Wallace Emma, McDowell Ronald, Bennett Kathleen, Fahey Tom, Smith Susan M
HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland.
Population and Health Sciences Division, Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland.
BMJ Open. 2016 Nov 14;6(11):e012336. doi: 10.1136/bmjopen-2016-012336.
Emergency admission is associated with the potential for adverse events in older people and risk prediction models are available to identify those at highest risk of admission. The aim of this study was to externally validate and compare the performance of the Probability of repeated admission (Pra) risk model and a modified version (incorporating a multimorbidity measure) in predicting emergency admission in older community-dwelling people.
15 general practices (GPs) in the Republic of Ireland.
n=862, ≥70 years, community-dwelling people prospectively followed up for 2 years (2010-2012).
Pra risk model (original and modified) calculated for baseline year where ≥0.5 denoted high risk (patient questionnaire, GP medical record review) of future emergency admission.
Emergency admission over 1 year (GP medical record review).
descriptive statistics, model discrimination (c-statistic) and calibration (Hosmer-Lemeshow statistic).
Of 862 patients, a total of 154 (18%) had ≥1 emergency admission(s) in the follow-up year. 63 patients (7%) were classified as high risk by the original Pra and of these 26 (41%) were admitted. The modified Pra classified 391 (45%) patients as high risk and 103 (26%) were subsequently admitted. Both models demonstrated only poor discrimination (original Pra: c-statistic 0.65 (95% CI 0.61 to 0.70); modified Pra: c-statistic 0.67 (95% CI 0.62 to 0.72)). When categorised according to risk-category model, specificity was highest for the original Pra at cut-point of ≥0.5 denoting high risk (95%), and for the modified Pra at cut-point of ≥0.7 (95%). Both models overestimated the number of admissions across all risk strata.
While the original Pra model demonstrated poor discrimination, model specificity was high and a small number of patients identified as high risk. Future validation studies should examine higher cut-points denoting high risk for the modified Pra, which has practical advantages in terms of application in GP. The original Pra tool may have a role in identifying higher-risk community-dwelling older people for inclusion in future trials aiming to reduce emergency admissions.
急诊入院与老年人发生不良事件的可能性相关，且有风险预测模型可用于识别入院风险最高的人群。本研究的目的是对重复入院概率（Pra）风险模型及其改良版本（纳入多病共存指标）在预测老年社区居民急诊入院方面的性能进行外部验证和比较。
爱尔兰共和国的15家全科诊所。
n = 862名年龄≥70岁的社区居民，前瞻性随访2年（2010 - 2012年）。
计算基线年份的Pra风险模型（原始版本和改良版本），≥0.5表示未来急诊入院的高风险（患者问卷、全科医生病历审查）。
1年内的急诊入院情况（全科医生病历审查）。
描述性统计、模型区分度（c统计量）和校准（Hosmer-Lemeshow统计量）。
862例患者中，共有154例（18%）在随访年度有≥1次急诊入院。原始Pra模型将63例患者（7%）分类为高风险，其中26例（41%）入院。改良Pra模型将391例患者（45%）分类为高风险，随后103例（26%）入院。两个模型的区分度均较差（原始Pra：c统计量0.65（95%CI 0.61至0.70）；改良Pra：c统计量0.67（95%CI 0.62至0.72））。根据风险类别模型进行分类时，原始Pra在≥0.5表示高风险的切点处特异性最高（95%），改良Pra在≥0.7的切点处特异性最高（95%）。两个模型在所有风险分层中均高估了入院人数。
虽然原始Pra模型的区分度较差，但模型特异性较高，且识别出的高风险患者数量较少。未来的验证研究应检查改良Pra表示高风险的更高切点，这在全科医生应用方面具有实际优势。原始Pra工具可能在识别高风险社区老年人群体以纳入未来旨在减少急诊入院的试验中发挥作用。
