Declining Mortality Rate of Hospitalised Patients in the Second Wave of the COVID-19 Epidemics in Italy: Risk Factors and the Age-Specific Patterns

Background: Mortality rate from COVID-19 in Italy is among the world’s highest. We aimed to ascertain whether there was any reduction of in-hospital mortality in patients hospitalised for COVID-19 in the second-wave period (October 2020–January 2021) compared to the first one (February–May 2020); further, we verified whether there were clusters of hospitalised patients who particularly benefitted from reduced mortality rate. Methods: Data collected related to in-patients’ demographics, clinical, laboratory, therapies and outcome. Primary end-point was time to in-hospital death. Factors associated were evaluated by uni- and multivariable analyses. A flow diagram was created to determine the rate of in-hospital death according to individual and disease characteristics. Results: A total of 1561 patients were included. The 14-day cumulative incidence of in-hospital death by competing risk regression was of 24.8% (95% CI: 21.3–28.5) and 15.9% (95% CI: 13.7–18.2) in the first and second wave. We observed that the highest relative reduction of death from first to second wave (more than 47%) occurred mainly in the clusters of patients younger than 70 years. Conclusions: Progress in care and supporting therapies did affect population over 70 years to a lesser extent. Preventive and vaccination campaigns should focus on individuals whose risk of death from COVID-19 remains high.

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Mortality and high risk of major adverse events in patients with COVID-19 and history of cardiovascular disease

Open Heart ◽

10.1136/openhrt-2020-001526 ◽

2021 ◽

Vol 8 (1) ◽

pp. e001526

Author(s):

Elena Tessitore ◽

David Carballo ◽

Antoine Poncet ◽

Nils Perrin ◽

Cedric Follonier ◽

...

Keyword(s):

Hospital Mortality ◽

Male Gender ◽

Hospital Death ◽

Chronic Obstructive ◽

University Hospitals ◽

Adverse Cardiovascular Event ◽

Risk Of Death ◽

Hospitalised Patients ◽

Increased Risk ◽

History Of

ObjectiveHistory of cardiovascular diseases (CVDs) may influence the prognosis of patients hospitalised for COVID-19. We investigated whether patients with previous CVD have increased risk of death and major adverse cardiovascular event (MACE) when hospitalised for COVID-19.MethodsWe included 839 patients with COVID-19 hospitalised at the University Hospitals of Geneva. Demographic characteristics, medical history, laboratory values, ECG at admission and medications at admission were collected based on electronic medical records. The primary outcome was a composite of in-hospital mortality or MACE.ResultsMedian age was 67 years, 453 (54%) were males and 277 (33%) had history of CVD. In total, 152 (18%) died and 687 (82%) were discharged, including 72 (9%) who survived a MACE. Patients with previous CVD were more at risk of composite outcomes 141/277 (51%) compared with those without CVD 83/562 (15%) (OR=6.0 (95% CI 4.3 to 8.4), p<0.001). Multivariate analyses showed that history of CVD remained an independent risk factor of in-hospital death or MACE (OR=2.4; (95% CI 1.6 to 3.5)), as did age (OR for a 10-year increase=2.2 (95% CI 1.9 to 2.6)), male gender (OR=1.6 (95% CI 1.1 to 2.3)), chronic obstructive pulmonary disease (OR=2.1 (95% CI 1.0 to 4.2)) and lung infiltration associated with COVID-19 at CT scan (OR=1.9 (95% CI 1.2 to 3.0)). History of CVD (OR=2.9 (95% CI 1.7 to 5)), age (OR=2.5 (95% CI 2.0 to 3.2)), male gender (OR=1.6 (95% CI 0.98 to 2.6)) and elevated C reactive protein (CRP) levels on admission (OR for a 10 mg/L increase=1.1 (95% CI 1.1 to 1.2)) were independent risk factors for mortality.ConclusionHistory of CVD is associated with higher in-hospital mortality and MACE in hospitalised patients with COVID-19. Other factors associated with higher in-hospital mortality are older age, male sex and elevated CRP on admission.

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First and second waves among hospitalised patients with COVID-19 with severe pneumonia: a comparison of 28-day mortality over the 1-year pandemic in a tertiary university hospital in Italy

BMJ Open ◽

10.1136/bmjopen-2021-054069 ◽

2022 ◽

Vol 12 (1) ◽

pp. e054069

Author(s):

Marianna Meschiari ◽

Alessandro Cozzi-Lepri ◽

Roberto Tonelli ◽

Erica Bacca ◽

Marianna Menozzi ◽

...

Keyword(s):

Mortality Rate ◽

Regression Model ◽

Cox Regression ◽

Severe Pneumonia ◽

University Hospital ◽

P Value ◽

Cox Regression Model ◽

Hospitalised Patients ◽

The Impact ◽

Second Wave

ObjectiveThe first COVID-19–19 epidemic wave was over the period of February–May 2020. Since 1 October 2020, Italy, as many other European countries, faced a second wave. The aim of this analysis was to compare the 28-day mortality between the two waves among COVID-19 hospitalised patients.DesignObservational cohort study. Standard survival analysis was performed to compare all-cause mortality within 28 days after hospital admission in the two waves. Kaplan-Meier curves as well as Cox regression model analysis were used. The effect of wave on risk of death was shown by means of HRs with 95% CIs. A sensitivity analysis around the impact of the circulating variant as a potential unmeasured confounder was performed.SettingUniversity Hospital of Modena, Italy. Patients admitted to the hospital for severe COVID-19 pneumonia during the first (22 February–31 May 2020) and second (1 October–31 December 2020) waves were included.ResultsDuring the two study periods, a total of 1472 patients with severe COVID-19 pneumonia were admitted to our hospital, 449 during the first wave and 1023 during the second. Median age was 70 years (IQR 56–80), 37% women, 49% with PaO2/FiO2 <250 mm Hg, 82% with ≥1 comorbidity, median duration of symptoms was 6 days. 28-day mortality rate was 20.0% (95% CI 16.3 to 23.7) during the first wave vs 14.2% (95% CI 12.0 to 16.3) in the second (log-rank test p value=0.03). After including key predictors of death in the multivariable Cox regression model, the data still strongly suggested a lower 28-day mortality rate in the second wave (aHR=0.64, 95% CI 0.45 to 0.90, p value=0.01).ConclusionsIn our hospitalised patients with COVID-19 with severe pneumonia, the 28-day mortality appeared to be reduced by 36% during the second as compared with the first wave. Further studies are needed to identify factors that may have contributed to this improved survival.

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Diabetes, even newly defined by HbA1c testing, is associated with an increased risk of in-hospital death in adults with COVID-19

10.21203/rs.3.rs-93792/v1 ◽

2020 ◽

Author(s):

Ye Liu ◽

Ran Lu ◽

Junhong Wang ◽

Qin Cheng ◽

Ruitao Zhang ◽

...

Keyword(s):

Risk Factors ◽

Mortality Rate ◽

Survival Probability ◽

Cox Regression ◽

Undiagnosed Diabetes ◽

Hospital Death ◽

Diabetes Group ◽

Risk Of Death ◽

Increased Risk ◽

The Impact

Abstract Aims: Diabetes is associated with poor coronavirus disease 2019 (COVID-19) outcomes. However, little is known on the impact of undiagnosed diabetes in the COVID-19 population. We investigated whether diabetes, particularly undiagnosed diabetes, was associated with an increased risk of death from COVID-19.Methods: This retrospective study identified adult patients with COVID-19 admitted to Tongji Hospital (Wuhan) from January 28 to April 4, 2020. Diabetes was determined using patients’ past history (diagnosed) or was newly defined if the hemoglobin A1c (HbA1c) level at admission was 6.5% (≥ 48 mmol/mol) (undiagnosed). The in-hospital mortality rate and survival probability were compared between the non-diabetes and diabetes (overall, diagnosed, and undiagnosed diabetes) groups. Risk factors of mortality were explored using Cox regression analysis. Results: Of 373 patients, 233 were included in the final analysis, among whom 80 (34.3%) had diabetes: 44 (55.0%) reported a diabetes history, and 36 (45.0%) were newly defined as having undiagnosed diabetes by HbA1c testing at admission. Compared with the non-diabetes group, the overall diabetes group had a significantly increased mortality rate (22.5% vs 5.9%, p <0.001). Moreover, the overall, diagnosed, and undiagnosed diabetes groups displayed lower survival probability in the Kaplan-Meier survival analysis (all p <0.01). Using multivariate Cox regression, diabetes, age, quick sequential organ failure assessment score, and D-dimer ≥ 1.0 mg/mL were identified as independent risk factors for in-hospital death in patients with COVID-19.Conclusions: The prevalence of undiagnosed pre-existing diabetes among patients with COVID-19 is high in China. Diabetes, even newly defined by HbA1c testing at admission, is associated with increased mortality in patients with COVID-19. Screening for undiagnosed diabetes by HbA1c measurement should be considered in adult Chinese inpatients with COVID-19.

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An Epidemiological Analysis of Head Injuries in Taiwan

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15112457 ◽

2018 ◽

Vol 15 (11) ◽

pp. 2457 ◽

Cited By ~ 6

Author(s):

I-Lin Hsu ◽

Chung-Yi Li ◽

Da-Chen Chu ◽

Li-Chien Chien

Keyword(s):

Risk Factors ◽

Head Injury ◽

Mortality Rate ◽

Hospital Mortality ◽

Rural Area ◽

Head Injuries ◽

Hospital Death ◽

National Health Insurance System ◽

Risk Of Death ◽

Acute Head Injury

Traumatic head injuries occur frequently in Taiwan, having catastrophic consequences for the victims, their families, and society as a whole. However, little is known about the risk factors at the population level in Taiwan. The primary aim of this study was to obtain more information on these variables and their relationships. Another aim was to analyze the effects of independent variables such as sex, age, residency, pre-existing conditions, mechanisms of injury, associated injuries, and severity on the probability of in-hospital death. Using the 2007–2008 total admissions claim dataset from Taiwan’s National Health Insurance system, total admissions due to acute head injury were selected for further analysis. The obtained data included patient demographics and trauma hospitalization rate. A total of 99,391 patients were admitted with head injury, 48,792 of which had moderate-to-severe head injury. There were 4935 cases recorded as in-hospital mortality and the standardized in-hospital mortality rate was 10.7 deaths per 100,000 person-years. The mortality rate increased with age. After adjustments, male sex, age older than 54 years, living in a rural area, lower monthly income, a Charlson comorbidity index greater than one, being a pedestrian hit by a motor vehicle, fall from a height, and having significant chest, abdominal, or lower extremity injury increased the risk of death during admission. This population-based analysis provides information about the incidence rate and death rate for admissions in Taiwan due to acute head injury and the factors that affect in-hospital mortality. Our results that highlight the risk factors for adverse outcome can help us prevent or improve rural area trauma care of head injury patients in the future.

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The prognostic role of functional dependency in older inpatients with COVID-19

BMC Geriatrics ◽

10.1186/s12877-021-02158-1 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Galina Plotnikov ◽

Efraim Waizman ◽

Irma Tzur ◽

Alexander Yusupov ◽

Yonatan Shapira ◽

...

Keyword(s):

Mortality Rate ◽

Functional Status ◽

Clinical Laboratory ◽

Prognostic Significance ◽

Functional Dependency ◽

Mortality Data ◽

Elderly Persons ◽

Risk Of Death ◽

Group 4 ◽

Older Inpatients

Abstract Background Coronavirus disease 2019 (COVID-19) is a pandemic infection with substantial risk of death, especially in elderly persons. Information about the prognostic significance of functional status in older patients with COVID-19 is scarce. Methods Demographic, clinical, laboratory and short-term mortality data were collected of 186 consecutive patients aged ≥ 65 years hospitalized with COVID-19. The data were compared between 4 study groups: (1) age 65–79 years without severe functional dependency; (2) age ≥ 80 years without severe functional dependency; (3) age 65–79 years with severe functional dependency; and (4) age ≥ 80 years with severe functional dependency. Multivariate logistic regressions were performed to evaluate the variables that were most significantly associated with mortality in the entire sample. Results Statistically significant differences were observed between the groups in the proportions of males (p = 0.007); of patients with diabetes mellitus (p = 0.025), cerebrovascular disease (p < 0.001), renal failure (p = 0.003), dementia (p < 0.001), heart failure (p = 0.005), pressure sores (p < 0.001) and malignant disorders (p = 0.007); and of patients residing in nursing homes (p < 0.001). Compared to groups 1 (n = 69) and 2 (n = 28), patients in groups 3 (n = 32) and 4 (n = 57) presented with lower mean serum albumin levels on admission (p < 0.001), and were less often treated with convalescent plasma (p < 0.001), tocilizumab (p < 0.001) and remdesivir (p < 0.001). The overall mortality rate was 23.1 %. The mortality rate was higher in group 4 than in groups 1 − 3: 45.6 % vs. 8.7 %, 17.9% and 18.3 %, respectively (p < 0.001). On multivariate analysis, both age ≥ 80 years and severe functional dependency were among the variables most significantly associated with mortality in the entire cohort (odds ratio [OR] 4.83, 95 % confidence interval [CI] 1.88 − 12.40, p < 0.001 and OR 2.51, 95 % CI 1.02 − 6.15, p = 0.044, respectively). Age ≥ 80 years with severe functional dependency (group 4) remained one of the variables most significantly associated with mortality (OR 10.42, 95 % CI 3.27–33.24 and p < 0.001). Conclusions Among patients with COVID-19, the association of severe functional dependency with mortality is stronger among those aged ≥ 80 years than aged 65–79 years. Assessment of functional status may contribute to decision making for care of older inpatients with COVID-19.

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Diabetes, even newly defined by HbA1c testing, is associated with an increased risk of in-hospital death in adults with COVID-19

BMC Endocrine Disorders ◽

10.1186/s12902-021-00717-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ye Liu ◽

Ran Lu ◽

Junhong Wang ◽

Qin Cheng ◽

Ruitao Zhang ◽

...

Keyword(s):

Risk Factors ◽

Mortality Rate ◽

Survival Probability ◽

Cox Regression ◽

Undiagnosed Diabetes ◽

Hospital Death ◽

Diabetes Group ◽

Risk Of Death ◽

Increased Risk ◽

The Impact

Abstract Background Diabetes is associated with poor coronavirus disease 2019 (COVID-19) outcomes. However, little is known on the impact of undiagnosed diabetes in the COVID-19 population. We investigated whether diabetes, particularly undiagnosed diabetes, was associated with an increased risk of death from COVID-19. Methods This retrospective study identified adult patients with COVID-19 admitted to Tongji Hospital (Wuhan) from January 28 to April 4, 2020. Diabetes was determined using patients’ past history (diagnosed) or was newly defined if the hemoglobin A1c (HbA1c) level at admission was ≥6.5% (48 mmol/mol) (undiagnosed). The in-hospital mortality rate and survival probability were compared between the non-diabetes and diabetes (overall, diagnosed, and undiagnosed diabetes) groups. Risk factors of mortality were explored using Cox regression analysis. Results Of 373 patients, 233 were included in the final analysis, among whom 80 (34.3%) had diabetes: 44 (55.0%) reported a diabetes history, and 36 (45.0%) were newly defined as having undiagnosed diabetes by HbA1c testing at admission. Compared with the non-diabetes group, the overall diabetes group had a significantly increased mortality rate (22.5% vs. 5.9%, p < 0.001). Moreover, the overall, diagnosed, and undiagnosed diabetes groups displayed lower survival probability in the Kaplan-Meier survival analysis (all p < 0.01). Using multivariate Cox regression, diabetes, age, quick sequential organ failure assessment score, and D-dimer ≥1.0 μg/mL were identified as independent risk factors for in-hospital death in patients with COVID-19. Conclusions The prevalence of undiagnosed pre-existing diabetes among patients with COVID-19 is high in China. Diabetes, even newly defined by HbA1c testing at admission, is associated with increased mortality in patients with COVID-19. Screening for undiagnosed diabetes by HbA1c measurement should be considered in adult Chinese inpatients with COVID-19.

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Diabetes, Even Newly Defined by HbA1c Testing, Is Associated With an Increased Risk of in-hospital Death in Adults With COVID-19

10.21203/rs.3.rs-133453/v1 ◽

2020 ◽

Author(s):

Ye Liu ◽

Ran Lu ◽

Junhong Wang ◽

Qin Cheng ◽

Ruitao Zhang ◽

...

Keyword(s):

Risk Factors ◽

Mortality Rate ◽

Survival Probability ◽

Cox Regression ◽

Undiagnosed Diabetes ◽

Hospital Death ◽

Diabetes Group ◽

Risk Of Death ◽

Increased Risk ◽

The Impact

Abstract Background: Diabetes is associated with poor coronavirus disease 2019 (COVID-19) outcomes. However, little is known on the impact of undiagnosed diabetes in the COVID-19 population. We investigated whether diabetes, particularly undiagnosed diabetes, was associated with an increased risk of death from COVID-19.Methods: This retrospective study identified adult patients with COVID-19 admitted to Tongji Hospital (Wuhan) from January 28 to April 4, 2020. Diabetes was determined using patients’ past history (diagnosed) or was newly defined if the hemoglobin A1c (HbA1c) level at admission was 6.5% (≥ 48 mmol/mol) (undiagnosed). The in-hospital mortality rate and survival probability were compared between the non-diabetes and diabetes (overall, diagnosed, and undiagnosed diabetes) groups. Risk factors of mortality were explored using Cox regression analysis. Results: Of 373 patients, 233 were included in the final analysis, among whom 80 (34.3%) had diabetes: 44 (55.0%) reported a diabetes history, and 36 (45.0%) were newly defined as having undiagnosed diabetes by HbA1c testing at admission. Compared with the non-diabetes group, the overall diabetes group had a significantly increased mortality rate (22.5% vs 5.9%, p <0.001). Moreover, the overall, diagnosed, and undiagnosed diabetes groups displayed lower survival probability in the Kaplan-Meier survival analysis (all p <0.01). Using multivariate Cox regression, diabetes, age, quick sequential organ failure assessment score, and D-dimer ≥ 1.0 mg/mL were identified as independent risk factors for in-hospital death in patients with COVID-19.Conclusions: The prevalence of undiagnosed pre-existing diabetes among patients with COVID-19 is high in China. Diabetes, even newly defined by HbA1c testing at admission, is associated with increased mortality in patients with COVID-19. Screening for undiagnosed diabetes by HbA1c measurement should be considered in adult Chinese inpatients with COVID-19.

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COVID Outcome Prediction in the Emergency Department (COPE)

10.1101/2020.12.30.20249023 ◽

2021 ◽

Author(s):

David van Klaveren ◽

Alexandros Rekkas ◽

Jelmer Alsma ◽

Rob JCG Verdonschot ◽

Dick TJJ Koning ◽

...

Keyword(s):

Emergency Department ◽

Hospital Admission ◽

Outcome Prediction ◽

Model Performance ◽

Hospital Death ◽

Icu Admission ◽

Risk Of Death ◽

Increased Risk ◽

Temporal Validation ◽

Second Wave

ABSTRACTBackground and aimThe COVID-19 pandemic is putting extraordinary pressure on emergency departments (EDs). To support decision making about hospital admission, we aimed to develop a simple and valid model for predicting mortality and need for admission to an intensive care unit (ICU) in suspected-COVID-19 patients presenting at the ED.MethodsFor model development, we included patients that presented at the ED and were admitted to 4 large Dutch hospitals with suspected COVID-19 between March and August 2020, the first wave of the pandemic in the Netherlands. Based on prior literature we included patient characteristics, vital parameters and blood test values, all measured at ED admission, as potential predictors. Logistic regression analyses with post-hoc uniform shrinkage was used to obtain predicted probabilities of in-hospital death and of being admitted to the ICU, both within 28 days after admission. Model performance (AUC; calibration plots, intercepts and slopes) was assessed with temporal validation in patients who presented between September and December 2020 (second wave). We used multiple imputation to account for missing predictor values.ResultsThe development data included 5,831 patients who presented at the ED and were hospitalized, of whom 629 (10.8%) died and 5,070 (86.9%) were discharged within 28 days after admission. A simple model – named COVID Outcome Prediction in the Emergency Department (COPE) – with linear age and logarithmic transforms of respiratory rate, CRP, LDH, albumin and urea captured most of the ability to predict death within 28 days. Patients who were admitted in the first month of the pandemic had substantially increased risk of death (odds ratio 1.99; 95% CI 1.61-2.47). COPE was well-calibrated and showed good discrimination for predicting death in 3,252 patients of the second wave (AUC in 4 hospitals: 0.82; 0.82; 0.79; 0.83). COPE was also able to identify patients at high risk of needing IC in second wave patients below the age of 70 (AUC 0.84; 0.81), but overestimated ICU admission for low-risk patients. The models are implemented as a web-based application.ConclusionCOPE is a simple tool that is well able to predict mortality and ICU admission for patients who present to the ED with suspected COVID-19 and may help to inform patients and doctors when deciding on hospital admission.

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Characteristics and outcome of patients with COVID-19 complicated by Takotsubo cardiomyopathy: case series with literature review

Open Heart ◽

10.1136/openhrt-2020-001360 ◽

2020 ◽

Vol 7 (2) ◽

pp. e001360 ◽

Cited By ~ 1

Author(s):

Shruti Hegde ◽

Rizwan Khan ◽

Magdi Zordok ◽

Michael Maysky

Keyword(s):

High Risk ◽

Mortality Rate ◽

Takotsubo Cardiomyopathy ◽

Clinical Characteristics ◽

Clinical Laboratory ◽

Case Series ◽

High Risk Group ◽

Hospital Death ◽

Retrospective Case ◽

Improved Outcomes

BackgroundCardiac involvement with COVID-19 is increasingly being recognised. Clinical characteristics and outcomes of patients with COVID-19 complicated by secondary Takotsubo cardiomyopathy (TC) is poorly understood.MethodsThis retrospective case series was conducted between March and April 2020 at four hospitals of Steward Health Care Network of Massachusetts, USA. Seven patients out of 169 who had echocardiogram were identified to have features of TC. Demographic, clinical, laboratory, management and outcome were gathered from their electronic medical records. We also reviewed all the published cases of COVID-19 and TC in the literature to recognise their common clinical characteristics, risk factors and outcomes.ResultsIn our series of seven patients, three typical, two inverted, one biventricular and one global TC were recognised. Three were females and four were males. The mean age was 71±11 years. In-hospital death was observed in 57% of patients. Patients who belonged to the high-risk group and had high-risk echocardiographic features in our series had a 100% mortality rate.ConclusionsCOVID-19 complicated by TC has a high mortality rate. Early identification of patients with COVID-19 who are at higher risk for developing secondary TC is important for the prevention of complications, and thus improved outcomes.

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3219 hospitalised patients with COVID-19 in Southeast Michigan: a retrospective case cohort study

BMJ Open ◽

10.1136/bmjopen-2020-042042 ◽

2021 ◽

Vol 11 (4) ◽

pp. e042042

Author(s):

Elie Mulhem ◽

Andrew Oleszkowicz ◽

David Lick

Keyword(s):

Mechanical Ventilation ◽

Cohort Study ◽

Mortality Rate ◽

Hospital Mortality ◽

Chronic Diseases ◽

Hospital Death ◽

Retrospective Case ◽

Peak Period ◽

Common Chronic Disease ◽

Hospitalised Patients

ObjectiveTo report the clinical characteristics of patients hospitalised with COVID-19 in Southeast Michigan.DesignRetrospective cohort study.SettingEight hospitals in Southeast Michigan.Participants3219 hospitalised patients with a positive SARS-CoV-2 infection by nasopharyngeal PCR test from 13 March 2020 until 29 April 2020.Main outcomes measuresOutcomes were discharge from the hospital or in-hospital death. Examined predictors included patient demographics, chronic diseases, home medications, mechanical ventilation, in-hospital medications and timeframe of hospital admission. Multivariable logistic regression was conducted to identify risk factors for in-hospital mortality.ResultsDuring the study period, 3219 (90.4%) patients were discharged or died in the hospital. The median age was 65.2 (IQR 52.6–77.2) years, the median length of stay in the hospital was 6.0 (IQR 3.2–10.1) days, and 51% were female. Hypertension was the most common chronic disease, occurring in 2386 (74.1%) patients. Overall mortality rate was 16.0%. Blacks represented 52.3% of patients and had a mortality rate of 13.5%. Mortality was highest at 18.5% in the prepeak hospital COVID-19 volume, decreasing to 15.3% during the peak period and to 10.8% in the postpeak period. Multivariable regression showed increasing odds of in-hospital death associated with older age (OR 1.04, 95% CI 1.03 to 1.05, p<0.001) for every increase in 1 year of age and being male (OR 1.47, 95% CI 1.21 to 1.81, p<0.001). Certain chronic diseases increased the odds of in-hospital mortality, especially chronic kidney disease. Administration of vitamin C, corticosteroids and therapeutic heparin in the hospital was associated with higher odds of death.ConclusionIn-hospital mortality was highest in early admissions and improved as our experience in treating patients with COVID-19 increased. Blacks were more likely to get admitted to the hospital and to receive mechanical ventilation, but less likely to die in the hospital than whites.

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