Abstract
Introduction: This study aims to evaluate the accuracy and the reliability of Boey’s score in predicting post-operative complications and mortality rates in patients with perforated peptic ulcers treated at district- and central-level hospitals.
Patients and Methods: The retrospective case series study was conducted at two hospitals: Le Van Thinh Hospital, a district-level facility, and Cho Ray Hospital, a central-level institution. Data were collected from 114 patients at Le Van Thinh Hospital between January 2020 and December 2023, and from 255 patients at Cho Ray Hospital between January 2021 and December 2022. The study included patients diagnosed with Perforated Peptic Ulcer (PPU) who underwent surgical intervention, and met the study criteria. With the data collected, we then determined Boey’s score value and variables independent of the complication and mortality ratio. A ROC curve was used, to evaluate the predictive capability of Boey’s score.
Results: Le Van Thinh Hospital: The complication and mortality rates were 15.8% and 5.3%, respectively. Both rates exhibited an increase with higher Boey scores: complication rates were 2.3%, 33.3%, 88.9%, and 100% (p<0.001) for Boey scores of 0, 1, 2, and 3, respectively, while mortality rates were 0%, 0%, 33.3%, and 100% (p<0.001). The (Area Under Curve) AUC for predicting complications was 0.918, and for mortality, it was 0.986. Cho Ray Hospital: The complication and mortality rates were considerably higher at 54.1% and 25.5%, respectively. The complication rates increased progressively with higher Boey scores: 12.5%, 26.7%, 75%, and 98.2% (p<0.001), while the corresponding mortality rates were 0%, 2.4%, 31.9%, and 70.2% (p<0.001). The AUC for predicting complication was 0.862, and for mortality, it was 0.878.
Conclusions: Boey’s score serves as an accurate predictor of both mortality and complication rates in patients undergoing surgical intervention for PPUs.
Keywords: Perforated peptic ulcer, Boey score, Mortality rate, Complication rate, Surgical outcomes, Prognosis, Area Under the Curve (AUC)
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