Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK.
University Hospitals Coventry and Warwickshire, Coventry, CV2 2DX, UK.
BMC Geriatr. 2023 Jan 23;23(1):42. doi: 10.1186/s12877-022-03649-5.
Postal screening has not previously been validated as a method for identifying fall and fracture risk in community-dwelling populations. We examined prognostic performance of a postal risk screener used in the UK Prevention of Falls Injury Trial (PreFIT; ISRCTN71002650), to predict any fall, recurrent falls, and fractures over 12 months. We tested whether adding variables would improve screener performance.
Nine thousand eight hundred and eight community-dwelling participants, aged 70 years and older, and 63 general practices in the UK National Health Service (NHS) were included in a large, pragmatic cluster randomised trial comparing screen and treat fall prevention interventions. The short postal screener was sent to all participants in the trial intervention arms as an A4 sheet to be completed and returned to the GP (n = 6,580). The postal screener items were embedded in the baseline pre-randomisation postal questionnaire for all arms of the trial (n = 9,808). We assessed discrimination and calibration using area under the curve (AUC). We identified additional predictors using data from the control arm and applied these coefficients to internal validation models in the intervention arm participants. We used logistic regression to identify additional predictor variables.
A total of 10,743 falls and 307 fractures were reported over 12 months. Over one third of participants 3,349/8,136 (41%) fell at least once over 12 month follow up. Response to the postal screener was high (5,779/6,580; 88%). Prediction models showed similar discriminatory ability in both control and intervention arms, with discrimination values for any fall AUC 0.67 (95% CI 0.65 to 0.68), and recurrent falls (AUC 0.71; 95% CI 0.69, 0.72) but poorer discrimination for fractures (AUC 0.60; 95% CI 0.56, 0.64). Additional predictor variables improved prediction of falls but had modest effect on fracture, where AUC rose to 0.71 (95% CI 0.67 to 0.74). Calibration slopes were very close to 1.
A short fall risk postal screener was acceptable for use in primary care but fall prediction was limited, although consistent with other tools. Fracture and fall prediction were only partially reliant on fall risk although were improved with the additional variables.
邮寄筛查此前尚未经过验证，无法作为识别社区居住人群中跌倒和骨折风险的方法。我们研究了英国预防跌倒伤害试验（PreFIT；ISRCTN71002650）中使用的邮寄风险筛查器在预测 12 个月内任何跌倒、复发性跌倒和骨折方面的预后表现。我们测试了添加变量是否会提高筛查器的性能。
9808 名年龄在 70 岁及以上的社区居住参与者和英国国民保健署（NHS）的 63 个普通实践被纳入一项大型、实用的群组随机试验，比较了筛查和治疗跌倒预防干预措施。简短的邮寄筛查器作为 A4 页发送给试验干预组的所有参与者，要求他们填写并寄回给全科医生（n=6580）。邮寄筛查器项目嵌入了试验所有组别的基线预随机邮寄问卷中（n=9808）。我们使用曲线下面积（AUC）评估区分度和校准度。我们使用对照臂的数据确定了其他预测因子，并将这些系数应用于干预臂参与者的内部验证模型。我们使用逻辑回归来确定其他预测变量。
在 12 个月的随访中，共报告了 10743 次跌倒和 307 次骨折。在超过 12 个月的随访中，超过三分之一的参与者（3349/8136；41%）至少跌倒一次。对邮寄筛查器的反应率很高（5779/6580；88%）。预测模型在对照组和干预组中均表现出相似的区分能力，任何跌倒的 AUC 值为 0.67（95%CI 0.65 至 0.68），复发性跌倒的 AUC 值为 0.71（95%CI 0.69，0.72），但骨折的区分能力较差（AUC 为 0.60；95%CI 0.56，0.64）。额外的预测变量提高了跌倒的预测能力，但对骨折的影响较小，AUC 上升至 0.71（95%CI 0.67 至 0.74）。校准斜率非常接近 1。
简短的跌倒风险邮寄筛查器可用于初级保健，但跌倒预测能力有限，尽管与其他工具一致。骨折和跌倒的预测仅部分依赖于跌倒风险，尽管添加额外变量后有所改善。
