Estimating rate of lung function change using clinical spirometry data.

IF 3.6 3区医学 Q1 RESPIRATORY SYSTEM

BMJ Open Respiratory Research Pub Date : 2024-10-03 DOI:10.1136/bmjresp-2023-001896

Aparna Balasubramanian, Christopher Cervantes, Andrew S Gearhart, Nirupama Putcha, Ashraf Fawzy, Meredith C McCormack, Anil Singh, Robert A Wise, Nadia N Hansel

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引用次数: 0

Abstract

Rationale: In chronic obstructive pulmonary disease (COPD), accurately estimating lung function from electronic health record (EHR) data would be beneficial but requires addressing complexities in clinically obtained testing. This study compared analytic methods for estimating rate of forced expiratory volume in one second (FEV₁) change from EHR data.

Methods: We estimated rate of FEV₁ change in patients with COPD from a single centre who had ≥3 outpatient tests spanning at least 1 year. Estimates were calculated as both an absolute mL/year and a relative %/year using non-regressive (Total Change, Average Change) and regressive (Quantile, RANSAC, Huber) methods. We compared distributions of the estimates across methods focusing on extreme values. Univariate zero-inflated negative binomial regressions tested associations between estimates and all-cause or COPD hospitalisations. Results were validated in an external cohort.

Results: Among 1417 participants, median rate of change was approximately -30 mL/year or -2%/year. Non-regressive methods frequently generated erroneous estimates due to outlier first measurements or short intervals between tests. Average change yielded the most extreme estimates (minimum=-3761 mL/year), while regressive methods, and Huber specifically, minimised extreme estimates. Huber, Total Change and Quantile FEV₁ slope estimates were associated with all-cause hospitalisations (Huber incidence rate ratio 0.98, 95% CI 0.97 to 0.99, p<0.001). Huber estimates were also associated with smoking status, comorbidities and prior hospitalisations. Similar results were identified in an external validation cohort.

Conclusions: Using EHR data to estimate FEV₁ rate of change is clinically applicable but sensitive to challenges intrinsic to clinically obtained data. While no analytic method will fully overcome these complexities, we identified Huber regression as useful in defining an individual's lung function change using EHR data.

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利用临床肺活量数据估算肺功能变化率。

理由：对于慢性阻塞性肺病（COPD）患者来说，从电子健康记录（EHR）数据中准确估计肺功能是有益的，但需要解决临床测试中的复杂问题。本研究比较了从电子病历数据中估算一秒钟用力呼气容积（FEV1）变化率的分析方法：我们估算了来自单一中心的 COPD 患者的 FEV1 变化率，这些患者至少在 1 年内接受了 3 次门诊测试。采用非回归法（总变化、平均变化）和回归法（定量法、RANSAC、Huber）计算出绝对毫升/年和相对%/年的估计值。我们比较了各种方法的估计值分布，重点关注极值。单变量零膨胀负二项回归测试了估计值与全因或慢性阻塞性肺病住院率之间的关联。结果在外部队列中得到验证：在 1417 名参与者中，中位变化率约为-30 毫升/年或-2%/年。由于首次测量结果离群或测试间隔时间短，非回归方法经常产生错误的估计值。平均变化产生了最极端的估计值（最小值=-3761 毫升/年），而回归方法，特别是 Huber 方法，将极端估计值降至最低。Huber、总变化和定量 FEV1 斜率估计值与全因住院率相关（Huber 发病率比为 0.98，95% CI 为 0.97 至 0.99，p 结论：使用电子病历数据估算 FEV1 变化率适用于临床，但容易受到临床数据固有挑战的影响。虽然没有一种分析方法能完全克服这些复杂性，但我们发现 Huber 回归法在使用电子病历数据定义个人肺功能变化时非常有用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMJ Open Respiratory Research RESPIRATORY SYSTEM-

CiteScore

6.60

自引率

2.40%

发文量

审稿时长

12 weeks

期刊介绍： BMJ Open Respiratory Research is a peer-reviewed, open access journal publishing respiratory and critical care medicine. It is the sister journal to Thorax and co-owned by the British Thoracic Society and BMJ. The journal focuses on robustness of methodology and scientific rigour with less emphasis on novelty or perceived impact. BMJ Open Respiratory Research operates a rapid review process, with continuous publication online, ensuring timely, up-to-date research is available worldwide. The journal publishes review articles and all research study types: Basic science including laboratory based experiments and animal models, Pilot studies or proof of concept, Observational studies, Study protocols, Registries, Clinical trials from phase I to multicentre randomised clinical trials, Systematic reviews and meta-analyses.