A nomogram to early predict isolation length for non-severe COVID-19 patients based on laboratory investigation: A multicenter retrospective study in Zhejiang Province, China

Autor: Jun Zhang, Jiangnan Chen, Yan Xia, Wei Zheng, Xinyou Xie, Shijin Yuan, Xiaoping Xu, Yan Zhang
Rok vydání: 2021
Předmět:
Male
0301 basic medicine
Time Factors
Clinical Biochemistry
AST
aspartate aminotransferase
SII
systemic immune-inflammation index
Biochemistry
Nomogram
AUC
area under the curve
Leukocyte Count
MERS-CoV
middle east respiratory syndrome coronavirus
COVID-19 Testing
0302 clinical medicine
WBC
white blood cell count
RBC
red blood cell count
AMC
absolute monocyte count
COVID-19
coronavirus disease 2019
Isolation length
LDH
lactate dehydrogenase
medicine.diagnostic_test
Area under the curve
General Medicine
Middle Aged
PNI
prognostic nutrition index
CT
computed tomography
Hospitalization
Activated partial thromboplastin time
Area Under Curve
030220 oncology & carcinogenesis
Quarantine
CRP
C-reactive protein
Female
Partial Thromboplastin Time
Partial thromboplastin time
Adult
China
medicine.medical_specialty
Isolation (health care)
Coronavirus disease 2019 (COVID-19)
RT-PCR
reverse transcription-polymerase chain reaction
SARS-CoV
severe acute respiratory syndrome coronavirus
Physical Distancing
C-index
Concordance index
SARS-CoV-2
severe acute respiratory syndrome coronavirus 2
Antiviral Agents
Article
WHO
World Health Organization
03 medical and health sciences
Absolute eosinophil count
ALT
alanine aminotransferase
PT
prothrombin time
Internal medicine
medicine
AEC
absolute eosinophil count
Humans
CDC
Centers for Disease Control
APTT
activated partial thromboplastin time
Proportional Hazards Models
Retrospective Studies
Biochemistry
medical
business.industry
Proportional hazards model
Biochemistry (medical)
COVID-19
ALC
absolute lymphocyte count
Reproducibility of Results
Retrospective cohort study
Ct
Cycle threshold
Training cohort
Eosinophils
Nomograms
030104 developmental biology
ANC
absolute neutrophil count
business
Zdroj: Clinica Chimica Acta
Clinica Chimica Acta; International Journal of Clinical Chemistry
ISSN: 0009-8981
DOI: 10.1016/j.cca.2020.11.019
Popis: Highlights • Non-severe COVID-19 patients have abnormal laboratory investigations. • Patients with prolonged pretreatment APTT have a longer isolation length. • Patients with elevated eosinophils after treatment have a shorter isolation length. • A nomogram could help to predict isolation probability at 11-, 16- and 21-day.
Background Majority coronavirus disease 2019 (COVID-19) patients are classified as mild and moderate (non-severe) diseases. We aim to develop a model to predict isolation length for non-severe patients. Methods Among 188 non-severe patients, 96 patients were enrolled as training cohort to identify factors associated with isolation length via Cox regression model and develop a nomogram. Other 92 patients formed as validation cohort to validate nomogram. Concordance index (C-index), area under the curve (AUC) and calibration curves were used to evaluated nomogram. Results Increasing absolute eosinophil count (AEC) after admission was correlated with shorter isolation length (P = 0.02). Baseline activated partial thromboplastin time (APTT) > 30 s was correlated with longer isolation length (P = 0.03). A nomogram to predict isolation probability at 11-, 16- and 21-day was developed and validated. The C-indices of training and validation cohort were 0.604 and 0.682 respectively. Both cohorts showed a good discriminative ability (AUC, 11-day: 0.646 vs 0.730; 16-day: 0.663 vs 0.750; 21-day: 0.711 vs 0.783; respectively) and calibration power. Conclusions Baseline APTT and dynamic change of AEC were two significant factors associated with isolation length of non-severe patients. Nomogram could predict isolation probability for each patient to estimate appropriate quarantine length.
Databáze: OpenAIRE
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