Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score
Background. COVID-19 may result in multiorgan failure and death. Early detection of patients at risk may allow triage and more intense monitoring. The aim of this study was to develop a simple, objective admission score, based on laboratory tests, that identifies patients who are likely going to det...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Critical Care Research and Practice |
| Online Access: | http://dx.doi.org/10.1155/2021/5585291 |
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| author | Luke Tseng Erin Hittesdorf Mitchell F. Berman Desmond A. Jordan Nina Yoh Katerina Elisman Katherine A. Eiseman Yuqi Miao Shuang Wang Gebhard Wagener |
| author_facet | Luke Tseng Erin Hittesdorf Mitchell F. Berman Desmond A. Jordan Nina Yoh Katerina Elisman Katherine A. Eiseman Yuqi Miao Shuang Wang Gebhard Wagener |
| author_sort | Luke Tseng |
| collection | DOAJ |
| description | Background. COVID-19 may result in multiorgan failure and death. Early detection of patients at risk may allow triage and more intense monitoring. The aim of this study was to develop a simple, objective admission score, based on laboratory tests, that identifies patients who are likely going to deteriorate. Methods. This is a retrospective cohort study of all COVID-19 patients admitted to a tertiary academic medical center in New York City during the COVID-19 crisis in spring 2020. The primary combined endpoint included intubation, stage 3 acute kidney injury (AKI), or death. Laboratory tests available on admission in at least 70% of patients (and age) were included for univariate analysis. Tests that were statistically or clinically significant were then included in a multivariate binary logistic regression model using stepwise exclusion. 70% of all patients were used to train the model, and 30% were used as an internal validation cohort. The aim of this study was to develop and validate a model for COVID-19 severity based on biomarkers. Results. Out of 2545 patients, 833 (32.7%) experienced the primary endpoint. 53 laboratory tests were analyzed, and of these, 47 tests (and age) were significantly different between patients with and without the endpoint. The final multivariate model included age, albumin, creatinine, C-reactive protein, and lactate dehydrogenase. The area under the ROC curve was 0.850 (CI [95%]: 0.813, 0.889), with a sensitivity of 0.800 and specificity of 0.761. The probability of experiencing the primary endpoint can be calculated as p=e−2.4475+0.02492age−0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH/1+e−2.4475+ 0.02492age−0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH. Conclusions. Our study demonstrated that poor outcome in COVID-19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. This is useful for identifying patients at risk during admission. |
| format | Article |
| id | doaj-art-74172a9f55ec487e836f290b09f53dc2 |
| institution | Kabale University |
| issn | 2090-1305 2090-1313 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Critical Care Research and Practice |
| spelling | doaj-art-74172a9f55ec487e836f290b09f53dc22025-02-03T05:47:09ZengWileyCritical Care Research and Practice2090-13052090-13132021-01-01202110.1155/2021/55852915585291Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 ScoreLuke Tseng0Erin Hittesdorf1Mitchell F. Berman2Desmond A. Jordan3Nina Yoh4Katerina Elisman5Katherine A. Eiseman6Yuqi Miao7Shuang Wang8Gebhard Wagener9Columbia University Vagelos College of Physicians & Surgeons, New York, NY, USADepartment of Anesthesiology, Columbia University Medical Center, New York, NY, USADepartment of Anesthesiology, Columbia University Medical Center, New York, NY, USADepartment of Anesthesiology, Columbia University Medical Center, New York, NY, USADepartment of Neurological Surgery, Columbia University Medical Center, New York, NY, USADepartment of Anesthesiology, Columbia University Medical Center, New York, NY, USAColumbia University Vagelos College of Physicians & Surgeons, New York, NY, USADepartment of Biostatistics, Mailman School of Public Health, New York, NY, USADepartment of Biostatistics, Mailman School of Public Health, New York, NY, USADepartment of Anesthesiology, Columbia University Medical Center, New York, NY, USABackground. COVID-19 may result in multiorgan failure and death. Early detection of patients at risk may allow triage and more intense monitoring. The aim of this study was to develop a simple, objective admission score, based on laboratory tests, that identifies patients who are likely going to deteriorate. Methods. This is a retrospective cohort study of all COVID-19 patients admitted to a tertiary academic medical center in New York City during the COVID-19 crisis in spring 2020. The primary combined endpoint included intubation, stage 3 acute kidney injury (AKI), or death. Laboratory tests available on admission in at least 70% of patients (and age) were included for univariate analysis. Tests that were statistically or clinically significant were then included in a multivariate binary logistic regression model using stepwise exclusion. 70% of all patients were used to train the model, and 30% were used as an internal validation cohort. The aim of this study was to develop and validate a model for COVID-19 severity based on biomarkers. Results. Out of 2545 patients, 833 (32.7%) experienced the primary endpoint. 53 laboratory tests were analyzed, and of these, 47 tests (and age) were significantly different between patients with and without the endpoint. The final multivariate model included age, albumin, creatinine, C-reactive protein, and lactate dehydrogenase. The area under the ROC curve was 0.850 (CI [95%]: 0.813, 0.889), with a sensitivity of 0.800 and specificity of 0.761. The probability of experiencing the primary endpoint can be calculated as p=e−2.4475+0.02492age−0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH/1+e−2.4475+ 0.02492age−0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH. Conclusions. Our study demonstrated that poor outcome in COVID-19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. This is useful for identifying patients at risk during admission.http://dx.doi.org/10.1155/2021/5585291 |
| spellingShingle | Luke Tseng Erin Hittesdorf Mitchell F. Berman Desmond A. Jordan Nina Yoh Katerina Elisman Katherine A. Eiseman Yuqi Miao Shuang Wang Gebhard Wagener Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score Critical Care Research and Practice |
| title | Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score |
| title_full | Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score |
| title_fullStr | Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score |
| title_full_unstemmed | Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score |
| title_short | Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score |
| title_sort | predicting poor outcome of covid 19 patients on the day of admission with the covid 19 score |
| url | http://dx.doi.org/10.1155/2021/5585291 |
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