We developed and evaluated a model to predict serious outcomes among 243 adults ≥60 years old with medically attended respiratory illness and laboratory‐confirmed respiratory syncytial virus (RSV); 47 patients had a serious outcome defined as hospital admission, emergency department (ED) visit, or pneumonia diagnosis. The model used logistic regression with penalized maximum likelihood estimation. The reduced penalized model included age ≥ 75 years, ≥1 ED visit in prior year, crackles/rales, tachypnea, wheezing, new/increased sputum, and new/increased dyspnea. The optimal score cutoff yielded sensitivity and specificity of 66.0% and 81.6%. This prediction model provided moderate utility for identifying older adults with elevated risk of complicated RSV illness.

中文翻译：

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在连续 12 个季节内预测患有门诊 RSV 呼吸道疾病的老年人的严重 RSV 相关结果。

我们开发并评估了一个模型，用于预测 243 名 60 岁以上的成人患有呼吸道疾病和实验室确诊的呼吸道合胞病毒 (RSV) 的严重后果；47 名患者的严重结果定义为入院、急诊科 (ED) 就诊或肺炎诊断。该模型使用逻辑回归和惩罚最大似然估计。减少的惩罚模型包括年龄 ≥ 75 岁、前一年 ≥ 1 次 ED 就诊、噼啪声/罗音、呼吸急促、喘息、新的/增加的痰和新的/增加的呼吸困难。最佳评分临界值产生的敏感性和特异性分别为 66.0% 和 81.6%。该预测模型为识别患有复杂 RSV 疾病风险升高的老年人提供了中等效用。