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Simple Coagulation Profile as Predictor of Mortality in Adults Admitted with COVID-19: A Meta-Analysis. ARCHIVES OF CLINICAL INFECTIOUS DISEASES 2021. [DOI: 10.5812/archcid.115442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Context: COVID-19 severe manifestations must be detected as soon as possible. One of the essential poor characteristics is the involvement of coagulopathy. Simple coagulation parameters, including prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (aPTT), and platelet, are widely accessible in many health centers. Objectives: This meta-analysis aimed to determine the association between simple coagulation profiles and COVID-19 in-hospital mortality. Method: We systematically searched five databases for studies measuring simple coagulation parameters in COVID-19 on admission. The random-effects and inverse-variance weighting were used in the study, which used a standardized-mean difference of coagulation profile values. The odds ratios were computed using the Mantel-Haenszel formula for dichotomous variables. Results: This meta-analysis comprised a total of 30 studies (9,175 patients). In our meta-analysis, we found that non-survivors had a lower platelet count [SMD = -0.56 (95% CI: -0.79 to -0.33), P < 0.01; OR = 3.00 (95% CI: 1.66 to 5.41), P < 0.01], prolonged PT [SMD = 1.22 (95%CI: 0.71 to 1.72), P < 0.01; OR = 1.86 (95%CI: 1.43 to 2.43), P < 0.01], prolonged aPTT [SMD = 0.24 (95%CI: -0.04 to 0.52), P = 0.99], and increased INR [SMD = 2.21 (95%CI: 0.10 to 4.31), P = 0.04] than survivors. Conclusions: In COVID-19 patients, abnormal simple coagulation parameters on admission, such as platelet, PT, and INR, were associated with mortality outcomes.
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Tjendra Y, Al Mana AF, Espejo AP, Akgun Y, Millan NC, Gomez-Fernandez C, Cray C. Predicting Disease Severity and Outcome in COVID-19 Patients: A Review of Multiple Biomarkers. Arch Pathol Lab Med 2020; 144:1465-1474. [PMID: 32818235 DOI: 10.5858/arpa.2020-0471-sa] [Citation(s) in RCA: 108] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/13/2020] [Indexed: 01/17/2023]
Abstract
CONTEXT.— An abundance of clinical reports focused on specific laboratory parameters have been reported on coronavirus disease 19 (COVID-19), but a systematic analysis synthesizing these findings has not been performed. OBJECTIVE.— To review and summarize the current available literature on the predictive role of various biomarkers in COVID-19 patients. DATA SOURCES.— A literature search was performed using databases including PubMed, medRxiv, and bioRxiv. A total of 72 papers were reviewed, including 54 peer-reviewed papers and 18 non-peer-reviewed preprints. CONCLUSIONS.— Although the markers are considered nonspecific, acute-phase reactants, including C-reactive protein (CRP), ferritin, serum amyloid A (SAA), and procalcitonin, were reported as sensitive markers of acute COVID-19 disease. Significantly elevated white blood cell count; marked lymphopenia; decreased CD3, CD4, or CD8 T-lymphocyte counts; high neutrophil count; thrombocytopenia; and markedly elevated inflammatory biomarkers were associated with severe disease and the risk of developing sepsis with rapid progression. Trends observed by serial laboratory measurements during hospitalization, including progressive decrease of lymphocyte count, thrombocytopenia, elevated CRP, procalcitonin, increased liver enzymes, decreased renal function, and coagulation derangements, were more common in critically ill patient groups and associated with a high incidence of clinical complications. Elevated interleukin 6 level and markedly increased SAA were most often reported in severely and critically ill patients. Indicators of systemic inflammation, such as neutrophil to lymphocyte ratio, systemic immune-inflammation index, or COVID-19 Severity Score, may be used to predict disease severity, outcome, and mortality. Interpretation of the data reported in the studies reviewed here is limited because of the study design (mostly retrospective), limited sample size, and a lack of defined clinical criteria.
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Affiliation(s)
- Youley Tjendra
- Department of Pathology & Laboratory Medicine (Tjendra, Al Mana, Akgun, Millan, Gomez-Fernandez), University of Miami Miller School of Medicine and Jackson Health System, Miami, Florida
| | - Abdulaziz F Al Mana
- Department of Pathology & Laboratory Medicine (Tjendra, Al Mana, Akgun, Millan, Gomez-Fernandez), University of Miami Miller School of Medicine and Jackson Health System, Miami, Florida
| | - Andrea P Espejo
- Department of Hematology and Medical Oncology (Espejo), University of Miami Miller School of Medicine and Jackson Health System, Miami, Florida
| | - Yamac Akgun
- Department of Pathology & Laboratory Medicine (Tjendra, Al Mana, Akgun, Millan, Gomez-Fernandez), University of Miami Miller School of Medicine and Jackson Health System, Miami, Florida
| | - Nicolas C Millan
- Department of Pathology & Laboratory Medicine (Tjendra, Al Mana, Akgun, Millan, Gomez-Fernandez), University of Miami Miller School of Medicine and Jackson Health System, Miami, Florida
| | - Carmen Gomez-Fernandez
- Department of Pathology & Laboratory Medicine (Tjendra, Al Mana, Akgun, Millan, Gomez-Fernandez), University of Miami Miller School of Medicine and Jackson Health System, Miami, Florida
| | - Carolyn Cray
- The Department of Pathology & Laboratory Medicine, University of Miami Miller School of Medicine, Miami, Florida (Cray)
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Luo HC, You CY, Lu SW, Fu YQ. Characteristics of coagulation alteration in patients with COVID-19. Ann Hematol 2020; 100:45-52. [PMID: 33079220 PMCID: PMC7572245 DOI: 10.1007/s00277-020-04305-x] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 10/15/2020] [Indexed: 02/07/2023]
Abstract
Abnormal blood coagulation often occurs in critically ill patients, which seriously affects their prognosis. This retrospective study investigated the implications of changes in blood coagulation in patients with coronavirus disease 2019 (COVID-19). Records were reviewed for patients admitted with COVID-19 between February 4 and 16, 2020. The primary outcome was in-hospital death. A total of 85 patients were included, of whom 12 died in the hospital. The admission prothrombin time (PT), international normalized ratio (INR), and levels of D-dimer and fibrin/fibrinogen degradation products (FDP) were significantly higher in non-survivors than in survivors, while the reverse was true for prothrombin time activity (PT-act) and PaO2/FiO2. Multivariate logistic regression showed that PT-act < 75% was independently associated with mortality. The area under the receiver operating characteristic curves for PT-act, D-dimer, and FDP at admission could significantly predict mortality. The AUCs for PT-act were larger than those for D-dimer and FDP; however, there was no significant difference. After 2 weeks of treatment, the coagulation parameters of the surviving patients improved. COVID-19 is often accompanied by abnormal coagulation. PT-act at admission is able to predict mortality in patients with COVID-19 as can D-dimer and FDP levels. PT-act < 75% is independently associated with mortality.
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Affiliation(s)
- Hong-Chun Luo
- Department of Infectious Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Cheng-Yan You
- Department of Critical Care Medicine, Children's Hospital, Chongqing Medical University, 136# Zhongshan Er Road, Yu Zhong District, Chongqing, 400014, People's Republic of China.,Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, People's Republic of China.,National Clinical Research Center for Child Health and Disorders (Chongqing), Chongqing, 400014, People's Republic of China
| | - Si-Wei Lu
- Department of Critical Care Medicine, Children's Hospital, Chongqing Medical University, 136# Zhongshan Er Road, Yu Zhong District, Chongqing, 400014, People's Republic of China.,Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, People's Republic of China.,National Clinical Research Center for Child Health and Disorders (Chongqing), Chongqing, 400014, People's Republic of China
| | - Yue-Qiang Fu
- Department of Critical Care Medicine, Children's Hospital, Chongqing Medical University, 136# Zhongshan Er Road, Yu Zhong District, Chongqing, 400014, People's Republic of China. .,Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, People's Republic of China. .,National Clinical Research Center for Child Health and Disorders (Chongqing), Chongqing, 400014, People's Republic of China. .,Third Batch Chongqing Medical Aid Team to Wuhan City of Hubei Province, Chongqing, People's Republic of China.
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Pan D, Cheng D, Cao Y, Hu C, Zou F, Yu W, Xu T. A Predicting Nomogram for Mortality in Patients With COVID-19. Front Public Health 2020; 8:461. [PMID: 32850612 PMCID: PMC7432145 DOI: 10.3389/fpubh.2020.00461] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 07/22/2020] [Indexed: 12/21/2022] Open
Abstract
Background: The global COVID-19 epidemic remains severe, with the cumulative global death toll reaching more than 207,170 as of May 2, 2020 (1). Purpose: Our research objective is to establish a reliable nomogram to predict mortality in COVID-19 patients. The nomogram can help us distinguish between patients who are at high risk of death and need close attention. Patients and Methods: For the single-center retrospective study, we collected 21 cases of patients who died in the critical illness area of the Optical Valley Branch of Tongji Hospital, Huazhong University of Science and Technology, from February 9 to March 10. Additionally, we selected 99 patients discharged during this period for analysis. The nomogram was constructed to predict the mortality for COVID-19 patients using the primary group of 120 patients and was validated using an independent cohort of 84 patients. We used multivariable logistic regression analysis to construct the prediction model. The nomogram was evaluated for calibration, differentiation, and clinical usefulness. Results: The predictors included in the nomogram were c-reactive protein, PaO2/FiO2, and cTnI. The areas under the curves of the nomogram were 0.988 (95% CI: 0.972-1.000) and 0.956 (95% CI, 0.874-1.000) in the primary and validation groups, respectively. Decision curve analysis suggests that the nomogram may have clinical usefulness. Conclusion: This study provides a nomogram containing c-reactive protein, PaO2/FiO2, and cTnI that can be conveniently used to predict individual mortality in COVID-19 patients. Next, we will collect as many cases as possible from multiple centers to build a more reliable nomogram to predict mortality for COVID-19 patients.
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Affiliation(s)
- Deng Pan
- Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Dandan Cheng
- Department of Hematology, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Yiwei Cao
- Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Chuan Hu
- Department of Joint Surgery, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Fenglin Zou
- Department of Biliary-Pancreatic Surgery, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Wencheng Yu
- Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tao Xu
- Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
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Deeks JJ, Dinnes J, Takwoingi Y, Davenport C, Spijker R, Taylor-Phillips S, Adriano A, Beese S, Dretzke J, Ferrante di Ruffano L, Harris IM, Price MJ, Dittrich S, Emperador D, Hooft L, Leeflang MM, Van den Bruel A. Antibody tests for identification of current and past infection with SARS-CoV-2. Cochrane Database Syst Rev 2020; 6:CD013652. [PMID: 32584464 PMCID: PMC7387103 DOI: 10.1002/14651858.cd013652] [Citation(s) in RCA: 436] [Impact Index Per Article: 109.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify current infection, rule out infection, identify people in need of care escalation, or to test for past infection and immune response. Serology tests to detect the presence of antibodies to SARS-CoV-2 aim to identify previous SARS-CoV-2 infection, and may help to confirm the presence of current infection. OBJECTIVES To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS-CoV-2 infection, and the accuracy of antibody tests for use in seroprevalence surveys. SEARCH METHODS We undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 27 April 2020. SELECTION CRITERIA We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in people suspected of current or previous SARS-CoV-2 infection, or where tests were used to screen for infection. We also included studies of people either known to have, or not to have SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR) and clinical diagnostic criteria). DATA COLLECTION AND ANALYSIS We assessed possible bias and applicability of the studies using the QUADAS-2 tool. We extracted 2x2 contingency table data and present sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data using random-effects logistic regression where appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs). MAIN RESULTS We included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n = 38), Europe (n = 15), and the USA and China (n = 1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n = 28) of the studies included were only available as preprints. We had concerns about risk of bias and applicability. Common issues were use of multi-group designs (n = 29), inclusion of only COVID-19 cases (n = 19), lack of blinding of the index test (n = 49) and reference standard (n = 29), differential verification (n = 22), and the lack of clarity about participant numbers, characteristics and study exclusions (n = 47). Most studies (n = 44) only included people hospitalised due to suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n = 33) defined COVID-19 cases based on RT-PCR results alone, ignoring the potential for false-negative RT-PCR results. We observed evidence of selective publication of study findings through omission of the identity of tests (n = 5). We observed substantial heterogeneity in sensitivities of IgA, IgM and IgG antibodies, or combinations thereof, for results aggregated across different time periods post-symptom onset (range 0% to 100% for all target antibodies). We thus based the main results of the review on the 38 studies that stratified results by time since symptom onset. The numbers of individuals contributing data within each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond three weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). There are insufficient studies to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range expected by chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity between assay type, but methodological concerns and sparse data prevent comparisons between test brands. AUTHORS' CONCLUSIONS The sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative, or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after the onset of symptoms. However, the duration of antibody rises is currently unknown, and we found very little data beyond 35 days post-symptom onset. We are therefore uncertain about the utility of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalised patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution and reporting of studies of the accuracy of COVID-19 tests requires considerable improvement. Studies must report data on sensitivity disaggregated by time since onset of symptoms. COVID-19-positive cases who are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are available in the public domain to prevent selective reporting. This is a fast-moving field and we plan ongoing updates of this living systematic review.
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Affiliation(s)
- Jonathan J Deeks
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Jacqueline Dinnes
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Yemisi Takwoingi
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Clare Davenport
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - René Spijker
- Medical Library, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Amsterdam, Netherlands
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Sian Taylor-Phillips
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
| | - Ada Adriano
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Sophie Beese
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Janine Dretzke
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Lavinia Ferrante di Ruffano
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Isobel M Harris
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Malcolm J Price
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | | | | | - Lotty Hooft
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Mariska Mg Leeflang
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
- Biomarker and Test Evaluation Programme (BiTE), Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Ann Van den Bruel
- Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
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