2022年 第13卷 第6期
《工程（英文）》 >> 2022年 第13卷 第6期 doi: 10.1016/j.eng.2021.07.021
新冠病毒肺炎转重的预测因素——对武汉集中隔离点内1753例患者进行的竞争性风险生存分析
a Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
b Heidelberg Institute of Global Health (HIGH), Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg 69117, Germany
c Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
d Department of Pulmonary and Critical Care Medicine, Beijing Hospital, Beijing 100730, China
e National Center of Gerontology,Institute of Geriatric Medicine, Beijing 100730, China
f Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, CA 94305, USA
g Peking Union Medical College Hospital, Beijing 100730, China
h State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
i National Clinical Research Center for Respiratory Diseases, Beijing 100029, China
j Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China–Japan Friendship Hospital, Beijing 100029, China
# These authors contributed equally to this work.
下一篇 上一篇
摘要
多数新冠病毒肺炎 (COVID-19) 研究主要侧重于研究患者在二级和三级医院内部、从普通病房到重症监护室的转移。在进行集中隔离的无症状患者或仅有轻度-中度症状的患者中，有关转变为重型新冠肺炎的预测因素还知之甚少。通过使用多变量竞争性风险生存分析方法，我们在入住武汉最大集中隔离点的患者中，发现了转变为重型新冠肺炎（而非康复）的几个重要预测因素，时间为 2020 年 2 月 6 日（隔离点开放之日）至 2020 年 3 月 9 日（隔离点关闭之日）。入住武汉集中隔离点的所有患者均为无症状或有轻度-中度新冠肺炎症状的患者。我们根据对该隔离中心内所有新冠肺炎患者 (n = 1753) 进行的一项队列研究得出的事件发生时间数据，执行了竞争性风险生存分析。我们考察的潜在预测因素是在入住该隔离中心时采集的常规患者数据、年龄、性别、呼吸症状、胃肠道症状、普通症状和计算机断层（CT）扫描表现。主要结果是从无症状或轻度-中度新冠肺炎症状到发生重型新冠肺炎或康复的时间。转变为重型新冠肺炎的预测因素是：男性性别[风险比 (HR) = 1.29, 95% 置信区间 (95%CI) 1.04–1.58，p = 0.018]、低龄和高龄、呼吸困难 (HR = 1.58，95%CI 1.24–2.01，p < 0.001) 以及毛玻璃样浑浊 (HR = 1.39，95%CI 1.04–1.86，p = 0.024) 和浸润影 (HR = 1.84，95%CI 1.22– 2.78，p = 0.004) 的 CT 表现。在有恶心和呕吐 (HR = 0.53，95%CI 0.30–0.96，p = 0.036) 以及头痛 (HR = 0.54，95%CI 0.29–0.99, p = 0.046) 的患者中，发现疾病出现进展的风险较低。我们的研究结果表明，即使是在资源匮乏的环境中，也有几种容易测量的因素（呼吸困难、性别和年龄）可用于识别疾病进展风险增高的轻型新冠肺炎患者。观察毛玻璃样浑浊和浸润影的 CT 表现可能是一个可负担的选项，可用于支持富资源型环境中的患者分检决策。常见的和非特异性的症状（头痛、恶心和呕吐）有可能导致识别出病情相对不太可能恶化的新冠肺炎患者，并随后进行集中隔离。应当根据该证据制定未来的公共卫生和临床指导意见，以提高无症状的或有轻度-重度症状的新冠肺炎患者的筛查、分检和监测。
补充材料
图片
Fig. 1
Fig. 2
Fig. 3
参考文献
[ 1 ] Nelson B. Too little or too much? Missing the Goldilocks zone of hospital capacity during COVID-19. BMJ 2020;369:m2332. 链接1
[ 2 ] Haroon S, Chandan JS, Middleton J, Cheng KK. COVID-19: breaking the chain of household transmission. BMJ 2020;370:m3181. 链接1
[ 3 ] Wilder-Smith A, Cook AR, Dickens BL. Institutional versus home isolation to curb the COVID-19 outbreak—authors’ reply. Lancet 2020;396(10263):1632–3. 链接1
[ 4 ] Chen S, Chen Q, Yang J, Lin L, Li L, Jiao L, et al. Curbing the COVID-19 pandemic with facility-based isolation of mild cases: a mathematical modeling study. J Travel Med 2020;28(2):taaa226. 链接1
[ 5 ] Chen S, Zhang Z, Yang J, Wang J, Zhai X, Bärnighausen T, et al. Fangcang shelter hospitals: a novel concept for responding to public health emergencies. Lancet 2020;395(10232):1305–14. 链接1
[ 6 ] The Atlantic. What’s behind South Korea’s COVID-19 exceptionalism [Internet]. The Atlantic Monthly Group; [updated 2020 May 6; cited 2020 May 14]. Available from: https://www.theatlantic.com/ideas/archive/2020/05/ whats-south-koreas-secret/611215/. 链接1
[ 7 ] Her M. Repurposing and reshaping of hospitals during the COVID-19 outbreak in South Korea. One Health 2020;10:100137. 链接1
[ 8 ] Chia ML, Him Chau DH, Lim KS, Yang Liu CW, Tan HK, Tan YR. Managing COVID-19 in a novel, rapidly deployable community isolation quarantine facility. Ann Intern Med 2021;174(2):247–51. 链接1
[ 9 ] Towards Data Science. COVID-19—what do we know about the situation in Vietnam? [Internet]. [updated 2020 May 2; cited 2020 Nov 13]. Available from: https://towardsdatascience.com/covid-19-what-do-we-know-about-thesituation-in-vietnam-82c195163d7e. 链接1
[10] Chen S, Yang J, Yang W, Wang C, Bärnighausen T. COVID-19 control in China during mass population movements at New Year. Lancet 2020;395 (10226):764–6. 链接1
[11] Centers for Disease Control and Prevention. Operational considerations for community isolation centers for COVID-19 in low-resource settings [Internet]. Washington, DC: US Department of Health & Human Services; [updated 2020 Aug 19; cited 2020 Sep 29]. Available from: https://www.cdc.gov/coronavirus/ 2019-ncov/global-covid-19/operational-considerations-isolation-centers.html. 链接1
[12] World Health Organization. Operational considerations for case management of COVID-19 in health facility and community. Interim guidance. Pediatria i Med Rodz 2020;16(1):27–32. 链接1
[13] Lipsitch M, Swerdlow DL, Finelli L. Defining the epidemiology of COVID-19— studies needed. N Engl J Med 2020;382(13):1194–6. 链接1
[14] Goh KJ, Choong MC, Cheong EH, Kalimuddin S, Wen SD, Phua GC, et al. Rapid progression to acute respiratory distress syndrome: review of current understanding of critical illness from COVID-19 infection. Ann Acad Med Singap 2020;49(1):1–9. 链接1
[15] Greenhalgh T, Koh GCH, Car J. COVID-19: a remote assessment in primary care. BMJ 2020;368:m1182. 链接1
[16] Li M, Lei P, Zeng B, Li Z, Yu P, Fan B, et al. Coronavirus disease (COVID-19): spectrum of CT findings and temporal progression of the disease. Acad Radiol 2020;27(5):603–8. 链接1
[17] Yousefzadegan S, Rezaei N. Case report: death due to novel coronavirus disease (COVID-19) in three brothers. Am J Trop Med Hyg 2020;102 (6):1203–4. 链接1
[18] Remuzzi A, Remuzzi G. COVID-19 and Italy: what next? Lancet 2020;395 (10231):1225–8. 链接1
[19] Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a singlecentered, retrospective, observational study. Lancet Respir Med 2020;8 (5):475–81. 链接1
[20] Vincent JL, Taccone FS. Understanding pathways to death in patients with COVID-19. Lancet Respir Med 2020;8(5):430–2. 链接1
[21] Chen J, Qi T, Liu L, Ling Y, Qian Z, Li T, et al. Clinical progression of patients with COVID-19 in Shanghai, China. J Infect 2020;80(5):e1–6. 链接1
[22] Wang L, He W, Yu X, Hu D, Bao M, Liu H, et al. Coronavirus disease 2019 in elderly patients: characteristics and prognostic factors based on 4-week follow-up. J Infect 2020;80(6):639–45. 链接1
[23] Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med 2020;180(7):934–43. 链接1
[24] Liang W, Liang H, Ou L, Chen B, Chen A, Li C et al.; China Medical Treatment Expert Group for COVID-19. Development and validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. JAMA Intern Med 2020;180(8):1081–9. 链接1
[25] Phua J, Weng L, Ling L, Egi M, Lim CM, Divatia JV et al.; Asian Critical Care Clinical Trials Group. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations. Lancet Respir Med 2020;8 (5):506–17. 链接1
[26] Liu W, Tao ZW, Wang L, Yuan ML, Liu K, Zhou L et al. Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease. Chin Med J 2020;133(9):1032–8. 链接1
[27] Liang WH, Guan WJ, Li CC, Li YM, Liang HR, Zhao Y, et al. Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei and outside Hubei: a nationwide analysis of China. Eur Respir J 2020;55(6):2000562. 链接1
[28] Wang X, Fang J, Zhu Y, Chen L, Ding F, Zhou R, et al. Clinical characteristics of non-critically ill patients with novel coronavirus infection (COVID-19) in a Fangcang hospital. Clin Microbiol Infect 2020;26(8):1063–8. 链接1
[29] Liao Y, Feng Y, Wang B, Wang H, Huang J, Wu Y, et al. Clinical characteristics and prognostic factors of COVID-19 patients progression to severe: a retrospective, observational study. Aging 2020;12(19):18853–65. 链接1
[30] Wang X. Mainland medics banking on experience to help HK fight COVID-19 [Internet]. Beijing: China Daily Information Co.; c1995–2021 [updated 2020 Aug 3; cited 2020 Aug 4]. Available online: https://www.chinadaily.com.cn/a/ 202008/03/WS5f27ad72a31083481725dd2e.html. 链接1
[31] The Lancet. Sustaining containment of COVID-19 in China. Lancet 2020;395 (10232):1230. 链接1
[32] Gilbert M, Dewatripont M, Muraille E, Platteau JP, Goldman M. Preparing for a responsible lockdown exit strategy. Nat Med 2020;26(5):643–4. 链接1
[33] Petersen E, Wasserman S, Lee SS, Go U, Holmes AH, Al-Abri S, et al. COVID-19— we urgently need to start developing an exit strategy. Int J Infect Dis 2020;96 (96):233–9. 链接1
[34] Chen S, Chen Q, Yang W, Xue L, Liu Y, Yang J, et al. Buying time for an effective epidemic response: the impact of a public holiday for outbreak control on COVID-19 epidemic spread. Engineering 2020;6(10):1108–14. 链接1
[35] National Health Commission of the People’s Republic of China. Manual for working in Fangcang shelter hospitals (3rd edition) [Internet]. Beijing: National Health Commission of the People’s Republic of China; [updated 2020 Feb 22; cited 2020 Feb 24]. Available from: https://mp.weixin.qq.com/ s/va9vs4HuP8wRQM5fALQcrg.Chinese. 链接1
[36] Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc 1999;94(446):496–509. 链接1
[37] Wolbers M, Koller MT, Stel VS, Schaer B, Jager KJ, Leffondré K, et al. Competing risks analyses: objectives and approaches. Eur Heart J 2014;35(42):2936–41. 链接1
[38] Lau B, Cole SR, Gange SJ. Competing risk regression models for epidemiologic data. Am J Epidemiol 2009;170(2):244–56. 链接1
[39] Hosmer DW, Lemeshow S, May S. Applied survival analysis: regression modeling of time to event data. New York: Wiley; 2002. 链接1
[40] McCaw ZR, Tian L, Vassy JL, Ritchie CS, Lee CC, Kim DH, et al. How to quantify and interpret treatment effects in comparative clinical studies of COVID-19. Ann Intern Med 2020;173(8):632–7. 链接1
[41] Schoenfeld D. Partial residuals for the proportional hazards regression model. Biometrika 1982;69(1):239–41. 链接1
[42] Austin PC, Fine JP. Practical recommendations for reporting Fine-Gray model analyses for competing risk data. Stat Med 2017;36(27):4391–400. 链接1
[43] Prettner K, Chen S, Kuhn M, Bloom DE. Effective pandemic management that minimises economic harm [Internet]. [updated 2021 Jan 4; cited 2021 Jan 22]. Available from: https://voxeu.org/article/effective-pandemic-managementminimises-economic-harm. 链接1
[44] Chen S, Prettner K, Kuhn M, Bloom DE. The economic burden of COVID-19 in the United States: estimates and projections under an infection-based herd immunity approach. J Econ Ageing 2021;20:100328. 链接1
[45] Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol 2020;146(1):110–8. 链接1
[46] Palaiodimos L, Kokkinidis DG, Li W, Karamanis D, Ognibene J, Arora S, et al. Severe obesity, increasing age and male sex are independently associated with worse in-hospital outcomes, and higher in-hospital mortality, in a cohort of patients with COVID-19 in the Bronx, New York. Metabolism 2020;108:154262. 链接1
[47] Xie J, Covassin N, Fan Z, Singh P, Gao W, Li G, et al. Association between hypoxemia and mortality in patients with COVID-19. Mayo Clin Proc 2020;95 (6):1138–47. 链接1
[48] Cecconi M, Piovani D, Brunetta E, Aghemo A, Greco M, Ciccarelli M, et al. Early predictors of clinical deterioration in a cohort of 239 patients hospitalized for COVID-19 infection in Lombardy, Italy. J Clin Med 2020;9(5):1548. 链接1
[49] Yuan M, Yin W, Tao Z, Tan W, Hu Y. Association of radiologic findings with mortality of patients infected with 2019 novel coronavirus in Wuhan, China. PLoS ONE 2020;15(3):e0230548. 链接1
[50] Gallo Marin B, Aghagoli G, Lavine K, Yang L, Siff EJ, Chiang SS et al.; Predictors of COVID-19 severity: a literature review. Rev Med Virol 2021;31(1):1–10. 链接1
[51] Takahashi T, Ellingson MK, Wong P, Israelow B, Lucas C, Klein J et al.; Yale IMPACT Research Team. Sex differences in immune responses that underlie COVID-19 disease outcomes. Nature 2020;588(7837):315–20. 链接1
[52] Uygun Ö, Ertas M, Ekizog˘lu E, Bolay H, Özge A, Kocasoy Orhan E, et al. Headache characteristics in COVID-19 pandemic—a survey study. J Headache Pain 2020;21(1):121. 链接1
[53] Yu F, Geldsetzer P, Meierkord A, Yang J, Chen Q, Jiao L, et al. Knowledge about coronavirus disease 2019 among adults in China: a cross-sectional online survey. J Med Internet Res 2021;23(4):e26940. 链接1
[54] Li J, Chen Z, Nie Y, Ma Y, Guo Q, Dai X. Identification of symptoms prognostic of COVID-19 severity: multivariate data analysis of a case series in Henan Province. J Med Internet Res 2020;22(6):e19636. 链接1
[55] Pan XF, Yang J, Wen Y, Li N, Chen S, Pan A. Non-communicable diseases during the COVID-19 pandemic and beyond. Engineering 2021;7(7):899–902.
[56] Reddy RK, Charles WN, Sklavounos A, Dutt A, Seed PT, Khajuria A. The effect of smoking on COVID-19 severity: a systematic review and meta-analysis. J Med Virol 2021;93(2):1045–56. 链接1
[57] Chen S, Kuhn M, Prettner K. Tobacco control policies: the authors reply. Health Aff 2020;39(2):346. 链接1
[58] Chen S, Kuhn M, Prettner K, Bloom DE. Noncommunicable diseases attributable to tobacco use in China: macroeconomic burden and tobacco control policies. Health Aff 2019;38(11):1832–9. 链接1
京公网安备 11010502051620号
