Intensive Care Unit Admission, Mechanical Ventilation, and Mortality Among Patients With Type 1 Diabetes Hospitalized for COVID-19 in the U.S

Impact of Charlson Comorbidity Index on in-hospital mortality of patients with hyperglycemic crises: A propensity score matching analysis

AIM

This study was designed to investigate the association between Charlson Comorbidity Index (CCI) and in-hospital mortality and other clinical outcomes among patients with hyperglycemic crises.

METHOD

This retrospective cohort study was conducted using data from electric medical records. A total of 1668 diabetic patients with hyperglycemic crises from six tertiary hospitals met the inclusion criteria. CCI < 4 was defined as low CCI and CCI ≥ 4 was defined as high CCI. Propensity score matching (PSM) with the 1:1 nearest neighbour matching method and the caliper value of 0.02 was used to match the baseline characteristics of patients with high CCI and low CCI to reduce the confounding bias. In-hospital mortality, ICU admission, hypoglycemia, hypokalemia, acute kidney injury, length of stay (LOS), and hospitalisation expense between low CCI and high CCI were compared and assessed. Univariate and multivariate regression were applied to estimate the impact of CCI on in-hospital and other clinical outcomes.

OUTCOME

One hundred twenty-one hyperglycemic crisis (HC) patients died with a mortality rate of 7.3%. After PSM, compared with low CCI, patients with high CCI suffered higher in-hospital mortality, ICU admission, LOS, and hospitalisation expenses. After multivariate regression, age (aOR: 1.12, 95% confidence interval [CI]: 1.06-1.18, p < 0.001), CCI(aOR: 4.42, 95% CI: 1.56-12.53, p = 0.005), uninsured (aOR: 22.32, 95% CI: 4.26-116.94, p < 0.001), shock (aOR: 10.57, 95% CI: 1.41-79.09, p = 0.022), mechanical ventilation (aOR: 75.29, 95% CI: 12.37-458.28, p < 0.001), and hypertension (aOR: 4.34, 95% CI: 1.37-13.82, p = 0.013) were independent risk factors of in-hospital mortality of HC patients. Besides, high CCI was an independent risk factor for higher ICU Admission (aOR: 5.91, 95% CI: 2.31-15.08, p < 0.001), hypoglycemia (aOR: 2.19, 95% CI:1.01-4.08, p = 0.049), longer LOS (aOR: 1.23, 95% CI: 1.19-2.27, p = 0.021), and higher hospitalisation expense (aOR: 2089.97, 95% CI: 193.33-3988.61, p = 0.031) of HC patients.

CONCLUSION

CCI is associated with in-hospital mortality, ICU admission, hypoglycemia, LOS, and hospitalisation expense of HC patients. CCI could be an ideal indicator to identify, monitor, and manage chronic comorbidities among HC patients.

Impact of diabetes on COVID-19 patient health outcomes in a vulnerable racial minority community

BACKGROUND

Diabetes is a growing health concern in the United States and especially New York City. New York City subsequently became an epicenter for the coronavirus pandemic in the Spring of 2020. Previous studies suggest that diabetes is a risk factor for adverse outcomes in COVID-19.

OBJECTIVE

To investigate the association between diabetes and COVID-19 outcomes as well as assess other covariates that may impact health outcomes.

DESIGN

Retrospective cohort study of COVID-19 hospitalized patients from March to May, 2020.

PARTICIPANTS

In total, 1805 patients were tested for COVID-19 and 778 tested positive for COVID-19. Patients were categorized into 2 groups: diabetes (measured by an Hba1c >6.5 or had a history of diabetes) and those without diabetes.

RESULTS

After controlling for other comorbidities, diabetes was associated with increased risk of mortality (aRR = 1.28, 95% CI 1.03-1.57, p = 0.0231) and discharge to tertiary care centers (aRR = 1.69, 95% CI 1.04-2.77, p = 0.036). compared to non-diabetes. Age and coronary artery disease (CAD) increased the risk of mortality among diabetic patients compared to patients with diabetes alone without CAD or advanced age. The diabetes cohort had more patients with resolving acute respiratory failure (62.2%), acute kidney injury secondary to COVID-19 (49.0%) and sepsis secondary to COVID-19 (30.1%).

CONCLUSION

This investigation found that COVID-19 patients with diabetes had increased mortality, multiple complications at discharge, and increased rates of admission to a tertiary care center than those without diabetes suggesting a more severe and complicated disease course that required additional services at time of discharge.

Development and validation of a prediction model for mechanical ventilation based on comorbidities in hospitalized patients with COVID-19

Background

Timely recognition of respiratory failure and the need for mechanical ventilation is crucial in managing patients with coronavirus disease 2019 (COVID-19) and reducing hospital mortality rate. A risk stratification tool could assist to avoid clinical deterioration of patients with COVID-19 and optimize allocation of scarce resources. Therefore, we aimed to develop a prediction model for early identification of patients with COVID-19 who may require mechanical ventilation.

Methods

We included patients with COVID-19 hospitalized in United States. Demographic and clinical data were extracted from the records of the Healthcare Cost and Utilization Project State Inpatient Database in 2020. Model construction involved the use of the least absolute shrinkage and selection operator and multivariable logistic regression. The model's performance was evaluated based on discrimination, calibration, and clinical utility.

Results

The training set comprised 73,957 patients (5,971 requiring mechanical ventilation), whereas the validation set included 10,428 (887 requiring mechanical ventilation). The prediction model incorporating age, sex, and 11 other comorbidities (deficiency anemias, congestive heart failure, coagulopathy, dementia, diabetes with chronic complications, complicated hypertension, neurological disorders unaffecting movement, obesity, pulmonary circulation disease, severe renal failure, and weight loss) demonstrated moderate discrimination (area under the curve, 0.715; 95% confidence interval, 0.709-0.722), good calibration (Brier score = 0.070, slope = 1, intercept = 0) and a clinical net benefit with a threshold probability ranged from 2 to 34% in the training set. Similar model's performances were observed in the validation set.

Conclusion

A robust prognostic model utilizing readily available predictors at hospital admission was developed for the early identification of patients with COVID-19 who may require mechanical ventilation. Application of this model could support clinical decision-making to optimize patient management and resource allocation.

Causal associations between type 1 diabetes and COVID-19 infection and prognosis: a two-sample Mendelian randomization study

INTRODUCTION

It has been suggested that type 1 diabetes was associated with increased COVID-19 morbidity and mortality. However, their causal relationship is still unclear. Herein, we performed a two-sample Mendelian randomization (MR) to investigate the causal effect of type 1 diabetes on COVID-19 infection and prognosis.

RESEARCH DESIGN AND METHODS

The summary statistics of type 1 diabetes were obtained from two published genome-wide association studies of European population, one as a discovery sample including 15 573 cases and 158 408 controls, and the other data as a replication sample consisting of 5913 cases and 8828 controls. We first performed a two-sample MR analysis to evaluate the causal effect of type 1 diabetes on COVID-19 infection and prognosis. Then, reverse MR analysis was conducted to determine whether reverse causality exists.

RESULTS

MR analysis results showed that the genetically predicted type 1 diabetes was associated with higher risk of severe COVID-19 (OR=1.073, 95% CI: 1.034 to 1.114, p_FDR=1.15×10^-3) and COVID-19 death (OR=1.075, 95% CI: 1.033 to 1.119, p_FDR=1.15×10^-3). Analysis of replication dataset showed similar results, namely a positive association between type 1 diabetes and severe COVID-19 (OR=1.055, 95% CI: 1.029 to 1.081, p_FDR=1.59×10^-4), and a positively correlated association with COVID-19 death (OR=1.053, 95% CI: 1.026 to 1.081, p_FDR=3.50×10^-4). No causal association was observed between type 1 diabetes and COVID-19 positive, hospitalized COVID-19, the time to the end of COVID-19 symptoms in the colchicine treatment group and placebo treatment group. Reverse MR analysis showed no reverse causality.

CONCLUSIONS

Type 1 diabetes had a causal effect on severe COVID-19 and death after COVID-19 infection. Further mechanistic studies are needed to explore the relationship between type 1 diabetes and COVID-19 infection and prognosis.

Influence of Age on Hyperoxia-Induced Cardiac Pathophysiology in Type 1 Diabetes Mellitus (T1DM) Mouse Model

Mechanical ventilation often results in hyperoxia, a condition characterized by excess SpO2 levels (>96%). Hyperoxia results in changes in the physiological parameters, severe cardiac remodeling, arrhythmia development, and alteration of cardiac ion channels, all of which can point toward a gradual increase in the risk of developing cardiovascular disease (CVD). This study extends the analysis of our prior work in young Akita mice, which demonstrated that exposure to hyperoxia worsens cardiac outcomes in a type 1 diabetic murine model as compared to wild-type (WT) mice. Age is an independent risk factor, and when present with a major comorbidity, such as type 1 diabetes (T1D), it can further exacerbate cardiac outcomes. Thus, this research subjected aged T1D Akita mice to clinical hyperoxia and analyzed the cardiac outcomes. Overall, aged Akita mice (60 to 68 weeks) had preexisting cardiac challenges compared to young Akita mice. Aged mice were overweight, had an increased cardiac cross-sectional area, and showed prolonged QTc and JT intervals, which are proposed as major risk factors for CVD like intraventricular arrhythmias. Additionally, exposure to hyperoxia resulted in severe cardiac remodeling and a decrease in Kv 4.2 and KChIP2 cardiac potassium channels in these rodents. Based on sex-specific differences, aged male Akita mice had a higher risk of poor cardiac outcomes than aged females. Aged male Akita mice had prolonged RR, QTc, and JT intervals even at baseline normoxic exposure. Moreover, they were not protected against hyperoxic stress through adaptive cardiac hypertrophy, which, at least to some extent, is due to reduced cardiac androgen receptors. This study in aged Akita mice aims to draw attention to the clinically important yet understudied subject of the effect of hyperoxia on cardiac parameters in the presence of preexisting comorbidities. The findings would help revise the provision of care for older T1D patients admitted to ICUs.

Severe COVID-19 Infection in Type 1 and Type 2 Diabetes During the First Three Waves in Sweden

OBJECTIVE

Type 2 diabetes is an established risk factor for hospitalization and death in COVID-19 infection, while findings with respect to type 1 diabetes have been diverging.

RESEARCH DESIGN AND METHODS

Using nationwide health registries, we identified all patients aged ≥18 years with type 1 and type 2 diabetes in Sweden. Odds ratios (ORs) describe the general and age-specific risk of being hospitalized, need for intensive care, or dying, adjusted for age, socioeconomic factors, and coexisting conditions, compared with individuals without diabetes. Machine learning models were used to find predictors of outcomes among individuals with diabetes positive for COVID-19.

RESULTS

Until 30 June 2021, we identified 365 (0.71%) and 11,684 (2.31%) hospitalizations in 51,402 and 504,337 patients with type 1 and 2 diabetes, respectively, with 67 (0.13%) and 2,848 (0.56%) requiring intensive care unit (ICU) care and 68 (0.13%) and 4,020 (0.80%) dying (vs 7,824,181 individuals without diabetes [41,810 hospitalizations (0.53%), 8,753 (0.11%) needing ICU care, and 10,160 (0.13%) deaths). Although those with type 1 diabetes had moderately raised odds of being hospitalized (multiple-adjusted OR 1.38 [95% CI 1.24-1.53]), there was no independent effect on ICU care or death (OR of 1.21 [95% CI 0.94-1.52] and 1.13 [95% CI 0.88-1.48], respectively). Age and socioeconomic factors were the dominating features for predicting hospitalization and death in both types of diabetes.

CONCLUSIONS

Type 2 diabetes was associated with increased odds for all outcomes, whereas patients with type 1 diabetes had moderately increased odds of hospitalization but not ICU care and death.

A confirmed COVID-19 in a patient with newly diagnosed hypertension and preexisting type 2 diabetes mellitus: a case report

Coronavirus disease 2019 (COVID-19) aggravates preexisting diabetes mellitus and contributes to newly discovered hypertension by increasing blood pressure by inhibiting the activity of angiotensin-converting enzyme 2 in the rennin-angiotensin system. Diabetes patients may be more vulnerable to COVID-19 due to chronic comorbidities such as obesity and cardiovascular disease such as hypertension.

Case presentation

On 23 March 2022, a retired black African woman in her 60s was taken into the emergency room with the chief complaints of frequent midnight urine, hazy vision, headache, fever, and tingling in her hands and feet. A throat swab PCR test that revealed positive results after 28 h was used to confirm COVID-19. Her electrocardiogram showed sinus tachycardia with a heart rate of 105 beats per minute. Fluid resuscitation (0.9% normal saline) of 1000 ml and drip insulin administration commenced as soon as she was brought to an ICU.

Clinical discussion

In this case report, the patient had been previously diagnosed with type 2 diabetes mellitus. COVID-19 affects the beta cells, forcing them to release insulin and increasing insulin insufficiency, which leads to her blood glucose raising. Type 2 diabetes mellitus is therefore the most frequent comorbidity of COVID-19 in this case report.

Conclusion

Poor blood glucose management in the case of COVID-19 may increase the pathogen's susceptibility, the likelihood that patients will be admitted to the hospital, and the likelihood that mortality will be enhanced.

Multiple BCG vaccinations for the prevention of COVID-19 and other infectious diseases in type 1 diabetes

There is a need for safe and effective platform vaccines to protect against coronavirus disease 2019 (COVID-19) and other infectious diseases. In this randomized, double-blinded, placebo-controlled phase 2/3 trial, we evaluate the safety and efficacy of a multi-dose Bacillus Calmette-Guérin (BCG) vaccine for the prevention of COVID-19 and other infectious disease in a COVID-19-unvaccinated, at-risk-community-based cohort. The at-risk population is made of up of adults with type 1 diabetes. We enrolled 144 subjects and randomized 96 to BCG and 48 to placebo. There were no dropouts over the 15-month trial. A cumulative incidence of 12.5% of placebo-treated and 1% of BCG-treated participants meets criteria for confirmed COVID-19, yielding an efficacy of 92%. The BCG group also displayed fewer infectious disease symptoms and lesser severity and fewer infectious disease events per patient, including COVID-19. There were no BCG-related systemic adverse events. BCG's broad-based infection protection suggests that it may provide platform protection against new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and other pathogens.

Symptoms and Glycemic Control in Young People With Type 1 Diabetes Following SARS-CoV-2 Infection: An Observational Study

CONTEXT

Data is needed regarding the effect of SARS-CoV-19 infection on young people with established type 1 diabetes. Identifying the disease outcomes, short and long-term sequelae may help to establish an evidence-based prevention and education policy for sick days management and DKA prevention.

OBJECTIVE

This work aims to describe clinical manifestations of SARS-CoV-2 infection in children, adolescents, and young adults with established type 1 diabetes (T1D) and explore the effects of COVID-19 on glycemic control and disease course.

METHODS

An observational study was conducted at 3 pediatric diabetes clinics in Israel between mid-March 2020 and mid-March 2021. Included were young people with established T1D, age younger than 30 years, who tested positive for SARS-CoV-2 (quantitative real-time polymerase chain reaction). Data were collected from medical files, diabetes devices, and COVID-19 questionnaire. Outcome measures were analyzed by the presence/absence of clinical symptoms (symptomatic/asymptomatic) and by age group (pediatric, < 19 years/young adults, 19-30 years).

RESULTS

Of 132 patients, mean age 16.9 ± 5.3years, with COVID-19-confirmed infection, 103 (78%) had related symptoms; the most common were headaches, fatigue, fever, and loss of sense of smell. All had a mild disease course, but 4 required hospitalization and 2 cases were directly related to COVID-19 infection (pleuropneumonia in a patient with immunodeficiency syndrome, 1 case of diabetic ketoacidosis). Logistic regression analysis showed that age (odds ratio [OR] = 1.11; 95% CI, 1.01-1.23; P = .033), elevated glucose levels (OR = 5.23; 95% CI, 1.12-24.41; P = .035), and comorbidities (OR = 8.21; 95% CI, 1.00-67.51; P = .050) were positively associated with symptomatic infection. Persistent symptoms occurred in 16.5% of the cohort over a median of 6.7 months; age (OR = 1.14; 95% CI, 1.01-1.29; P = .030) and elevated glucose levels (OR = 3.42; 95% CI, 1.12-10.40; P = .031) were positively associated with persistent symptoms. Usually, no change was reported in glucose levels (64%) except for a temporary deterioration in glycemic control during the short infection period.

CONCLUSION

Young people with established T1D experience mild COVID-19 infection. Elevated glucose levels during COVID-19 infection and older age were associated with prolonged disease course.

Trends in Type 1 Diabetic Ketoacidosis During COVID-19 Surges at 7 US Centers: Highest Burden on non-Hispanic Black Patients

CONTEXT

The impact of the COVID-19 pandemic on individuals with type 1 diabetes remains poorly defined.

OBJECTIVE

We examined United States trends in diabetic ketoacidosis (DKA) among individuals with type 1 diabetes (T1D) during the COVID-19 pandemic at 7 large US medical centers and factors associated with these trends.

METHODS

We compared DKA events among children and adults with T1D during COVID-19 surge 1 (March-May 2020) and COVID-19 surge 2 (August-October 2020) to the same periods in 2019. Analysis was performed using descriptive statistics and chi-square tests.

RESULTS

We found no difference in the absolute number of T1D patients experiencing DKA in 2019 vs 2020. However, a higher proportion of non-Hispanic Black (NHB) individuals experienced DKA in 2019 than non-Hispanic White (NHW) individuals (44.6% vs 16.0%; P < .001), and this disparity persisted during the COVID-19 pandemic (48.6% vs 18.6%; P < .001). DKA was less common among patients on continuous glucose monitor (CGM) or insulin pump in 2020 compared to 2019 (CGM: 13.2% vs 15.0%, P < .001; insulin pump: 8.0% vs 10.6%, P < .001). In contrast to annual DKA totals, a higher proportion of patients had DKA during COVID-19 surges 1 and 2 compared to the same months in 2019 (surge 1: 7.1% vs 5.4%, P < .001; surge 2: 6.6% vs 5.7%, P = .001).

CONCLUSION

DKA frequency increased among T1D patients during COVID-19 surges with highest frequency among NHB patients. DKA was less common among patients using CGM or insulin pumps. These findings highlight the urgent need for improved strategies to prevent DKA among patients with T1D-not only under pandemic conditions, but under all conditions-especially among populations most affected by health inequities.

Effects of Sodium Thiosulfate During Resuscitation From Trauma-and-Hemorrhage in Cystathionine-γ-Lyase Knockout Mice With Diabetes Type 1

Background

Sodium thiosulfate (STS) is a recognized drug with antioxidant and H2S releasing properties. We recently showed that STS attenuated organ dysfunction and injury during resuscitation from trauma-and-hemorrhage in CSE-ko mice, confirming its previously described organ-protective and anti-inflammatory properties. The role of H2S in diabetes mellitus type 1 (DMT1) is controversial: genetic DMT1 impairs H2S biosynthesis, which has been referred to contribute to endothelial dysfunction and cardiomyopathy. In contrast, development and severity of hyperglycemia in streptozotocin(STZ)-induced DMT1 was attenuated in CSE-ko mice. Therefore, we tested the hypothesis whether STS would also exert organ-protective effects in CSE-ko mice with STZ-induced DMT1, similar to our findings in animals without underlying co-morbidity.

Methods

Under short-term anesthesia with sevoflurane and analgesia with buprenorphine CSE-ko mice underwent DMT1-induction by single STZ injection (100 μg⋅g-1). Seven days later, animals underwent blast wave-induced blunt chest trauma and surgical instrumentation followed by 1 h of hemorrhagic shock (MAP 35 ± 5 mmHg). Resuscitation comprised re-transfusion of shed blood, lung-protective mechanical ventilation, fluid resuscitation and continuous i.v. norepinephrine together with either i.v. STS (0.45 mg⋅g-1) or vehicle (n = 9 in each group). Lung mechanics, hemodynamics, gas exchange, acid-base status, stable isotope-based metabolism, and visceral organ function were assessed. Blood and organs were collected for analysis of cytokines, chemokines, and immunoblotting.

Results

Diabetes mellitus type 1 was associated with more severe circulatory shock when compared to our previous study using the same experimental design in CSE-ko mice without co-morbidity. STS did not exert any beneficial therapeutic effect. Most of the parameters measured of the inflammatory response nor the tissue expression of marker proteins of the stress response were affected either.

Conclusion

In contrast to our previous findings in CSE-ko mice without underlying co-morbidity, STS did not exert any beneficial therapeutic effect in mice with STZ-induced DMT1, possibly due to DMT1-related more severe circulatory shock. This result highlights the translational importance of both integrating standard ICU procedures and investigating underlying co-morbidity in animal models of shock research.

Evidence and Implications of the Affordable Care Act for Racial/Ethnic Disparities in Diabetes Health During and Beyond the Pandemic

Amid the global pandemic, it becomes more apparent that diabetes is a pressing health concern because racial/ethnic minorities with underlying diabetes conditions have been disproportionately affected. The study proposes a multiyear examination to document the role of the Affordable Care Act (ACA) in racial/ethnic disparities in diabetes health. Using the Behavioral Risk Factor Surveillance System from 2011 to 2019, the study with a pre-post design investigated changes in access to care and diabetes health among non-White minorities compared with Whites before and after the ACA by conducting multivariable linear regression, with state-fixed effects and robust standard errors. Compared with Whites, racial/ethnic minorities showed significant improvements in health insurance coverage, having a personal doctor, and not seeing a doctor because of cost. Blacks (3.2% points, P ≤ 0.000), Hispanics (1.6% points, P = 0.001), and "other" racial/ethnic group (1.5% points, P = 0.003) experienced a greater increase in diagnosed prediabetes than Whites, whereas no and small differences were found in diagnosed diabetes and obesity, respectively. The yearly comparisons of changes in diagnosed prediabetes showed that Blacks compared with Whites had a growing increase from 1.2% points (P = 0.001) in 2014 to 3.3% points (P = 0.001) in 2019. Insurance coverage has declined after 2016, and obesity had an increasing trend across race/ethnicity. The ACA had a positive role in improving access to care and identifying those at risk for diabetes to a larger extent among racial/ethnic minorities. However, the policy impacts have been diminishing in recent years. Continued efforts are needed for sustained policy effects.