Enterprise Intelligence and Data Solutions (EIDS) Program Office, Program Executive Office, Defense Healthcare Management Systems (PEO DHMS), San Antonio, Texas, USA.
Defense and Veterans Center for Integrative Pain Management, Department of Anesthesiology, Uniformed Services University, Bethesda, Maryland, USA.
Pain Med. 2022 Oct 29;23(11):1902-1907. doi: 10.1093/pm/pnac064.
To evaluate the current cutoff score and a recalibrated adaptation of the Veterans Health Administration (VHA) Risk Index for Serious Prescription Opioid-Induced Respiratory Depression or Overdose (RIOSORD) in active duty service members.
Retrospective case-control.
Military Health System.
Active duty service members dispensed ≥ 1 opioid prescription between January 1, 2018, and December 31, 2019.
Service members with a documented opioid overdose were matched 1:10 to controls. An active duty-specific (AD) RIOSORD was constructed using the VHA RIOSORD components. Analyses examined the risk stratification and predictive characteristics of two RIOSORD versions (VHA and AD).
Cases (n = 95) were matched with 950 controls. Only 6 of the original 17 elements were retained in the AD RIOSORD. Long-acting or extended-release opioid prescriptions, antidepressant prescriptions, hospitalization, and emergency department visits were associated with overdose events. The VHA RIOSORD had fair performance (C-statistic 0.77, 95% CI 0.75, 0.79), while the AD RIOSORD did not demonstrate statistically significant performance improvement (C-statistic 0.78, 95% CI, 0.77, 0.80). The DoD selected cut point (VHA RIOSORD > 32) only identified 22 of 95 ORD outcomes (Sensitivity 0.23), while an AD-specific cut point (AD RIOSORD > 16) correctly identified 53 of 95 adverse events (Sensitivity 0.56).
Results highlight the need to continually recalibrate predictive models and to consider multiple measures of performance. Although both models had similar overall performance with respect to the C-statistic, an AD-specific index threshold improves sensitivity. The calibrated AD RIOSORD does not represent an end-state, but a bridge to a future model developed on a wider range of patient variables, taking into consideration features that capture both care received, and care that was not received.
评估退伍军人事务部（VA）严重处方类阿片诱导呼吸抑制或过量风险指数（RIOSORD）的当前截断值和经修正后用于现役军人的适应性。
回顾性病例对照。
医疗保健系统。
2018 年 1 月 1 日至 2019 年 12 月 31 日期间，有≥1 份阿片类药物处方的现役军人。
记录阿片类药物过量的现役军人与对照 1:10 匹配。使用 VA RIOSORD 成分构建特定于现役军人的（AD）RIOSORD。分析检查了两种 RIOSORD 版本（VA 和 AD）的风险分层和预测特征。
病例（n=95）与 950 名对照匹配。AD RIOSORD 仅保留了原始 17 个元素中的 6 个。长效或缓释阿片类药物处方、抗抑郁药处方、住院和急诊就诊与过量事件相关。VA RIOSORD 具有良好的性能（C 统计量为 0.77，95%CI 为 0.75，0.79），而 AD RIOSORD 没有表现出统计学上显著的性能改善（C 统计量为 0.78，95%CI 为 0.77，0.80）。国防部选择的切点（VA RIOSORD > 32）仅识别出 95 例 ORD 结果中的 22 例（敏感性 0.23），而特定于 AD 的切点（AD RIOSORD > 16）正确识别出 95 例不良事件中的 53 例（敏感性 0.56）。
结果强调需要不断修正预测模型，并考虑多种性能衡量标准。虽然两种模型在 C 统计量方面的总体性能相似，但特定于 AD 的指数阈值可提高敏感性。校准后的 AD RIOSORD 不是最终状态，而是一个桥梁，通向一个基于更广泛患者变量的未来模型，同时考虑到捕捉所接受的护理和未接受的护理的特征。
