty days mortality data was collected and then observed to expected (O/E) mortality ratio was calculated. The sample size for our study was nine hundred and three (903) patients. Results: The mean ACS-NSQIP mortality risk score (%) for the study was 0.49. Expected number of mortalities was 4.42 while observed mortalities were 11, yielding an O/E ratio of 2.48 (p-value 0.000). We did not find a significant difference between expected and observed mortalities except for ASA class 3 and 4 patients where expected numbers of mortalities were lower than observed (p-value < 0.05). Conclusion: ACS-NSQIP can be reliably used for postoperative mortality prediction especially in lower risk groups. Copyright:
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