Comorbidities, sequelae, blood biomarkers and their associated clinical outcomes in the Mount Sinai Health System COVID-19 patients

Inflammatory Biomarkers for Assessing In-Hospital Mortality Risk in Severe COVID-19-A Retrospective Study

(1) Background: Our study aims to investigate the utility of inflammatory factors as prognostic indicators for disease severity and mortality in COVID-19 patients admitted to the Intensive Care Unit (ICU) Department of Pelican Clinical Hospital Oradea Romania. While elevated white blood cell (WBC) levels are associated with COVID-19 severity and mortality, they may not effectively predict the risk of death; (2) Methods: In our ICU department, we conducted assessments on the 10th and 14th days of COVID-19 patients' hospitalization, measuring the following markers: C-reactive protein (CRP) levels, procalcitonin (PCT) levels, granulocytes/lymphocytes (G/L) ratios, ferritin levels, age, and obesity status. We included a total of 209 eligible COVID-19 patients in the final analysis. Our goal was to identify biomarkers that could quickly identify high-risk patients with a potential for disease progression and mortality; (3) Results: Our study (a retrospective, single-center observational cohort study) demonstrated statistically significant differences in predicting mortality and disease severity based on G/L ratio (p < 0.0001), PCT (p < 0.0002), CRP (p < 0.0001), ferritin (p < 0.0001), age (p < 0.0001), and obesity (p < 0.0001); (4) Conclusions: Having a G/L ratio exceeding 20 units, along with elevated levels of PCR, PCT, and ferritin in older and obese patients on the 3rd day of ICU admission, represents significant risk factors for in-hospital mortality in severe COVID-19 patients.

Thrombo-inflammatory response in hospitalised patients with COVID-19: a single institution experience

BACKGROUND

Severe COVID-19 causes acute inflammation, which is complicated by venous thromboembolism events (VTE). However, it is unclear if VTE risk has evolved over time since the COVID-19 outbreak.

AIMS

To determine markers of thrombo-inflammation and rates of symptomatic VTE in patients hospitalised for COVID-19 in a metropolitan hospital in Sydney, Australia.

METHODS

A retrospective, single-centre, cohort study was performed by reviewing electronic medical records of consecutive patients admitted to Royal Prince Alfred Hospital between March 2020 and September 2021. This period included three waves of COVID-19 outbreaks in Australia with the ancestral, alpha and delta variants. Standard coagulation assays and inflammatory markers were recorded over 4 weeks.

RESULTS

A total of 205 patients were consecutively admitted during the study period. Activated partial thromboplastin time, neutrophil count and C-reactive protein (CRP) were significantly increased in patients hospitalised in the intensive care unit (ICU) compared with non-ICU patients. The use of anti-inflammatory medication increased in 2021 compared with 2020. The mortality rate was 7.3% in our cohort. Ninety-four per cent of patients received anticoagulation with 6.3% of patients developing VTE.

CONCLUSION

We observed lower rates of VTE compared to the internationally reported rate for the same period. We conclude that in the setting of controlled hospital admission rate and standard anticoagulation guidelines, COVID-19 resulted in similar thrombo-inflammatory response and VTE rates over the first 1.5 years of the pandemic.

Older adults with epilepsy and COVID-19: Outcomes in a multi-hospital health system

BACKGROUND

Coronavirus disease 2019 (COVID-19) is associated with high rates of mortality and morbidity in older adults, especially those with pre-existing conditions. There is little work investigating how neurological conditions affect older adults with COVID-19. We aimed to compare in-hospital outcomes, including mortality, in older adults with and without epilepsy.

METHODS

This retrospective study in a large multicenter New York health system included consecutive older patients (age ≥65 years) either with or without epilepsy who were admitted with COVID-19 between 3/2020-5/2021. Epilepsy was identified using a validated International Classification of Disease (ICD) and antiseizure medicationbased case definition. Univariate comparisons were calculated using Chi-square, Fisher's exact, Mann-Whitney U, or Student's t-tests. Multivariable logistic regression models were generated to examine factors associated with mortality, discharge disposition and length of stay (LOS).

RESULTS

We identified 5384 older adults admitted with COVID-19 of whom 173 (3.21 %) had epilepsy. Mean age was significantly lower in those with (75.44, standard deviation (SD): 7.23) compared to those without epilepsy (77.98, SD: 8.68, p = 0.007). Older adults with epilepsy were more likely to be ventilated (35.84 % vs. 16.18 %, p < 0.001), less likely to be discharged home (21.39 % vs. 43.12 %, p < 0.001), had longer median LOS (13 days vs. 8 days, p < 0.001), and had higher in-hospital death (35.84 % vs. 28.29 %, p = 0.030) compared to those without epilepsy. Epilepsy in older adults was associated with increased odds of in-hospital death (adjusted odds ratio (aOR), 1.55; 95 % CI 1.12-2.14, p = 0.032), non-routine discharge disposition (aOR, 3.34; 95 % CI 2.21-5.03, p < 0.001), and longer LOS (46.46 % 95 % CI 34 %-59 %, p < 0.001).

CONCLUSIONS

In models that adjusted for multiple confounders including comorbidity and age, our study found that epilepsy was still associated with higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19 higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19. This work reinforces that epilepsy is a risk factor for worse outcomes in older adults admitted with COVID-19. Timely identification and treatment of COVID-19 in epilepsy may improve outcomes in older people with epilepsy.

The Effect of Metabolic Control on Diabetes Complication Rates and the Need for Medical Care During COVID-19 Social Isolation in Adjara, Georgia

INTRODUCTION

Social isolation or distancing during the COVID-19 pandemic was associated with poor metabolic control in patients with diabetes mellitus. It might have contributed to the high mortality rate of those with diabetes who became infected. This study aims to determine the degree or level of metabolic control in patients with diabetes mellitus, the progression of its complications, and the need for emergency care during social isolation caused by the COVID-19 pandemic.

MATERIALS AND METHODS

A retrospective study was conducted in Georgia on 752 diabetic patients aged under 65 years old. Results showed that many patients did not control their blood glucose levels, measure their blood pressure, or know their cholesterol and glycated hemoglobin levels before and after the pandemic. Over 35% of patients experienced glycemic profile fluctuations. We compared metabolic rates with complications of diabetes and the need for emergency medical care during isolation. It was found that the testability of glycemia (p = 0.006), fluctuations in glucose (p = 0.001), and glycated hemoglobin levels before (p = 0.001) and after the pandemic (p = 0.004) increased the prevalence of diabetes-related heart disease and multiple micro- and macroangiopathies. Blood pressure (p = 0.001), cholesterol levels (p = 0.001), and glucose control (p = 0.012) affected the condition of patients with diabetes mellitus. It increased the need for medical care due to infarction, hypertension crisis, and hyperglycemia.

CONCLUSIONS

In a crisis where medical care is limited, the management of diabetes patients requires more attention. Our study proves that active middle-aged patients during isolation had poor metabolic control in terms of self-control of the disease. It is necessary to constantly inform and educate patients about the importance of metabolic parameters in progressing diabetes complications. Proper metabolic control could prevent complications of diabetes and improve a patient's quality of life.

In-hospital outcomes in patients with and without epilepsy diagnosed with COVID-19-A cohort study

OBJECTIVES

Coronavirus disease 2019 (COVID-19) is associated with mortality in persons with comorbidities. The aim of this study was to evaluate in-hospital outcomes in patients with COVID-19 with and without epilepsy.

METHODS

We conducted a retrospective study of patients with COVID-19 admitted to a multicenter health system between March 15, 2020, and May 17, 2021. Patients with epilepsy were identified using a validated International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)/ICD-10-CM case definition. Logistic regression models and Kaplan-Meier analyses were conducted for mortality and non-routine discharges (i.e., not discharged home). An ordinary least-squares regression model was fitted for length of stay (LOS).

RESULTS

We identified 9833 people with COVID-19 including 334 with epilepsy. On univariate analysis, people with epilepsy had significantly higher ventilator use (37.70% vs 14.30%, p < .001), intensive care unit (ICU) admissions (39.20% vs 17.70%, p < .001) mortality rate (29.60% vs 19.90%, p < .001), and longer LOS (12 days vs 7 days, p < .001). and fewer were discharged home (29.64% vs 57.37%, p < .001). On multivariate analysis, only non-routine discharge (adjusted odds ratio [aOR] 2.70, 95% confidence interval [CI] 2.00-3.70; p < .001) and LOS (32.50% longer, 95% CI 22.20%-43.60%; p < .001) were significantly different. Factors associated with higher odds of mortality in epilepsy were older age (aOR 1.05, 95% CI 1.03-1.08; p < .001), ventilator support (aOR 7.18, 95% CI 3.12-16.48; p < .001), and higher Charlson comorbidity index (CCI) (aOR 1.18, 95% CI 1.04-1.34; p = .010). In epilepsy, admissions between August and December 2020 or January and May 2021 were associated with a lower odds of non-routine discharge and decreased LOS compared to admissions between March and July 2020, but this difference was not statistically significant.

SIGNIFICANCE

People with COVID-19 who had epilepsy had a higher odds of non-routine discharge and longer LOS but not higher mortality. Older age (≥65), ventilator use, and higher CCI were associated with COVID-19 mortality in epilepsy. This suggests that older adults with epilepsy and multimorbidity are more vulnerable than those without and should be monitored closely in the setting of COVID-19.

A probabilistic approach for the study of epidemiological dynamics of infectious diseases: Basic model and properties

The dynamics of epidemiological phenomena associated to infectious diseases have long been modelled taking different approaches. However, recent pandemic events exposed many areas of opportunity to improve the existing models. We develop a stochastic model based on the idea that transitions between epidemiological stages are alike sampling processes that may involve more than one subset of the population or may be mostly dependent on time intervals defined by pathological or clinical criteria. We apply the model to simulate epidemics, analyse the final distribution of the case fatality ratio, and define a basic reproductive number to determine the existence of a probabilistic phase transition for the dynamics. The resulting modelling scheme is robust, easy to implement, and can readily lend itself for extensions aimed at answering questions that emerge from close examination of data trends, such as those emerging from the COVID-19 pandemic, and other infectious diseases.

Unraveling Acute and Post-COVID Cytokine Patterns to Anticipate Future Challenges

The aims of this study were to analyze cytokine profiles in patients with COVID-19, gain insights into the immune response during acute infection, identify cytokines associated with disease severity and post-COVID complications, and explore potential biomarkers for prognosis and therapeutic targets. Using a multiplex analysis, we studied the cytokine pattern in 294 acute COVID-19 and post-COVID patients with varying severities of infection. Our findings revealed that disease severity was associated with elevated levels of IL-15, IL-8, and fractalkine. Severe/extremely severe forms in comparison with mild/moderate disease were associated with MCP-1, IFNa2, IL-7, IL-15, EGF, IP-10, IL-8, Eotaxin, FGF-2, GROa, sCD40L, and IL-10. The key cytokines of post-COVID are FGF-2, VEGF-A, EGF, IL-12(p70), IL-13, and IL-6. By the sixth month after recovering from a coronavirus infection, regardless of disease severity, some patients may develop complications such as arterial hypertension, type 2 diabetes mellitus, glucose intolerance, thyrotoxicosis, atherosclerosis, and rapid progression of previously diagnosed conditions. Each complication is characterized by distinct cytokine profiles. Importantly, these complications can also be predicted during the acute phase of the coronavirus infection. Understanding cytokine patterns can aid in predicting disease progression, identifying high-risk patients, and developing targeted interventions to improve the outcomes of COVID-19.

Rehabilitation Therapy Allocation and Changes in Physical Function Among Patients Hospitalized Due to COVID-19: A Retrospective Cohort Analysis

OBJECTIVE

Limited staffing and initial transmission concerns have limited rehabilitation services during the COVID-19 pandemic. The purpose of this analysis was to determine the associations between Activity Measure for Post-Acute Care (AM-PAC) mobility categories and allocation of rehabilitation, and in-hospital AM-PAC score change and receipt of rehabilitation services for patients with COVID-19.

METHODS

This was a retrospective cohort study of electronic health record data from 1 urban hospital, including adults with a COVID-19 diagnosis, admitted August 2020 to April 2021. Patients were stratified by level of medical care (intensive care unit [ICU] and floor). Therapy allocation (referral for rehabilitation, receipt of rehabilitation, and visit frequency) was the primary outcome; change in AM-PAC score was secondary. AM-PAC Basic Mobility categories (None [21-24], Minimum [18-21], Moderate [10-17], and Maximum [6-9]) were the main predictor variable. Primary analysis included logistic and linear regression, adjusted for covariates.

RESULTS

A total of 1397 patients (ICU: n = 360; floor: n = 1037) were included. AM-PAC mobility category was associated with therapy allocation outcomes for floor but not patients in the ICU: the Moderate category had greater adjusted odds of referral (adjusted odds ratio [aOR] = 10.88; 95% CI = 5.71-21.91), receipt of at least 1 visit (aOR = 3.45; 95% CI = 1.51-8.55), and visit frequency (percentage mean difference) (aOR = 42.14; 95% CI = 12.45-79.67). The secondary outcome of AM-PAC score improvement was highest for patients in the ICU who were given at least 1 rehabilitation therapy visit (aOR = 5.31; 95% CI = 1.90-15.52).

CONCLUSION

AM-PAC mobility categories were associated with rehabilitation allocation outcomes for floor patients. AM-PAC score improvement was highest among patients requiring ICU-level care with at least 1 rehabilitation therapy visit.

IMPACT

Use of AM-PAC Basic Mobility categories may help improve decisions for rehabilitation therapy allocation among patients who do not require critical care, particularly during times of limited resources.

Developing a mortality risk prediction model using data of 3663 hospitalized COVID-19 patients: a retrospective cohort study in an Egyptian University Hospital

PURPOSE

Since the declaration of COVID-19 as a pandemic, a wide between-country variation was observed regarding in-hospital mortality and its predictors. Given the scarcity of local research and the need to prioritize the provision of care, this study was conducted aiming to measure the incidence of in-hospital COVID-19 mortality and to develop a simple and clinically applicable model for its prediction.

METHODS

COVID-19-confirmed patients admitted to the designated isolation areas of Ain-Shams University Hospitals (April 2020-February 2021) were included in this retrospective cohort study (n = 3663). Data were retrieved from patients' records. Kaplan-Meier survival and Cox proportional hazard regression were used. Binary logistic regression was used for creating mortality prediction models.

RESULTS

Patients were 53.6% males, 4.6% current smokers, and their median age was 58 (IQR 41-68) years. Admission to intensive care units was 41.1% and mortality was 26.5% (972/3663, 95% CI 25.1-28.0%). Independent mortality predictors-with rapid mortality onset-were age ≥ 75 years, patients' admission in critical condition, and being symptomatic. Current smoking and presence of comorbidities particularly, obesity, malignancy, and chronic haematological disorders predicted mortality too. Some biomarkers were also recognized. Two prediction models exhibited the best performance: a basic model including age, presence/absence of comorbidities, and the severity level of the condition on admission (Area Under Receiver Operating Characteristic Curve (AUC) = 0.832, 95% CI 0.816-0.847) and another model with added International Normalized Ratio (INR) value (AUC = 0.842, 95% CI 0.812-0.873).

CONCLUSION

Patients with the identified mortality risk factors are to be prioritized for preventive and rapid treatment measures. With the provided prediction models, clinicians can calculate mortality probability for their patients. Presenting multiple and very generic models can enable clinicians to choose the one containing the parameters available in their specific clinical setting, and also to test the applicability of such models in a non-COVID-19 respiratory infection.

Clinical Characteristics and Predictors of Mortality in Elderly Patients Hospitalized with COVID-19 in Bangladesh: A Multicenter, Retrospective Study

Purpose

Elderly patients are at high risk of fatality from COVID-19. The present work aims to describe the clinical characteristics of elderly inpatients with COVID-19 and identify the predictors of in-hospital mortality at admission.

Materials and Methods

In this retrospective, multicenter cohort study, we included elderly COVID-19 inpatients (n = 245) from four hospitals in Sylhet, Bangladesh, who had been discharged between October 2020 and February 2021. Demographic, clinical, and laboratory data were extracted from hospital records and compared between survivors and nonsurvivors. We used univariable and multivariable logistic regression analysis to explore the risk factors associated with in-hospital death. Principal Results. Of the included patients, 202 (82.44%) were discharged and 43 (17.55%) died in hospital. Except hypertension, other comorbidities like diabetes, chronic kidney disease, ischemic heart disease, and chronic obstructive pulmonary disease were more prevalent in nonsurvivors. Nonsurvivors had a higher prevalence of leukocytosis (51.2 versus 30.7; p=0.01), lymphopenia (72.1 versus 55; p=0.05), and thrombocytopenia (20.9 versus 9.9; p=0.07). Multivariable regression analysis showed an increasing odds ratio of in-hospital death associated with older age (odds ratio 1.05, 95% CI 1.01–1.10, per year increase; p=0.009), thrombocytopenia (OR = 3.56; 95% CI 1.22–10.33, p=0.019), and admission SpO₂ (OR 0.91, 95% CI 0.88–0.95; p=0.001).

Conclusions

Higher age, thrombocytopenia, and lower initial level of SpO₂ at admission are predictors of in-hospital mortality in elderly patients with COVID-19.

Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study

Our study objective was to construct models using 20 routine laboratory parameters on admission to predict disease severity and mortality risk in a group of 254 hospitalized COVID-19 patients. Considering the influence of confounding factors in this single-center study, we also retrospectively assessed the correlations between the risk of death and the routine laboratory parameters within individual comorbidity subgroups. In multivariate regression models and by ROC curve analysis, a model of three routine laboratory parameters (AUC 0.85; 95% CI: 0.79–0.91) and a model of six laboratory factors (AUC 0.86; 95% CI: 0.81–0.91) were able to predict severity and mortality of COVID-19, respectively, compared with any other individual parameter. Hierarchical cluster analysis showed that inflammatory laboratory markers grouped together in three distinct clusters including positive correlations: WBC with NEU, NEU with neutrophil-to-lymphocyte ratio (NLR), NEU with systemic immune-inflammation index (SII), NLR with SII and platelet-to-lymphocyte ratio (PLR) with SII. When analyzing the routine laboratory parameters in the subgroups of comorbidities, the risk of death was associated with a common set of laboratory markers of systemic inflammation. Our results have shown that a panel of several routine laboratory parameters recorded on admission could be helpful for early evaluation of the risk of disease severity and mortality in COVID-19 patients. Inflammatory markers for mortality risk were similar in the subgroups of comorbidities, suggesting the limited effect of confounding factors in predicting COVID-19 mortality at admission.

Comorbidities and clinical complications associated with SARS-CoV-2 infection: an overview

The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes major challenges to the healthcare system. SARS-CoV-2 infection leads to millions of deaths worldwide and the mortality rate is found to be greatly associated with pre-existing clinical conditions. The existing dataset strongly suggests that cardiometabolic diseases including hypertension, coronary artery disease, diabetes and obesity serve as strong comorbidities in coronavirus disease (COVID-19). Studies have also shown the poor outcome of COVID-19 in patients associated with angiotensin-converting enzyme-2 polymorphism, cancer chemotherapy, chronic kidney disease, thyroid disorder, or coagulation dysfunction. A severe complication of COVID-19 is mostly seen in people with compromised medical history. SARS-CoV-2 appears to attack the respiratory system causing pneumonia, acute respiratory distress syndrome, which lead to induction of severe systemic inflammation, multi-organ dysfunction, and death mostly in the patients who are associated with pre-existing comorbidity factors. In this article, we highlighted the key comorbidities and a variety of clinical complications associated with COVID-19 for a better understanding of the etiopathogenesis of COVID-19.

Novel Insights into the Therapeutic Potential of Lung-Targeted Gene Transfer in the Most Common Respiratory Diseases

Over the past decades, a better understanding of the genetic and molecular alterations underlying several respiratory diseases has encouraged the development of new therapeutic strategies. Gene therapy offers new therapeutic alternatives for inherited and acquired diseases by delivering exogenous genetic materials into cells or tissues to restore physiological protein expression and/or activity. In this review, we review (1) different types of viral and non-viral vectors as well as gene-editing techniques; and (2) the application of gene therapy for the treatment of respiratory diseases and disorders, including pulmonary arterial hypertension, idiopathic pulmonary fibrosis, cystic fibrosis, asthma, alpha-1 antitrypsin deficiency, chronic obstructive pulmonary disease, non-small-cell lung cancer, and COVID-19. Further, we also provide specific examples of lung-targeted therapies and discuss the major limitations of gene therapy.

The impact of glucose tolerance state on seropositivity rate after hepatitis B vaccination

Immunization is recommended for people with diabetes mellitus (DM), but little information is available on their seropositivity rates. To determine the impact of glucose tolerance state on seropositivity rate after hepatitis B vaccination, we included 7645 adult participants from the National Health and Nutrition Examination Survey 2005-2016 who reported three doses of hepatitis B vaccine and were seropositive for anti-hepatitis B surface antibody (≥ 12.0 mIU/mL), after exclusion of those positive for anti-hepatitis B core antibody and/or hepatitis B surface antigen. We classified the states of glucose tolerance as normal glucose tolerance (NGT, 61.68%), abnormal glucose tolerance (AGT, 26.02%), or DM (13.30%). We observed a stepwise decline in hepatitis B seropositivity rate from NGT (53.64%) to AGT (45.52%) to DM (28.84%) (P < 0.0001). We confirmed these results after standardization for age and BMI (P < 0.0001 for all subgroup analyses) and in subgroup analyses by gender and racial/ethnic group. Dysregulated glucose metabolism is associated with a decreased seropositivity rate after hepatitis B vaccination. Our observations suggest that regular follow-up screening for anti-hepatitis B surface antibody, with additional booster vaccination as necessary, is especially important in patients with DM. Whether a similar phenomenon exits for other vaccines, especially COVID-19, remains to be investigated.

Comparative frequency and prognostic impact of myocardial injury in hospitalized patients with COVID-19 and Influenza

AIMS

Myocardial injury (MINJ) in Coronavirus disease 2019 (COVID-19) identifies individuals at high mortality risk but its clinical relevance is less well established for Influenza and no comparative analyses evaluating frequency and clinical implications of MINJ among hospitalized patients with Influenza or COVID-19 are available.

METHODS AND RESULTS

Hospitalized adults with laboratory confirmed Influenza A or B or COVID-19 underwent highly sensitive cardiac T Troponin (hs-cTnT) measurement at admission in four regional hospitals in Canton Ticino, Switzerland. MINJ was defined as hs-cTnT >14 ng/L. Clinical, laboratory and outcome data were retrospectively collected. The primary outcome was mortality up to 28 days. Cox regression models were used to assess correlations between admission diagnosis, MINJ, and mortality. Clinical correlates of MINJ in both viral diseases were also identified. MINJ occurred in 94 (65.5%) out of 145 patients hospitalized for Influenza and 216 (47.8%) out of 452 patients hospitalized for COVID-19. Advanced age and renal impairment were factors associated with MINJ in both diseases. At 28 days, 7 (4.8%) deaths occurred among Influenza and 76 deaths (16.8%) among COVID-19 patients with a hazard ratio (HR) of 3.69 [95% confidence interval (CI) 1.70-8.00]. Adjusted Cox regression models showed admission diagnosis of COVID-19 [HR 6.41 (95% CI 4.05-10.14)] and MINJ [HR 8.01 (95% CI 4.64-13.82)] to be associated with mortality.

CONCLUSIONS

Myocardial injury is frequent among both viral diseases and increases the risk of death in both COVID-19 and Influenza. The absolute risk of death is considerably higher in patients admitted for COVID-19 when compared with Influenza.

The Effects of Previous Thyroid Disease on the Susceptibility to, Morbidity of, and Mortality Due to COVID-19: A Nationwide Cohort Study in South Korea

This study aimed to investigate the associations of the susceptibility to, morbidity of, and mortality due to coronavirus disease 2019 (COVID-19) with thyroid diseases. Korea National Health Insurance Database Coronavirus disease 2019 (NHID-COVID-19) medical claim code data from 2015 to 2020 were analyzed. A total of 8070 COVID-19 patients and 32,280 matched control participants were evaluated for histories of hypothyroidism, hyperthyroidism, Graves’ disease, thyroiditis, and autoimmune thyroiditis. The relationships of susceptibility to, morbidity of, and mortality due to COVID-19 with hypothyroidism, hyperthyroidism, Graves’ disease, thyroiditis, and autoimmune thyroiditis were analyzed using a conditional logistic regression. Hypothyroidism, hyperthyroidism, Graves’ disease, thyroiditis, and autoimmune thyroiditis were not associated with susceptibility to, morbidity of, or mortality due to COVID-19. Graves’ disease was related to higher odds of mortality due to COVID-19 in the adjusted model but the confidence interval (CI) was wide, probably due to the small number of deaths among patients with Graves’ disease (aOR = 11.43, 95% CI = 1.29–101.22, p = 0.029). Previous histories of hypothyroidism, hyperthyroidism, Graves’ disease, thyroiditis, and autoimmune thyroiditis were not related to susceptibility to COVID-19. In addition, prior histories of thyroid diseases were not related to increased risks of COVID-19-related morbidity and mortality.