External Validation of the MAGENTA Model for Predicting In-Hospital Mortality in Patients with Acute Severe Exacerbation of Chronic Obstructive Pulmonary Disease at Lampang Hospital
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Abstract
Background: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is associated with high mortality, especially among hospitalized patients. Although several prognostic tools exist, they are often difficult to apply in resource-limited settings. The MAGENTA model was therefore developed using easily accessible clinical variables to predict in-hospital mortality. If proven effective at Lampang Hospital, it could enhance the care of this high-risk population.
Objective: To externally validate the MAGENTA model for predicting in-hospital mortality in patients with AECOPD at Lampang Hospital. If the model demonstrates inadequate performance, it will be recalibrated for improved applicability.
Materials and Methods: This was a prognostic study involving patients aged >18 years with AECOPD admitted to Lampang Hospital between October 2019 and October 2023. The MAGENTA model uses seven variables collected on the first hospital day: age, body temperature, mean arterial pressure, endotracheal intubation, serum sodium, blood urea nitrogen, and serum albumin. The primary outcome was in-hospital mortality. Discriminative performance was evaluated using the area under the receiver operating characteristic curve (AuROC). If miscalibration was detected, the model was recalibrated by adjusting the intercept and/or slope to address overfitting and derive an updated equation. The model’s performance in risk classification (low, intermediate, and high) was assessed using the positive predictive value (PPV) and positive likelihood ratio (LR+).
Results: A total of 115 patients (324 exacerbation episodes) were included. Most were male with a mean age of 75.6 years and had severe COPD. The original MAGENTA model showed excellent discrimination (AuROC = 0.926), but miscalibration was observed (observedto-expected ratio [O:E ratio] = 2.054, calibration-in-the-large [CITL] = 1.182, slope = 1.293). After recalibration (O:E ratio, CITL, and slope all = 1.000), the model maintained the same discrimination (AuROC = 0.926). The revised equation classified patients into low, intermediate, and high-risk groups with PPVs of 1.05%, 10.00%, and 53.01%, and LR+values of 0.06, 0.59, and 6.04, respectively.
Conclusion: The MAGENTA model accurately identified hospitalized AECOPD patients at risk of in-hospital mortality. Although miscalibration was observed with external data, statistical recalibration improved its predictive accuracy, making it suitable for clinical application in Lampang Hospital.
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บทความที่ส่งมาลงพิมพ์ต้องไม่เคยพิมพ์หรือกำลังได้รับการพิจารณาตีพิมพ์ในวารสารอื่น เนื้อหาในบทความต้องเป็นผลงานของผู้นิพนธ์เอง ไม่ได้ลอกเลียนหรือตัดทอนจากบทความอื่น โดยไม่ได้รับอนุญาตหรือไม่ได้อ้างอิงอย่างเหมาะสม การแก้ไขหรือให้ข้อมูลเพิ่มเติมแก่กองบรรณาธิการ จะต้องเสร็จสิ้นเป็นที่เรียบร้อยก่อนจะได้รับพิจารณาตีพิมพ์ และบทความที่ตีพิมพ์แล้วเป็นสมบัติ ของลำปางเวชสาร
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