Development and validation of a prediction model for in-hospital mortality in older adults with acute poisoning.

BackgroundThis study aimed to develop a mortality risk model for older adult patients with acute poisoning, addressing the lack of age-specific tools.MethodsA retrospective study was conducted to develop and validate a nomogram for predicting in-hospital mortality. The training cohort included 452 patients (62.2% men; 51.3% ≥70 years; main poisoning types: pesticides, 39.9%; drugs, 28.2%), with 133 patients in an external validation cohort. Independent risk factors were identified through logistic regression, and the nomogram was developed in R. Model performance was assessed using area under the curve, sensitivity, specificity, calibration, and decision curve analysis; external validation was performed using data from another hospital.ResultsMultivariate analysis identified independent risk factors for in-hospital mortality: age ≥70 years (odds ratio = 2.66), heart rate <60 or ≥110 bpm (odds ratio = 2.00), lactate ≥3.5 mmol/L (odds ratio = 2.61), white blood count ≥15 × 109/L (odds ratio = 3.46), and myoglobin ≥1000 ng/mL (odds ratio = 8.62). Internal validation showed an area under the curve of 0.824, sensitivity of 72.4%, and specificity of 76.1%. External validation showed an area under the curve of 0.854, sensitivity of 85.3%, and specificity of 75.8%.ConclusionThe nomogram effectively predicts in-hospital mortality in older adult patients with acute poisoning, outperforming conventional scores. It enables rapid risk stratification within 24 h of admission to guide early intervention.