Impacts of COVID-19 on Glycemia and Risk of Diabetic Ketoacidosis.

Reports indicate that COVID-19 may impact pancreatic function and increase type 2 diabetes (T2D) risk, although real-world COVID-19 impacts on HbA1c and T2D are unknown. We tested whether COVID-19 increased HbA1c, risk of T2D, or diabetic ketoacidosis (DKA). We compared pre- and post-COVID-19 HbA1c, and T2D risk in a large real-world clinical cohort of 8,755 COVID-19(+) patients and 11,998 COVID-19(-) matched controls. We investigated if DKA risk was modified in COVID-19(+) patients with type 1 diabetes (T1D) (N=701) or T2D (N=21,830), or by race and sex. We observed a statistically significant, albeit clinically insignificant, HbA1c increase post-COVID-19 (all patients △HbA1c=0.06%; with T2D △HbA1c=0.1%), and no increase among COVID-19(-) patients. COVID-19(+) patients were 40% more likely to be diagnosed with T2D compared to COVID-19(-) patients and 28% more likely for the same HbA1c change as COVID-19(-) patients, indicating that COVID-19 attributed T2D risk may be due to increased recognition during COVID-19 management. DKA in COVID-19(+) patients with T1D was not increased. COVID-19(+) Black patients with T2D displayed disproportionately increased DKA risk (HR:2.46[1.48-6.09], P=0.004) compared to White patients, suggesting a need for further clinical awareness and investigation.

Impact of Telehealth on the Delivery of Prenatal Care During the COVID-19 Pandemic: Mixed Methods Study of the Barriers and Opportunities to Improve Health Care Communication in Discussions About Pregnancy and Prenatal Genetic Testing.

BACKGROUND: The COVID-19 pandemic brought significant changes in health care, specifically the accelerated use of telehealth. Given the unique aspects of prenatal care, it is important to understand the impact of telehealth on health care communication and quality, and patient satisfaction. This mixed methods study examined the challenges associated with the rapid and broad implementation of telehealth for prenatal care delivery during the pandemic. OBJECTIVE: In this study, we examined patients' perspectives, preferences, and experiences during the COVID-19 pandemic, with the aim of supporting the development of successful models to serve the needs of pregnant patients, obstetric providers, and health care systems during this time. METHODS: Pregnant patients who received outpatient prenatal care in Cleveland, Ohio participated in in-depth interviews and completed the Coronavirus Perinatal Experiences-Impact Survey (COPE-IS) between January and December 2021. Transcripts were coded using NVivo 12, and qualitative analysis was used, an approach consistent with the grounded theory. Quantitative data were summarized and integrated during analysis. RESULTS: Thematic saturation was achieved with 60 interviews. We learned that 58% (35/60) of women had telehealth experience prior to their current pregnancy. However, only 8% (5/60) of women had used both in-person and virtual visits during this pregnancy, while the majority (54/60, 90%) of women participated in only in-person visits. Among 59 women who responded to the COPE-IS, 59 (100%) felt very well supported by their provider, 31 (53%) were moderately to highly concerned about their child's health, and 17 (29%) reported that the single greatest stress of COVID-19 was its impact on their child. Lead themes focused on establishing patient-provider relationships that supported shared decision-making, accessing the information needed for shared decision-making, and using technology effectively to foster discussions during the COVID-19 pandemic. Key findings indicated that participants felt in-person visits were more personal, established greater rapport, and built better trust in the patient-provider relationship as compared to telehealth visits. Further, participants felt they could achieve a greater dialogue and ask more questions regarding time-sensitive information, including prenatal genetic testing information, through an in-person visit. Finally, privacy concerns arose if prenatal genetic testing or general pregnancy conversations were to take place outside of the health care facility. CONCLUSIONS: While telehealth was recognized as an option to ensure timely access to prenatal care during the COVID-19 pandemic, it also came with multiple challenges for the patient-provider relationship. These findings highlighted the barriers and opportunities to achieve effective and patient-centered communication with the continued integration of telehealth in prenatal care delivery. It is important to address the unique needs of this population during the pandemic and as health care increasingly adopts a telehealth model.

COVID-19 Home Monitoring After Diagnosis and Health Care Utilization in an Integrated Health System.

This cohort study examines health care utilization patterns for patients with COVID-19 who were enrolled vs not enrolled in a home monitoring program.

Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study.

BACKGROUND: Driven by quality outcomes and economic incentives, predicting 30-day hospital readmissions remains important for healthcare systems. The Cleveland Clinic Health System (CCHS) implemented an internally validated readmission risk score in the electronic medical record (EMR). OBJECTIVE: We evaluated the predictive accuracy of the readmission risk score across CCHS hospitals, across primary discharge diagnosis categories, between surgical/medical specialties, and by race and ethnicity. DESIGN: Retrospective cohort study. PARTICIPANTS: Adult patients discharged from a CCHS hospital April 2017-September 2020. MAIN MEASURES: Data was obtained from the CCHS EMR and billing databases. All patients discharged from a CCHS hospital were included except those from Oncology and Labor/Delivery, patients with hospice orders, or patients who died during admission. Discharges were categorized as surgical if from a surgical department or surgery was performed. Primary discharge diagnoses were classified per Agency for Healthcare Research and Quality Clinical Classifications Software Level 1 categories. Discrimination performance predicting 30-day readmission is reported using the c-statistic. RESULTS: The final cohort included 600,872 discharges from 11 Northeast Ohio and Florida CCHS hospitals. The readmission risk score for the cohort had a c-statistic of 0.6875 with consistent yearly performance. The c-statistic for hospital sites ranged from 0.6762, CI [0.6634, 0.6876], to 0.7023, CI [0.6903, 0.7132]. Medical and surgical discharges showed consistent performance with c-statistics of 0.6923, CI [0.6807, 0.7045], and 0.6802, CI [0.6681, 0.6925], respectively. Primary discharge diagnosis showed variation, with lower performance for congenital anomalies and neoplasms. COVID-19 had a c-statistic of 0.6387. Subgroup analyses showed c-statistics of > 0.65 across race and ethnicity categories. CONCLUSIONS: The CCHS readmission risk score showed good performance across diverse hospitals, across diagnosis categories, between surgical/medical specialties, and by patient race and ethnicity categories for 3 years after implementation, including during COVID-19. Evaluating clinical decision-making tools post-implementation is crucial to determine their continued relevance, identify opportunities to improve performance, and guide their appropriate use.

Metabolic Syndrome Is a Risk Factor for Hospitalization and Mortality from COVID-19 Independent of Other Comorbidities

Purpose: Characterize association between metabolic syndrome (MS) and COVID-19. Methods: This retrospective study included adult patients who tested for COVID-19 between March 8 and May 17, 2020. Demographics, labs, hospitalization, ICU admission, and mortality were analyzed with SAS. Groups were defined by MS according to NCEP/ATP criteria and serum AST:ALT, TG:HDL, and uric acid. Results: Of 23282 tested patients, 3679 (16%) were COVID-positive. MS was present in 834 (39%) of 2146 positive patients with available data. Patients with MS were older, male, Black, heavier, and had more comorbidities. MS was associated with higher rates of hospital admission and death (p<0.001). On multivariable analysis, patients with MS had increased risk of hospitalization (77%), ICU admission (57%) and death (81%) relative to those without MS (p<0.001). After adjusting for age, sex, race and comorbidities, MS remained a significant predictor of outcomes. AST:ALT>1 was a predictor of hospital and ICU admission, but not mortality. Higher TG:HDL ratio and uric acid were associated with worse outcomes, but were not independent predictors. Conclusion: MS is a significant predictor of hospital and ICU admission and mortality due to COVID-19, even after adjusting for other factors. Targeting modifiable components of MS including obesity, hyperglycemia, and hypertension may reduce mortality from COVID-19.

Impact of the COVID-19 Pandemic on Healthcare Workers' Risk of Infection and Outcomes in a Large, Integrated Health System.

BACKGROUND: Understanding the impact of the COVID-19 pandemic on healthcare workers (HCW) is crucial. OBJECTIVE: Utilizing a health system COVID-19 research registry, we assessed HCW risk for COVID-19 infection, hospitalization, and intensive care unit (ICU) admission. DESIGN: Retrospective cohort study with overlap propensity score weighting. PARTICIPANTS: Individuals tested for SARS-CoV-2 infection in a large academic healthcare system (N = 72,909) from March 8-June 9, 2020, stratified by HCW and patient-facing status. MAIN MEASURES: SARS-CoV-2 test result, hospitalization, and ICU admission for COVID-19 infection. KEY RESULTS: Of 72,909 individuals tested, 9.0% (551) of 6145 HCW tested positive for SARS-CoV-2 compared to 6.5% (4353) of 66,764 non-HCW. The HCW were younger than the non-HCW (median age 39.7 vs. 57.5, p < 0.001) with more females (proportion of males 21.5 vs. 44.9%, p < 0.001), higher reporting of COVID-19 exposure (72 vs. 17%, p < 0.001), and fewer comorbidities. However, the overlap propensity score weighted proportions were 8.9 vs. 7.7 for HCW vs. non-HCW having a positive test with weighted odds ratio (OR) 1.17, 95% confidence interval (CI) 0.99-1.38. Among those testing positive, weighted proportions for hospitalization were 7.4 vs. 15.9 for HCW vs. non-HCW with OR of 0.42 (CI 0.26-0.66) and for ICU admission: 2.2 vs. 4.5 for HCW vs. non-HCW with OR of 0.48 (CI 0.20-1.04). Those HCW identified as patient facing compared to not had increased odds of a positive SARS-CoV-2 test (OR 1.60, CI 1.08-2.39, proportions 8.6 vs. 5.5), but no statistically significant increase in hospitalization (OR 0.88, CI 0.20-3.66, proportions 10.2 vs. 11.4) and ICU admission (OR 0.34, CI 0.01-3.97, proportions 1.8 vs. 5.2). CONCLUSIONS: In a large healthcare system, HCW had similar odds for testing SARS-CoV-2 positive, but lower odds of hospitalization compared to non-HCW. Patient-facing HCW had higher odds of a positive test. These results are key to understanding HCW risk mitigation during the COVID-19 pandemic.