奥密克戎时代老年 COVID-19 肺炎患者早期进展的风险因素分析和列线图。

Risk Factor Analysis and Nomogram for Early Progression of COVID-19 Pneumonia in Older Adult Patients in the Omicron Era.

机构信息

Department of Geriatrics, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, People's Republic of China.

Clinical Research Center, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, People's Republic of China.

出版信息

Clin Interv Aging. 2024 Mar 11;19:439-449. doi: 10.2147/CIA.S453057. eCollection 2024.

Abstract

BACKGROUND AND OBJECTIVE

Timely recognition of risk factors for early progression in older adult patients with COVID-19 is of great significance to the following clinical management. This study aims to analyze the risk factors and create a nomogram for early progression in older adult patients with COVID-19 in the Omicron era.

METHODS

A total of 272 older adults infected with COVID-19 admitted from December 2022 to February 2023 were retrospectively recruited. Risk factor selection was determined using the logistic and the least absolute shrinkage and selection operator (LASSO) regression. A nomogram was then created to predict early progression, followed by the internal validation and assessment of its performance through plotting the receiver operating characteristic (ROC), calibration, and decision curves.

RESULTS

A total of 83 (30.5%) older adult patients presented an early progression on chest CT after 3-5 days of admission under standard initiate therapy. Six independent predictive factors were incorporated into the nomogram to predict the early progression, including CRP > 10 mg/L, IL-6 > 6.6 pg/mL, LDH > 245 U/L, CD4 T-lymphocyte count <400/µL, the Activities of Daily Living (ADL) score ≤40 points, and the Mini Nutritional Assessment Scale-Short Form (MNA-SF) score ≤7 points. The area under the curve (AUC) of the nomogram in discriminating older adult patients who had risk factors in the training and validation cohort was 0.857 (95% CI 0.798, 0.916) and 0.774 (95% CI 0.667, 0.881), respectively. The calibration and decision curves demonstrated a high agreement in the predicted and observed risks, and the acceptable net benefit in predicting the early progression, respectively.

CONCLUSION

We created a nomogram incorporating highly available laboratory data and the Comprehensive Geriatric Assessment (CGA) findings that effectively predict early-stage progression in older adult patients with COVID-19 in the Omicron era.

摘要

背景与目的

及时识别 COVID-19 老年患者早期进展的危险因素对后续临床管理具有重要意义。本研究旨在分析奥密克戎时代 COVID-19 老年患者早期进展的危险因素,并建立预测模型。

方法

回顾性招募了 2022 年 12 月至 2023 年 2 月期间因 COVID-19 住院的 272 名老年患者。采用逻辑回归和最小绝对值收缩和选择算子(LASSO)回归确定危险因素选择。然后创建一个预测模型,通过绘制受试者工作特征(ROC)曲线、校准和决策曲线评估内部验证和性能。

结果

在标准起始治疗后 3-5 天,共有 83 名(30.5%)老年患者的胸部 CT 显示早期进展。纳入了 6 个独立的预测因素到预测模型中,包括 CRP > 10mg/L、IL-6 > 6.6pg/mL、LDH > 245U/L、CD4 T 淋巴细胞计数 <400/µL、日常生活活动(ADL)评分≤40 分和迷你营养评估量表-简短形式(MNA-SF)评分≤7 分。该预测模型在训练和验证队列中区分有危险因素的老年患者的曲线下面积(AUC)分别为 0.857(95%CI 0.798,0.916)和 0.774(95%CI 0.667,0.881)。校准和决策曲线分别表明在预测和观察风险方面具有高度一致性,以及在预测早期进展方面具有可接受的净收益。

结论

我们建立了一个包含高度可用的实验室数据和全面老年评估(CGA)结果的预测模型,可以有效地预测奥密克戎时代 COVID-19 老年患者的早期进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eadb/10942253/8388e6013f3b/CIA-19-439-g0001.jpg

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