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一项使用STRATIFY工具预测住院患者跌倒的研究的系统评价和荟萃分析:该工具的效果如何?

A systematic review and meta-analysis of studies using the STRATIFY tool for prediction of falls in hospital patients: how well does it work?

作者信息

Oliver David, Papaioannou Alexandra, Giangregorio Lora, Thabane Lehana, Reizgys Katerina, Foster Gary

机构信息

School of Health and Social Care (& Institute of Health Sciences), University of Reading, London Road, Reading, RG1 5AQ, UK.

出版信息

Age Ageing. 2008 Nov;37(6):621-7. doi: 10.1093/ageing/afn203. Epub 2008 Oct 1.

Abstract

BACKGROUND

STRATIFY is a prediction tool developed for use in for hospital inpatients, using a 0-5 score to predict patients who will fall. It has been widely used as part of hospital fall prevention plans, but it is not clear how good its operational utility is in a variety of settings.

OBJECTIVES

(i) to describe the predictive validity of STRATIFY for identifying hospital inpatients who will fall via systematic review and descriptive analysis, based on its use in several prospective cohort studies of hospital inpatients; (ii) to describe the predictive validity of STRATIFY among inpatients in geriatric rehabilitation via meta-analysis and (iii) in turn, to help practitioners and institutions wishing to implement interventions to prevent in-hospital falls.

METHODS

a systematic literature review of prospective validation studies of STRATIFY for falls prediction in hospital inpatients. For inclusion, studies must report prospective validation cohorts, with sufficient data for calculation of sensitivity (SENS), specificity (SPEC), negative and positive predictive value (NPV and PPV), total predictive accuracy (TPA) and 95% confidence intervals (CI). We performed meta-analysis using precision-weighted fixed- and random-effects models using studies that evaluated STRATIFY among geriatric rehabilitation inpatients.

MEASUREMENTS

key features of the patient population, setting, study design and numbers of falls/fallers were abstracted. SENS, SPEC, PPV, NPV, TPA and 95% CI were reported for each cohort. Pooled values and chi-squared test for homogeneity were reported for a meta-analysis of studies conducted in geriatric rehabilitation settings.

RESULTS

forty-one papers were identified by the search, with eight ultimately eligible for inclusion in the systematic review and four for inclusion in the meta-analysis. The predictive validity of STRATIFY, using a random-effects model, for the four studies involving geriatric patients was as follows: SENS 67.2 (95% CI 60.8, 73.6), SPEC 51.2 (95% CI 43.0, 59.3), PPV 23.1 (95% CI 14.9, 31.2), NPV 86.5 (95% CI 78.4, 94.6). The Q((3)) test for homogeneity was not significant for SENS at P = 0.36, but it was significant at P < 0.01 for SPEC, PPV and NPV. TPA across all four studies varied from 43.2 to 60.0.

CONCLUSION

the current study reveals a relatively high NPV and low PPV and TPA for the STRATIFY instrument, suggesting that it may not be optimal for identifying high-risk individuals for fall prevention. Further, the study demonstrates that population and setting affect STRATIFY performance.

摘要

背景

STRATIFY是一种为医院住院患者开发的预测工具,使用0至5分来预测可能跌倒的患者。它已被广泛用作医院跌倒预防计划的一部分,但尚不清楚其在各种环境中的实际应用效果如何。

目的

(i)通过系统评价和描述性分析,基于其在多项住院患者前瞻性队列研究中的应用,描述STRATIFY在识别可能跌倒的住院患者方面的预测效度;(ii)通过荟萃分析描述STRATIFY在老年康复住院患者中的预测效度;(iii)进而帮助希望实施预防住院跌倒干预措施的从业者和机构。

方法

对STRATIFY用于预测住院患者跌倒的前瞻性验证研究进行系统的文献综述。纳入标准为研究必须报告前瞻性验证队列,并提供足够的数据以计算敏感性(SENS)、特异性(SPEC)、阴性和阳性预测值(NPV和PPV)、总预测准确性(TPA)及95%置信区间(CI)。我们对评估STRATIFY在老年康复住院患者中的研究,使用精确加权固定效应和随机效应模型进行荟萃分析。

测量指标

提取患者群体、环境、研究设计的关键特征以及跌倒/跌倒者的数量。报告每个队列的SENS、SPEC、PPV、NPV、TPA及95%CI。对在老年康复环境中进行的研究进行荟萃分析时,报告合并值和同质性卡方检验结果。

结果

检索到41篇论文,最终8篇符合纳入系统评价的标准,4篇符合纳入荟萃分析的标准。对于涉及老年患者的四项研究,使用随机效应模型时STRATIFY的预测效度如下:SENS 67.2(95%CI 60.8,73.6),SPEC 51.2(95%CI 43.0,59.3),PPV 23.1(95%CI 14.9,31.2),NPV 86.5(95%CI 78.4,94.6)。SENS的同质性Q((3))检验P = 0.36时不显著,但SPEC、PPV和NPV在P < 0.01时显著。四项研究的TPA在43.2至60.0之间变化。

结论

当前研究表明,STRATIFY工具的NPV相对较高,而PPV和TPA较低,这表明它可能并非识别预防跌倒高危个体的最佳工具。此外,研究表明人群和环境会影响STRATIFY的性能。

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