TY - JOUR
T1 - Time-to-Death Longitudinal Characterization of Clinical Variables and Longitudinal Prediction of Mortality in COVID-19 Patients
T2 - A Two-Center Study
AU - Chen, Anne
AU - Zhao, Zirun
AU - Hou, Wei
AU - Singer, Adam J.
AU - Li, Haifang
AU - Duong, Tim Q.
N1 - Publisher Copyright:
© Copyright © 2021 Chen, Zhao, Hou, Singer, Li and Duong.
PY - 2021/4/29
Y1 - 2021/4/29
N2 - Objectives: To characterize the temporal characteristics of clinical variables with time lock to mortality and build a predictive model of mortality associated with COVID-19 using clinical variables. Design: Retrospective cohort study of the temporal characteristics of clinical variables with time lock to mortality. Setting: Stony Brook University Hospital (New York) and Tongji Hospital. Patients: Patients with confirmed positive for severe acute respiratory syndrome coronavirus-2 using polymerase chain reaction testing. Patients from the Stony Brook University Hospital data were used for training (80%, N = 1,002) and testing (20%, N = 250), and 375 patients from the Tongji Hospital (Wuhan, China) data were used for testing. Intervention: None. Measurements and Main Results: Longitudinal clinical variables were analyzed as a function of days from outcome with time-lock-to-day of death (non-survivors) or discharge (survivors). A predictive model using the significant earliest predictors was constructed. Performance was evaluated using receiver operating characteristics area under the curve (AUC). The predictive model found lactate dehydrogenase, lymphocytes, procalcitonin, D-dimer, C-reactive protein, respiratory rate, and white-blood cells to be early predictors of mortality. The AUC for the zero to 9 days prior to outcome were: 0.99, 0.96, 0.94, 0.90, 0.82, 0.75, 0.73, 0.77, 0.79, and 0.73, respectively (Stony Brook Hospital), and 1.0, 0.86, 0.88, 0.96, 0.91, 0.62, 0.67, 0.50, 0.63, and 0.57, respectively (Tongji Hospital). In comparison, prediction performance using hospital admission data was poor (AUC = 0.59). Temporal fluctuations of most clinical variables, indicative of physiological and biochemical instability, were markedly higher in non-survivors compared to survivors (p < 0.001). Conclusion: This study identified several clinical markers that demonstrated a temporal progression associated with mortality. These variables accurately predicted death within a few days prior to outcome, which provides objective indication that closer monitoring and interventions may be needed to prevent deterioration.
AB - Objectives: To characterize the temporal characteristics of clinical variables with time lock to mortality and build a predictive model of mortality associated with COVID-19 using clinical variables. Design: Retrospective cohort study of the temporal characteristics of clinical variables with time lock to mortality. Setting: Stony Brook University Hospital (New York) and Tongji Hospital. Patients: Patients with confirmed positive for severe acute respiratory syndrome coronavirus-2 using polymerase chain reaction testing. Patients from the Stony Brook University Hospital data were used for training (80%, N = 1,002) and testing (20%, N = 250), and 375 patients from the Tongji Hospital (Wuhan, China) data were used for testing. Intervention: None. Measurements and Main Results: Longitudinal clinical variables were analyzed as a function of days from outcome with time-lock-to-day of death (non-survivors) or discharge (survivors). A predictive model using the significant earliest predictors was constructed. Performance was evaluated using receiver operating characteristics area under the curve (AUC). The predictive model found lactate dehydrogenase, lymphocytes, procalcitonin, D-dimer, C-reactive protein, respiratory rate, and white-blood cells to be early predictors of mortality. The AUC for the zero to 9 days prior to outcome were: 0.99, 0.96, 0.94, 0.90, 0.82, 0.75, 0.73, 0.77, 0.79, and 0.73, respectively (Stony Brook Hospital), and 1.0, 0.86, 0.88, 0.96, 0.91, 0.62, 0.67, 0.50, 0.63, and 0.57, respectively (Tongji Hospital). In comparison, prediction performance using hospital admission data was poor (AUC = 0.59). Temporal fluctuations of most clinical variables, indicative of physiological and biochemical instability, were markedly higher in non-survivors compared to survivors (p < 0.001). Conclusion: This study identified several clinical markers that demonstrated a temporal progression associated with mortality. These variables accurately predicted death within a few days prior to outcome, which provides objective indication that closer monitoring and interventions may be needed to prevent deterioration.
KW - SARS-CoV-2
KW - clinical variables
KW - longitudinal
KW - prediction
KW - trend
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U2 - 10.3389/fmed.2021.661940
DO - 10.3389/fmed.2021.661940
M3 - Article
AN - SCOPUS:85105960583
SN - 2296-858X
VL - 8
JO - Frontiers in Medicine
JF - Frontiers in Medicine
M1 - 661940
ER -