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The mNCP-SPI Score Predicting Risk of Severe COVID-19 among Mild-Pneumonia Patients on Admission

To predict the risk of developing severe pneumonia among mild novel coronavirus pneumonia (mNCP) patients on admission. A retrospective cohort study was conducted at three hospitals in Shanghai and Wuhan from January 2020 to February 2020. Real-time polymerasechain-reaction assays were used to detec...

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Published in:Infection and drug resistance 2020-01, Vol.13, p.3593-3600
Main Authors: Guo, Lingxi, Xiong, Weining, Liu, Dong, Feng, Yun, Wang, Peng, Dong, Xuan, Chen, Rong, Wang, Yi, Zhang, Lei, Huang, Jingwen, Summah, Hanssa Dwarka, Lu, Fangying, Xie, Yusang, Lin, Huihuang, Yan, Jiayang, Lu, Hongzhou, Zhou, Min, Qu, Jieming
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container_title Infection and drug resistance
container_volume 13
creator Guo, Lingxi
Xiong, Weining
Liu, Dong
Feng, Yun
Wang, Peng
Dong, Xuan
Chen, Rong
Wang, Yi
Zhang, Lei
Huang, Jingwen
Summah, Hanssa Dwarka
Lu, Fangying
Xie, Yusang
Lin, Huihuang
Yan, Jiayang
Lu, Hongzhou
Zhou, Min
Qu, Jieming
description To predict the risk of developing severe pneumonia among mild novel coronavirus pneumonia (mNCP) patients on admission. A retrospective cohort study was conducted at three hospitals in Shanghai and Wuhan from January 2020 to February 2020. Real-time polymerasechain-reaction assays were used to detect COVID-19. A total of 529 patients diagnosed with NCP were recruited from three hospitals and classified by four severity types during hospitalization following the standards of the Chinese Diagnosis and Treatment of Pneumonia Caused by New Coronavirus Infection (eighth version). Patients were excluded if admitted by ICU on admission (n=92, on a general ward while meeting the condition of severe or critical type on admission (n=25), or there was insufficient clinical information (n=64). In sum, 348 patients with mNCP were finally included, and 68 developed severe pneumonia. mNCP severity prognostic index values were calculated based on multivariate logistic regression: history of diabetes (OR 2.064, 95% CI 1.010-4.683; =0.043), time from symptom onset to admission ≥7 days (OR 1.945, 95% CI 1.054-3.587; =0.033), lymphocyte count ≤0.8 (OR 1.816, 95% CI 1.008-3.274; =0.047), myoglobin ≥90 mg/L (OR 2.496, 95% CI 1.235-5.047; =0.011), and D-dimer ≥0.5 mg/L (OR 2.740, 95% CI 1.395-5.380; =0.003). This model showed a -statistics of 0.747, with sensitivity and specificity 0.764 and 0.644, respectively, under cutoff of 165. We designed a clinical predictive tool for risk of severe pneumonia among mNCP patients to provided guidance for medicines. Further studies are required for external validation.
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A retrospective cohort study was conducted at three hospitals in Shanghai and Wuhan from January 2020 to February 2020. Real-time polymerasechain-reaction assays were used to detect COVID-19. A total of 529 patients diagnosed with NCP were recruited from three hospitals and classified by four severity types during hospitalization following the standards of the Chinese Diagnosis and Treatment of Pneumonia Caused by New Coronavirus Infection (eighth version). Patients were excluded if admitted by ICU on admission (n=92, on a general ward while meeting the condition of severe or critical type on admission (n=25), or there was insufficient clinical information (n=64). In sum, 348 patients with mNCP were finally included, and 68 developed severe pneumonia. mNCP severity prognostic index values were calculated based on multivariate logistic regression: history of diabetes (OR 2.064, 95% CI 1.010-4.683; =0.043), time from symptom onset to admission ≥7 days (OR 1.945, 95% CI 1.054-3.587; =0.033), lymphocyte count ≤0.8 (OR 1.816, 95% CI 1.008-3.274; =0.047), myoglobin ≥90 mg/L (OR 2.496, 95% CI 1.235-5.047; =0.011), and D-dimer ≥0.5 mg/L (OR 2.740, 95% CI 1.395-5.380; =0.003). This model showed a -statistics of 0.747, with sensitivity and specificity 0.764 and 0.644, respectively, under cutoff of 165. We designed a clinical predictive tool for risk of severe pneumonia among mNCP patients to provided guidance for medicines. Further studies are required for external validation.</description><identifier>ISSN: 1178-6973</identifier><identifier>EISSN: 1178-6973</identifier><identifier>DOI: 10.2147/IDR.S263157</identifier><identifier>PMID: 33116679</identifier><language>eng</language><publisher>New Zealand: Dove Medical Press Limited</publisher><subject>Antibiotics ; Cardiovascular disease ; Cell number ; China ; Coronaviruses ; COVID-19 ; Development and progression ; Diabetes ; Diabetes mellitus ; Ethics ; Health aspects ; Hospital patients ; Hospitalization ; Hospitals ; Infections ; Laboratories ; Lymphocytes ; Medical care quality ; Medical schools ; Multivariate analysis ; Myoglobin ; Myoglobins ; novel coronavirus pneumonia ; Original Research ; Patients ; Pneumonia ; predicting score ; Public health ; severe pneumonia ; Variables</subject><ispartof>Infection and drug resistance, 2020-01, Vol.13, p.3593-3600</ispartof><rights>2020 Guo et al.</rights><rights>COPYRIGHT 2020 Dove Medical Press Limited</rights><rights>2020. 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mNCP-SPI Score Predicting Risk of Severe COVID-19 among Mild-Pneumonia Patients on Admission</atitle><jtitle>Infection and drug resistance</jtitle><addtitle>Infect Drug Resist</addtitle><date>2020-01-01</date><risdate>2020</risdate><volume>13</volume><spage>3593</spage><epage>3600</epage><pages>3593-3600</pages><issn>1178-6973</issn><eissn>1178-6973</eissn><abstract>To predict the risk of developing severe pneumonia among mild novel coronavirus pneumonia (mNCP) patients on admission. A retrospective cohort study was conducted at three hospitals in Shanghai and Wuhan from January 2020 to February 2020. Real-time polymerasechain-reaction assays were used to detect COVID-19. A total of 529 patients diagnosed with NCP were recruited from three hospitals and classified by four severity types during hospitalization following the standards of the Chinese Diagnosis and Treatment of Pneumonia Caused by New Coronavirus Infection (eighth version). Patients were excluded if admitted by ICU on admission (n=92, on a general ward while meeting the condition of severe or critical type on admission (n=25), or there was insufficient clinical information (n=64). In sum, 348 patients with mNCP were finally included, and 68 developed severe pneumonia. mNCP severity prognostic index values were calculated based on multivariate logistic regression: history of diabetes (OR 2.064, 95% CI 1.010-4.683; =0.043), time from symptom onset to admission ≥7 days (OR 1.945, 95% CI 1.054-3.587; =0.033), lymphocyte count ≤0.8 (OR 1.816, 95% CI 1.008-3.274; =0.047), myoglobin ≥90 mg/L (OR 2.496, 95% CI 1.235-5.047; =0.011), and D-dimer ≥0.5 mg/L (OR 2.740, 95% CI 1.395-5.380; =0.003). This model showed a -statistics of 0.747, with sensitivity and specificity 0.764 and 0.644, respectively, under cutoff of 165. We designed a clinical predictive tool for risk of severe pneumonia among mNCP patients to provided guidance for medicines. 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1178-6973
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source Open Access: PubMed Central; Publicly Available Content Database; Taylor & Francis Open Access Journals; Coronavirus Research Database
subjects Antibiotics
Cardiovascular disease
Cell number
China
Coronaviruses
COVID-19
Development and progression
Diabetes
Diabetes mellitus
Ethics
Health aspects
Hospital patients
Hospitalization
Hospitals
Infections
Laboratories
Lymphocytes
Medical care quality
Medical schools
Multivariate analysis
Myoglobin
Myoglobins
novel coronavirus pneumonia
Original Research
Patients
Pneumonia
predicting score
Public health
severe pneumonia
Variables
title The mNCP-SPI Score Predicting Risk of Severe COVID-19 among Mild-Pneumonia Patients on Admission
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T00%3A11%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20mNCP-SPI%20Score%20Predicting%20Risk%20of%20Severe%20COVID-19%20among%20Mild-Pneumonia%20Patients%20on%20Admission&rft.jtitle=Infection%20and%20drug%20resistance&rft.au=Guo,%20Lingxi&rft.date=2020-01-01&rft.volume=13&rft.spage=3593&rft.epage=3600&rft.pages=3593-3600&rft.issn=1178-6973&rft.eissn=1178-6973&rft_id=info:doi/10.2147/IDR.S263157&rft_dat=%3Cgale_doaj_%3EA642011037%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c573t-e0bc14eaba4cf473c4e6e6beb98d323b584892848ed9954f460b46d494c78b643%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2456304881&rft_id=info:pmid/33116679&rft_galeid=A642011037&rfr_iscdi=true