Suppr超能文献

qSOFA、PRIEST、PAINT和ISARIC4C评分在预测75岁以上COVID-19患者严重预后中的比较分析

Comparative Analysis of qSOFA, PRIEST, PAINT, and ISARIC4C Scores in Predicting Severe COVID-19 Outcomes Among Patients Aged over 75 Years.

作者信息

Rosca Daniela, Krishna Vamsi, Chetarajupalli Chandramouli, Jianu Adelina Maria, Deak Ilona Emoke, Virzob Claudia Raluca Balasa, Laitin Sorina Maria Denisa, Boruga Madalina, Lighezan Rodica

机构信息

Doctoral School, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania.

Sri Devaraj Urs Medical College, Kolar 563101, India.

出版信息

Diseases. 2024 Nov 28;12(12):304. doi: 10.3390/diseases12120304.

Abstract

BACKGROUND

Elderly patients, particularly those over 75 years old, have been disproportionately affected by COVID-19, exhibiting higher rates of severe outcomes, such as ICU admissions and mortality. This study aimed to evaluate and compare the effectiveness of various clinical scoring systems-qSOFA, PRIEST, PAINT, and ISARIC4C-in predicting ICU admission, the need for mechanical ventilation, and mortality among elderly COVID-19 patients.

METHODS

In this retrospective cohort study conducted at two tertiary care hospitals, 131 elderly patients (aged ≥ 75) and 226 younger controls (aged < 65) with confirmed COVID-19 were included. Clinical scores were computed at admission and five days after symptom onset. Kaplan-Meier survival analysis and Receiver Operating Characteristic (ROC) curve analysis were performed to assess the predictive performance of the scores regarding severe outcomes.

RESULTS

Kaplan-Meier analysis indicated significantly lower survival probabilities for elderly patients with high scores at admission. Those with an ISARIC4C score above 11.8 had a survival probability of 25% compared to 74% for those below this threshold ( < 0.001). Similarly, elderly patients with a qSOFA score above 2.1 had a survival probability of 36% compared to 72% for those with lower scores ( < 0.001). The PRIEST and PAINT scores also demonstrated predictive validity; patients with a PRIEST score above 6.3 and a PAINT score above 6.5 at admission showed comparable decreases in survival probabilities. ROC analysis at five days post-symptom onset revealed that the ISARIC4C score had the highest area under the curve (AUC) of 0.772, suggesting excellent predictive validity for severe outcomes, including mortality. The optimal cutoffs identified were 11.2 for ISARIC4C, 6.3 for PRIEST, and 6.5 for PAINT, each displaying high sensitivity and specificity.

CONCLUSIONS

The ISARIC4C, qSOFA, PRIEST, and PAINT scores are robust predictors of severe outcomes in elderly COVID-19 patients over 75 years old, as confirmed by Kaplan-Meier and ROC analyses. These tools can be crucial for early identification of patients at high risk of adverse outcomes, guiding clinical decision making, and optimizing resource allocation. The use of these scoring systems should be encouraged in clinical settings to enhance the management of elderly COVID-19 patients. Further research is necessary to validate these findings across different populations and settings.

摘要

背景

老年患者,尤其是75岁以上的患者,受新冠病毒病(COVID-19)的影响尤为严重,出现重症结局(如入住重症监护病房和死亡)的比例更高。本研究旨在评估和比较各种临床评分系统——快速序贯器官衰竭评估(qSOFA)、老年人重症肺炎风险评估(PRIEST)、肺炎严重程度综合评估(PAINT)和英国感染协会快速临床评估(ISARIC4C)——在预测老年COVID-19患者入住重症监护病房、机械通气需求和死亡率方面的有效性。

方法

在两家三级护理医院进行的这项回顾性队列研究中,纳入了131例确诊COVID-19的老年患者(年龄≥75岁)和226例年轻对照者(年龄<65岁)。在入院时和症状出现后五天计算临床评分。进行Kaplan-Meier生存分析和受试者工作特征(ROC)曲线分析,以评估评分对重症结局的预测性能。

结果

Kaplan-Meier分析表明,入院时评分高的老年患者生存概率显著降低。ISARIC4C评分高于11.8的患者生存概率为25%,而低于该阈值(<11.8)的患者生存概率为74%(P<0.001)。同样,qSOFA评分高于2.1的老年患者生存概率为36%,而评分较低的患者生存概率为72%(P<0.001)。PRIEST和PAINT评分也显示出预测有效性;入院时PRIEST评分高于6.3和PAINT评分高于6.5的患者生存概率下降幅度相当。症状出现后五天的ROC分析显示,ISARIC4C评分的曲线下面积(AUC)最高,为0.772,表明对包括死亡率在内的重症结局具有良好的预测有效性。确定的最佳截断值分别为ISARIC4C为11.2、PRIEST为6.3、PAINT为6.5,每个截断值均显示出高敏感性和特异性。

结论

Kaplan-Meier和ROC分析证实,ISARIC4C、qSOFA、PRIEST和PAINT评分是75岁以上老年COVID-19患者重症结局的有力预测指标。这些工具对于早期识别不良结局高风险患者、指导临床决策和优化资源分配至关重要。应鼓励在临床环境中使用这些评分系统,以加强对老年COVID-19患者的管理。有必要进一步开展研究,在不同人群和环境中验证这些发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b201/11727413/9095e359a529/diseases-12-00304-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验