Department of Infection and Tropical Medicine, Royal Hallamshire Hospital, Sheffield, UK.
Department of Microbiology, Royal Derby Hospital, Derby, UK.
J Antimicrob Chemother. 2021 Jul 15;76(8):2204-2212. doi: 10.1093/jac/dkab127.
Outpatient parenteral antimicrobial therapy (OPAT) is increasingly used to treat a variety of infections. However, hospital readmissions remain relatively common. We examined the external validity and clinical usefulness of a previously derived risk prediction model for 30 day unplanned hospitalization in patients receiving OPAT.
A retrospective cohort study was conducted at two large teaching hospitals in the UK. The design comprised quasi-external temporal validation on patients from the same OPAT setting as the model development, and broader external validation on patients from a different setting. The model predictors were age, prior hospitalizations in the preceding 12 months, Charlson comorbidity score, concurrent IV antimicrobial therapy, type of infection and mode of OPAT treatment. Discriminative ability, calibration and clinical usefulness were assessed.
Data from 2578 OPAT patients were analysed. The rates of 30 day unplanned hospitalization were 11.5% (123/1073), 12.9% (140/1087) and 25.4% (106/418) in the model derivation, temporal validation and broader external validation cohorts, respectively. The discriminative ability of the prediction model was adequate on temporal validation (c-statistic 0.75; 95% CI: 0.71-0.79) and acceptable on broader validation (c-statistic 0.67; 95% CI: 0.61-0.73). In both external cohorts, the model displayed excellent calibration between observed and predicted probabilities. Decision curve analysis showed increased net benefit across a range of meaningful risk thresholds.
A simple risk prediction model for unplanned readmission in OPAT patients demonstrated reproducible predictive performance, broad clinical transportability and clinical usefulness. This model may help improve OPAT outcomes through better identification of high-risk patients and provision of tailored care.
门诊静脉注射抗菌疗法（OPAT）越来越多地用于治疗各种感染。然而，患者住院率仍然相对较高。本研究旨在评估先前开发的 30 天内非计划性住院风险预测模型在接受 OPAT 治疗的患者中的外部有效性和临床实用性。
在英国的两家大型教学医院进行了回顾性队列研究。设计包括在与模型开发相同的 OPAT 环境中对患者进行准外部时间验证，以及在不同环境中对患者进行更广泛的外部验证。模型预测因子包括年龄、前 12 个月内的住院次数、Charlson 合并症评分、同时进行的静脉内抗菌治疗、感染类型和 OPAT 治疗方式。评估了判别能力、校准和临床实用性。
共分析了 2578 例 OPAT 患者的数据。在模型推导、时间验证和更广泛的外部验证队列中，30 天内非计划性住院率分别为 11.5%（123/1073）、12.9%（140/1087）和 25.4%（106/418）。预测模型在时间验证上具有良好的判别能力（C 统计量 0.75；95%CI：0.71-0.79），在更广泛的验证上具有可接受的判别能力（C 统计量 0.67；95%CI：0.61-0.73）。在两个外部队列中，模型在观察到的和预测的概率之间均具有极好的校准。决策曲线分析表明，在一系列有意义的风险阈值下，净收益增加。
用于 OPAT 患者非计划性再入院的简单风险预测模型具有可重复的预测性能、广泛的临床适用性和临床实用性。该模型可以通过更好地识别高风险患者和提供针对性的护理，来改善 OPAT 结果。
