key: cord-0939194-j8j0dya2
authors: Wang, Zhi; Zhong, Bin-Yan; Dai, Hui; Xu, Qiu-Zhen; Yang, Wei-Bin; Zhang, Xin; Xu, Chuan-Jun; Shu, Jin-Er; Shi, Biao; Zeng, Chu-Hui; Li, Cheng; Ji, Jian-Song; Li, Yong-Gang; Teng, Gao-Jun
title: Prognostic Nomogram on Admission Predicting Progression for Patients with Nonsevere COVID-19
date: 2021-01-26
journal: nan
DOI: 10.1016/j.fmre.2021.01.012
sha: 7ec4f00e4a0e3631097b4ae6815ab79518c56254
doc_id: 939194
cord_uid: j8j0dya2

The present study aimed to establish a prognostic nomogram to stratify high-risk patients with Coronavirus Disease 2019 (COVID-19) who progressed from the nonsevere condition on admission to severe during hospitalization. This multicenter retrospective study included patients with nonsevere COVID-19 on admission from Jan 10, 2020 to Feb 7, 2020. In the training cohort, independent risk factors associated with disease progression were identified by univariate and multivariate analyses. The prognostic nomogram was established and then validated externally using C-index. The study included 351 patients (293 and 58 in the training and validation cohorts, respectively), with 27 (9.2%) and 5 (8.6%) patients progressed, respectively. In the training cohort, older age (OR 1.036, 95% CI 1.000-1.073), more lobes involved on chest CT (OR 1.841, 95% CI 1.117-3.035), comorbidity present (OR 2.478, 95% CI 1.020-6.018), and lower lymphocyte count (OR 0.081, 95% CI 0.019-0.349) were identified as independent risk factors. The prognostic nomogram was established in the training cohort with satisfied external prognostic performance (C-index 0.906, 95% CI 0.806-1.000). In conclusion, older age, comorbidity present, more lobes involved on chest CT, and lower lymphocyte count are independent risk factors associated with disease progression during hospitalization for patients with nonsevere COVID-19.

In December 2019, a cluster of cases with viral pneumonia of unknown origin were confirmed to contract a novel coronavirus, previously known as 2019 novel coronavirus (2019-nCoV). The pathogen has subsequently been renamed severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) and is a member of the subgenus Sarbecovirus (Beta-CoV lineage B) closely related to severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) [1, 2] . Clinical features of the first confirmed cases were characterized in Feb 2020 [3] . As of Dec 1, 2020, a total of 65,872,391 Previous reports indicated that 26%-33% of patients in Wuhan required intensive care and 4%-15% died [2, 3, 5] . Afterwards, the largest case series of 72,314 cases published by the Chinese Center for Disease Control and Prevention (China CDC) has further elaborated severe and critical disease in 18.5% of cases and an overall case-fatality rate (CFR) of 2.3% [6] . Notably, the case fatality in severe (8.1% vs 0.1%) or critical cases (49.0% vs 0.0%) is far beyond that in nonsevere cases [6, 7] . Therefore, it is important to distinguish several possible hallmarks of progression at the early stage to guide clinical decision-making as well as infection management. An early study elaborated that ICU patients had higher plasma levels of cytokines compared with non-ICU patients [3] . Moreover, it was reported that COVID-19 more likely affected older males with comorbidities [8] and patients who required ICU care were significantly older and more likely to have underlying comorbidities, such as hypertension, diabetes, cardiovascular disease and cerebrovascular disease [5] .

Herein, we aimed to further elucidate the potential risk factors for disease progression and to establish a prognostic nomogram among hospitalized patients with COVID-19. To our knowledge, this prediction model is the first nomogram, which combined demographic, clinical, laboratory and radiologic characteristics solely on admission and was validated externally, for calculating risk of progression in patients with COVID-19.

This multicenter retrospective study was approved by the institutional review boards of the relevant centers. The need for written informed consent was waived due to the retrospective nature of the study. The study was performed in accordance with the Declaration of Helsinki. Patients admitted to hospital with laboratory-confirmed COVID-19 in 16 designated tertiary hospitals outside Hubei Province (13, 2, and 1 hospitals in Jiangsu, Zhejiang, and Anhui Provinces, respectively) from Jan 10, 2020 to Feb 7, 2020 were screened and included in the study. The cutoff date of follow-up and data collection for the study was Mar 17, 2020. The diagnosis of COVID-19 was based on the WHO interim guidance with a positive result on high-throughput sequencing or real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of nasal and pharyngeal swab specimens [9] . The illness severity of COVID-19 was defined according to the Chinese management guideline for COVID-19 (version 6.0) [10] . Mild was characterized by mild symptoms without imaging findings.

Moderate was characterized by fever and/or respiratory symptom as well as imaging findings. Severe was characterized by dyspnea, respiratory frequency ≥ 30/minute, blood oxygen saturation ≤93%, PaO2/FiO2 ratio <300, and/or lung infiltrates >50% within 24-48 hours. Critical cases were those that exhibited respiratory failure, septic shock, and/or multiple organ dysfunction/failure. Based on this, we classify mild/moderate disease as "nonsevere" and severe/critical diseases as "severe" in this study. Progression was defined as one patient was categorized as "severe" at any time during hospitalization. Patients admitted to designated hospitals in Jiangsu Province were included in the training cohort to establish the prognostic nomogram and those from Zhejiang and Anhui Provinces were included in the validation cohort to validate the nomogram externally.

The inclusion criteria of the study were as follows: 1) laboratory-confirmed diagnosis of COVID-19 during the first hospital admission as mentioned above; 2) classified as nonsevere condition on admission; and 3) chest computed tomography (CT) and laboratory tests performed within 24 hours after admission. The major exclusion criterion was patients in the severe condition on admission.

Laboratory confirmation with RT-PCR, laboratory tests (mainly including a complete blood count, serum biochemistry, and coagulation test), and chest CT were conducted on admission and repeated according to the clinical care needs of the patient. Most patients received antiviral treatment mainly with interferon alpha inhalation, lopinavir, and ritonavir. Baseline characteristics, recent exposure history, clinical signs and symptoms, and laboratory results on admission were extracted from electronic medical records of the participating hospitals. CT images on admission were re-reviewed by HD and YGL, with more than 15 years' experience in diagnostic radiology. Major disagreement between these two radiologists was resolved by the third radiologist, QZX., with more than 25 years' experience in diagnostic radiology.

Image interpretation including ground-glass opacity, consolidation, bilateral lung involved and number of involved lobes was recorded. Any ground-glass opacity or consolidation was considered as abnormalities on chest CT. All medical records were copied and collected under the coordination of the corresponding authors of the study.

Re-collection was requested from the participating hospitals if core data was missing.

The endpoint of the study was the progression of COVID-19 severity from nonsevere at the time of admission to severe during hospitalization. Fever was defined as axillary temperature of at least 37.3°C. The definitions of lymphocytopenia and thrombocytopenia were made based on a previous study with the largest COVID-19 cohort reported [7] . Comorbidity is defined as hypertension, diabetes and cardiovascular disease.

The prognostic nomogram was established based on the identified independent risk factors associated with the primary endpoint in the training cohort. The performance on prognostic discrimination about the nomogram was validated externally using the concordance c statistic (C-index) in the validation cohort.

Patients were classified into two groups: with progression of COVID-19 severity from nonsevere to severe (study group) and without progression of COVID-19 severity from nonsevere to severe (control group). Variables with P ≤ 0.10 in the univariate logistic analysis were considered strong risk factors associated with prognosis and were then put into the multivariate logistic analysis with forward selection. Variables remaining in the multivariate logistic analysis results were considered independent risk factors associated with prognosis. Continuous variables were presented as mean (SD) or median (IQR), and categorical variables as frequency www.r-project.org).

Of 374 patients with laboratory-confirmed COVID-19 cases, a total of 351 patients were included in the study, with 293 and 58 in the training and validation cohort, respectively ( Figure 1 ). Among them, 27 (9.2%) patients progressed from nonsevere on admission to severe disease during hospitalization in the training cohort, Table 1) . Six variables, namely, older age, comorbidity present, more lobes involved on chest CT, lesions consolidation on chest CT, lower lymphocyte count, and elevated C-reactive protein (CRP), were identified as strong risk factors after univariate analysis ( Table 2) . After multivariate analysis, older age, comorbidity present, more lobes involved on chest CT, and lower lymphocyte count were identified as independent risk factors associated with severity progression ( Figure 2 ). 

For patients with COVID-19 in the nonsevere condition on admission, a simple prognostic nomogram, which included older age, comorbidity present, more lobes involved on chest CT, and lower lymphocyte count, was established for severity progression from nonsevere on admission to severe during hospitalization. In addition, the nomogram showed high accuracy after external validation. Through the nomogram, probability of disease progression from nonsevere on admission to severe during hospitalization could be predicted individually and accurately. Hence, early detection and intervention could be applied exactly to prevent disease progression.

In this study, 27 (9.2%) and 5 (8.6%) patients in the training and validation cohorts experienced disease progression from nonsevere on admission to severe during hospitalization. The rates were lower than two previous studies with large sample sizes from China, mainly due to the difference in inclusion criteria and sample sizes [6, 7] . The rates were much lower when compared to a cohort from Wuhan, with 41.8% developed acute respiratory distress syndrome during hospitalization [11] , attributed to the relative mild condition in other areas.

Many studies have so far observed reduced absolute values of lymphocytes in most patients [3, 5, 7, 8, 12] , suggesting that SARS-CoV-2 might mainly act on lymphocytes, especially on T lymphocytes. In addition, cytokine storm is thought to play an important role in disease severity [13] , followed by several immune responses causing lymphocytes to decrease. Considering that older patients are associated with declined immune competence, it is reasonable to be a potential risk factor associated with disease progression. In line with previous studies, we identified that lower lymphocyte count and older age were independent risk factors associated with disease progression [3, 5, 7, 8, 11, 12, 14] .

Previous studies showed that more patients with hypertension, diabetes, or cardiovascular disease were observed in severe patients compared to that for nonsevere ones [5, 7, 14] . Human pathogenic coronaviruses including SARS-CoV-2 bind to their target cells through angiotensin-converting enzyme 2 (ACE2) [15] . Therefore, patients with hypertension, diabetes, and cardiovascular disease, who often experience upregulation of ACE2 with certain medications, are at higher risk for SARS-CoV-2 infection and disease progression [16] .

With its non-invasive modality, high accuracy and speed, chest CT plays an important role in diagnosis and severity assessment for COVID-19 [17] [18] [19] . Previous studies demonstrated that chest CT has a high sensitivity for diagnosing COVID-19 when compared to RT-PCR [20] . Chest CT abnormalities occurred in most patients with COVID-19 even in asymptomatic patients [21] . It developed rapidly from focal unilateral to diffuse bilateral ground-glass opacities that progressed to or co-existed with consolidations within 1-3 weeks [21] . In addition, previous studies found that incidence of diffuse lesions and more lobes involved was higher and associated with disease severity [22] . A perspective from China indicated that in severe COVID-19, CT scan often presented with bilateral multiple lobular and subsegmental involvement [19] . In this study, we demonstrated that more lobes involvement on chest CT scan on admission was an independent risk factor associated with disease progression, indicating that advanced progression presented on chest CT might occur earlier than that for clinical symptom [21] [22] [23] . Several notable limitations of this study should be acknowledged. First, incomplete documentation of the laboratory testing made it difficult to fully analyze the potential risk factors such as D-dimer and lactic dehydrogenase, which have been mentioned previously. Such limitation therefore can affect the accuracy of the nomogram. Urgent timeline for data collection and extraction was to blame for this challenge. Second, the sample size was relatively small for a prognostic nomogram. A larger cohort study is warranted to validate the accuracy and application of the nomogram.

In conclusion, older age, comorbidity present, more lobes involved on chest CT, and lower lymphocyte count are the key risk factors for patients with nonsevere COVID-19 on admission to progress to the severe condition during hospitalization.

The nomogram based on these factors has a strong and accurate predictive ability for disease progression. It is able to accurately stratify high-risk patients and assist clinicians in making appropriate decisions for nonsevere COVID-19 patients. Jiansong Ji, M.D., Ph.D, is a certified radiologist and Interventional radiologist of Lishui Hospital of Zhejiang University. He is the vice president of the hospital, and the director of Key laboratory of imaging diagnosis and interventional minimally invasive research of Zhejiang Province. As the chief scientist of the National Key Research and Development Program, he entitled to the "Special Allowance of the State Council". Besides, Dr. Ji honored as "National talent project candidate", "The outstanding contributor of the country", "The national role model worker" etc. As a researcher and a physician for more than two decades, Dr. Ji worked tirelessly，persistently, and creatively to boost the development of a discipline. So far, Dr.Ji has published over 200 papers and achieved more than 7 Provincial Science and Technology Progress Award. Therefore, he has been considered as a leading character

A Novel Coronavirus Genome Identified in a Cluster of Pneumonia Cases -Wuhan

A Novel Coronavirus from Patients with Pneumonia in China

Clinical features of patients infected with 2019 novel coronavirus in Wuhan

Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China

The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) -China

Clinical Characteristics of Coronavirus Disease 2019 in China. The New England journal of medicine

Epidemiological and clinical characteristics of study

Clinical management of severe acute respiratory infection when novel coronavirus ( 2019-nCoV) infection is suspected: interim guidance

National Health Commission of the People's Republic of China. Chinese management guideline for COVID-19 (version 6.0)

fc2/files/b218cfeb1bc54639af227f922bf6b817.pdf

Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease

Pneumonia in Wuhan, China. JAMA internal medicine

Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series

Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology. Seminars in immunopathology

Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. The Lancet Respiratory medicine

Receptor Recognition by the Novel Coronavirus from Wuhan: an Analysis Based on Decade-Long Structural Studies of SARS Coronavirus

Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection? The Lancet Respiratory medicine

COVID-19) Outbreak: What the Department of Radiology Should Know

Time Course of Lung Changes On Chest CT During Recovery From 2019 Novel Coronavirus (COVID-19) Pneumonia. Radiology

COVID-19): A Perspective from China

Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases

Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. The Lancet Infectious diseases

Relation Between Chest CT Findings and Clinical Conditions of Coronavirus Disease (COVID-19) Pneumonia: A Multicenter Study

CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV)

This study was supported by the National Natural Science Foundation of China All other authors critically reviewed the manuscript and approved the final version.

The authors declare that they have no conflict of interest.