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
| العنوان: | 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 |
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| المؤلفون: | Jun Zhang, Jiangnan Chen, Yan Xia, Wei Zheng, Xinyou Xie, Shijin Yuan, Xiaoping Xu, Yan Zhang |
| المصدر: | Clinica Chimica Acta Clinica Chimica Acta; International Journal of Clinical Chemistry |
| بيانات النشر: | Elsevier BV, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | 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 |
| الوصف: | 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. |
| تدمد: | 0009-8981 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05f7b8c31016bf4dd023e0346dae27f0Test https://doi.org/10.1016/j.cca.2020.11.019Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....05f7b8c31016bf4dd023e0346dae27f0 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 00098981 |
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