Association between Covid-19 and Diabetes Mellitus

Aim: To determine the association between Covid-19 and diabetes mellitus. Study Design: Retrospective study. Place and Duration of Study: Department of Medicine & Respiratory Physiology, Independent Medical College Faisalabad from 1st July 2022 to 31st December 2022. Methodology: Fifty five patients received at outdoor patient department of Independent University Hospital with confirmed diagnosis for Covid-19 through naso-pharyngeal reverse transcription polymerase chain reaction (RT-PCR) and aged 13-65 years were included. The complete medical files of each confirmed Covid-19 case was completely studied in relevance to diabetes mellitus association and compared with normal matched controls that only visited the OPD against the suspicion of the disease and underwent complete biochemical profiling. The baseline levels of HbA1C and glucose monitoring in each patient and control was done and compared. Result(s): The mean age of the CoVid-19 cases was 39.5+/-5.3 years while of controls as 25.65+/-4.3 years. There was an obvious significant variance in the odds ratio of Covid-19 patients and those of controls in reference to diabetes mellitus. A significant increase was observed in Odds Ratio of Covid-19 cases within the age group of 51-65 years. The Elixhauser Comorbidity Index (ECI) categories also presented, ECI >5 to be higher in Covid-19 cases than controls. Conclusion(s): There is a higher risk of diabetes new onset in Covid-19 confirmed cases as compared to matched controls.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Presentation Traits Of Vaccinated Versus Unvaccinated Heart Failure Patients At Acute Covid-19 Hospitalization

Introduction: Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) exhibits 25-30% mortality in hospitalized patients with heart failure (HF). Cardiovascular disease is the most significant comorbidity associated with increased mortality in COVID-19 patients with data suggesting local and systemic inflammation play a critical role in cardiac functional abnormalities. SARS-CoV-2 vaccination reportedly reduces severity of infection. We sought to characterize if vaccination had any protective effect on patients with HF hospitalized for acute COVID-19. Hypothesis: Baseline cardiac biomarkers including CRP, ferritin, high sensitivity cardiac troponin I (hs-cTnI), and pro-brain natriuretic peptide (pBNP) may be lower in vaccinated COVID-19 HF patients revealing the impact of vaccination on reducing inflammation by SARS-CoV-2 infection. Method(s): Electronic health records underwent IRB exempted extraction of demographics, anthropometrics, vital signs, laboratory tests, and ICD-10-CM-based Elixhauser comorbidity categories. Continuous data summarized with median [IQR] were compared using Kruskal-Wallis test and discrete data with chi-squared test. Result(s): Among HF patients with a recorded vaccine status admitted between July 3, 2021 and March 17, 2022, 206 underwent acute COVID-19 hospitalization. Vaccinated (n=91, 44%) and unvaccinated (115, 56%) patients exhibited statistically similar distribution of males (56%), aged 78[69-86] years with comorbidities 5[4-7] distributed across Whites (88%), Blacks (8%), and other races (4%). There were no intergroup differences with most prevalent comorbidities at admission including hypertension (99%), diabetes (41%), chronic pulmonary disease (37%), obesity (36%), deficiency anemia (31%), and renal failure (25%). There were no intergroup differences in initiation of COVID-19 directed treatments. Baseline biomarkers in vaccinated versus unvaccinated were CRP 6.0[1.3-9.5] vs. 6.9[2.7-11.3] mg/dL (p=.25), ferritin 171[76-552] vs. 432[79-876] ng/mL (p=.13), LDH 245[192-317] vs. 338[260-439] U/L (p=.003), D-dimer 0.89[0.53-1.73] vs. 1.36[0.95-2.80] mg/L FEU (p=.06), hs-cTnI 27[14-67] vs. 28[16-81] ng/L (p=.39), and pro-BNP 3487[1516-7162] vs. 3278[1549 vs. 9001] pg/mL (p=.90). Clinical visit criteria respectively were hospital LOS 4.9[2.9-10.3] vs. 5.4[3.4-10.3] days (p=.27), ICU admission 10% vs. 17% (p=.15), and discharge disposition expired or Hospice 15% vs. 16% (p=.48). Rehospitalization occurred similarly between groups and was not significant. Conclusion(s): Acute and chronic inflammation are pathogenic drivers of HF. Inflammatory biomarkers lower among vaccinated patients with HF included CRP, ferritin, D-dimer, and hs-cTnI, although not significant. LDH, however, was significantly lower suggesting improved host widespread tissue perfusion as one mechanism of reduced severity in patients with HF undergoing SARS-CoV-2 vaccine breakthrough infection. One study caveat is that despite inclusion of all patients, these preliminary findings are likely not sufficiently powered to validate our hypothesis.Copyright © 2022

Comorbidities Associated With Myocarditis In Hospitalized COVID-19 Patients

Introduction: While COVID-19 is predominantly a lung infection, it can cause systemic viremia in susceptible patients and lead to cardiac involvement and myocarditis (MC);an inflammation of the myocardium characterized by arrhythmias, cardiogenic shock, acute heart failure, and death. Although rare, there is evidence of a surge in MC-related admissions during the COVID-19 pandemic, implying a correlation. However, the risk factors associated with MC susceptibility in these patients remain unclear. This study aims to assess the comorbidities and demographic features associated with the development of MC in adult patients with COVID-19. Method(s): Data were obtained from the PearlDiver database (PearlDiver Technologies, Fort Wayne, IN). The database provides all-payers administrative claims data on the patient level. Using ICD-10-CM codes, a cohort of patients hospitalized with a primary diagnosis of COVID-19 was identified. The study included only patients admitted to the hospital between January and October 2020 to minimize bias associated with vaccine-related MC. Within this cohort, patients diagnosed with MC during and up to one month after admission were identified and their demographic features and comorbidities to were compared to those without MC. We calculated Risk Ratios with their respective 95% CI. A p-value <0.05 was deemed significant. Result(s): We found 627,465 admissions due to COVID-19 from January to October 2020, with 506 (0.08 %) diagnosis of MC. Patients with MC were more likely to be males (60%), younger (mean age 48, SD= 23 vs. 60, SD =17 - p<0.01), and they had more comorbidities (mean Elixhauser Comorbidity Index: 7.52, SD= 5 vs. 6.9, SD = 5 - p<0.001). The development of MC was significantly associated with a history of coagulopathies [0.55(0.46-0.66);p<0.0001], asthma [1.20 (1.06-1.23);p= 0.01], deep venous thrombosis [1.54(1.38-1.68);p<0.0001], renal disease[1.15 (1.02-1.27);p= 0.03], congestive heart failure [1.24 (1.12-1.34);p=0.006], ischemic heart disease [1.25 (1.14-1.35);p=0.0001], and arrhythmias [1.24 (1.14-1.32);p< 0.0001]. However, a history of diabetes [0.89 (0.67-0.99);p=0.02], hypertension [0.71 (0.62-0.80);<0.000.1], depression [0.71(0.52-0.88);p=0.0001], and hypothyroidism [0.42(0.08-0.69);p<0.0001] was associated with lower risk of MC-related hospitalization. Other preexistent conditions including, psychosis, rheumatoid arthritis, cerebrovascular disease, obesity, tobacco use, alcohol abuse, HIV, anemia, peripheral vascular disease, and non-metastatic solid tumor were not significantly correlated with MC. Discussion(s): MC is a rare yet serious complication of COVID-19. Therefore, a better knowledge of the pathophysiology of COVID-19 and the patient factors associated with development to MC is crucial for prognostication and providing risk-adjusted treatment. Conclusion(s): Patients with a history of cardiovascular disease, renal and pulmonary disease were more likely to develop MC as a result of COVID-19. However, hypertension and diabetes were associated with lower risk of MC, which warrants further investigation.Copyright © 2022

Myocarditis And COVID-19: An Analysis Of All Claims Administrative Data From Before And During The Pandemic

Background: Myocarditis (MC) is an inflammatory condition of the myocardium often caused by a virus and can lead to hospitalization, heart failure, or death. Although rare, data suggest an increased incidence associated with the COVID-19 virus. However, the risk for COVID-19-induced MC remains poorly understood and debated. We sought to evaluate the prevalence of pandemic MC-related inpatient encounters during 2020 through a descriptive approach and compare it to the pre-pandemic era. Given that the first COVID-19 vaccine doses were administered on December 14, 2020, a significant increase in MC prevalence could be attributable to COVID-19 exposure. Method(s): Data were obtained from the PearlDiver database (PearlDiver Technologies, Fort Wayne, IN). The database provides all-payers administrative claims data on the patient level. Using ICD-10-CM codes, a cohort of patients who had their first inpatient encounter with MC was identified and divided into pre-pandemic (January- October 2019) and pandemic (January-October 2020) groups and classified by age, gender, and month of hospitalization. We described these patients' demographics, calculated the prevalence ratio (PR) and 95% CI of MC-related encounters during the pandemic, and compared it with the same period in the pre-pandemic period. A p-value <0.05 was deemed significant. Result(s): The median age, length of stay in previous hospitalizations, mean gender and Elixhauser Comorbidity Index were similar between groups. The prevalence of MC was 22/100,000 cases in 2019 and 25/100,000 in 2020. The overall PR of hospitalization due to MC was 13% higher in 2020 than it was in 2019 (PR=1.13, p<0.0001), with a significantly higher risk in age groups 5-9 (PR=1.41 p=0.02), 60-64 (PR=1.24 p<0.0001), 65-69 (PR=1.14 p=0.01), 70-74 (PR=1.28 P<0.0001), and 80-85 (PR=1.36 p<0.0001). The risk was significantly higher in March (PR=1.27 p<0.0001), July (PR=1.41 p<0.0001, and September (PR=1.52 p<0.0001) in 2020. In 2020, the risk of MC in males with respect to females decreased by 3% compared to 2019. Discussion(s): Our results suggest a temporal correlation between increased prevalence of inpatient encounters for MC since COVID-19's inception. The risk was significantly higher in older adults and during months with a higher COVID-19 incidence. These findings do not demonstrate causation between the COVID-19 virus and MC and are limited by the typical biases associated with retrospective studies. Conclusion(s): Although MC is a less common hospitalization condition, our data supports a significantly increased prevalence of MC-related encounters during the initial year of the COVID-19 pandemic. We found risk variations according to age, gender, and month.Copyright © 2022

Multimorbidity Profile of COVID-19 Deaths in Portugal during 2020.

BACKGROUND: COVID-19 is caused by SARS-CoV-2 infection and has reached pandemic proportions. Since then, several clinical characteristics have been associated with poor outcomes. This study aimed to describe the morbidity profile of COVID-19 deaths in Portugal. METHODS: A study was performed including deaths certificated in Portugal with "COVID-19" (ICD-10: U07.1 or U07.2) coded as the underlying cause of death from the National e-Death Certificates Information System between 16 March and 31 December 2020. Comorbidities were derived from ICD-10 codes using the Charlson and Elixhauser indexes. The resident Portuguese population estimates for 2020 were used. RESULTS: The study included 6701 deaths (death rate: 65.1 deaths/100,000 inhabitants), predominantly males (72.1). The male-to-female mortality ratio was 1.1. The male-to-female mortality rate ratio was 1.2; however, within age groups, it varied 5.0-11.4-fold. COVID-19 deaths in Portugal during 2020 occurred mainly in individuals aged 80 years or older, predominantly in public healthcare institutions. Uncomplicated hypertension, uncomplicated diabetes mellitus, congestive heart failure, renal failure, cardiac arrhythmias, dementia, and cerebrovascular disease were observed among COVID-19 deceased patients, with prevalences higher than 10%. A high prevalence of zero morbidities was registered using both the Elixhauser and Charlson comorbidities lists (above 40.2%). Nevertheless, high multimorbidity was also identified at the time of COVID-19 death (about 36.5%). Higher multimorbidity levels were observed in men, increasing with age up to 80 years old. Zero-morbidity prevalence and high multimorbidity prevalences varied throughout the year 2020, seemingly more elevated in the mortality waves' peaks, suggesting variation according to the degree of disease incidence at a given period. CONCLUSIONS: This study provides detailed sociodemographic and clinical information on all certificated deaths from COVID-19 in Portugal during 2020, showing complex and extreme levels of morbidity (zero-morbidity vs. high multimorbidity) dynamics during the first year of the pandemic in Portugal.

Comorbidities Associated with All-Cause Readmission to the Same Hospital after Index COVID-19 Hospitalization: A Retrospective Cohort Study of 232155 Patients in the United States

Background. Understanding comorbidities that drive all-cause readmission in patients hospitalized with Coronavirus disease 2019 (COVID-19) can inform healthcare system capacity planning and improve post-discharge care. Methods. This was a retrospective cohort study of patients hospitalized for COVID-19 between April 2020-December 2020 (index cohort) across 760 hospitals in the Premier Healthcare Database. Patients who died or left against medical advice were excluded from the index cohort. Surviving patients in the index cohort were followed until May 2021. First readmission to the same hospital as the COVID-19 index admission was considered all-cause readmission. The all-cause 14-month risk (95% confidence interval) of readmission was calculated using the Kaplan-Meier approach. A multivariable Cox proportional hazards model adjusted for demographic variables, hospital characteristics, co-existing comorbidities, and COVID-19 severity was built to study the association between Elixhauser comorbidities and readmission. Results. Among 232155 unique patients in the index cohort, 36680 were readmitted to the same hospital at least once, followed through May 2021. The 14-month risk of readmission was 16.2% (95% CI:16.1% - 16.4%). The most frequent primary diagnosis on readmission was infectious disease (14240, 38.8%), of which 8754 (24%) were for COVID-19. With each additional comorbidity, the readmission hazard increased by 19% (HR, 1.19;95% CI:1.18 - 1.19). In the multivariable Cox proportional hazards model, many comorbidity categories were associated with an increased risk of readmission. Metastatic cancer (HR, 1.74;95% CI:1.60 -1.89), lymphoma (HR, 1.61;95% CI:1.47 - 1.77), drug abuse (HR, 1.51;95% CI:1.41 - 1.62), congestive heart failure (HR, 1.47;95% CI:1.44- 1.51), and alcohol abuse (HR, 1.46;95% CI:1.36- 1.56) were associated with the highest hazard for readmission. Conclusion. COVID-19 patients have a high risk of all-cause readmission and are frequently readmitted for COVID-19. With the continued emergence of COVID-19 variants, this study provides valuable insights into developing more informed discharge plans and improving post-discharge care for COVID-19 patients with existing comorbidities to prevent readmission.

Do Empiric Antibiotics Improve Outcomes in Clinically Stable Patients Admitted with COVID-19 Pneumonia? Retrospective Cohort Study of 221 U.S. Hospitals, March 1st, 2020-December 31st, 2020

Background. Patients admitted with COVID19 pneumonia often receive initial empiric antibacterial therapy (IEAT) despite a known low probability of bacterial co-infection. However, evidence supporting this practice is lacking. We studied the impact of IEAT on the risk of in-hospital mortality, clinical deterioration and antibiotic-associated risks in stable inpatients with COVID-19. Methods. Adult inpatients coded for COVID-19 pneumonia stable (no mechanical ventilation or vasopressors) on admission (+1 day) without a clear indication for antibiotics, were identified at hospitals in the Premier Healthcare Database. Patients who received IEAT, defined as the receipt of >= 1 antibacterial agent on admission (+1 day), were compared to a control group, using binomial regression with overlap weight matching and downstream adjustment for baseline characteristics (age, gender, race, admission month, surge index, Elixhauser score, any AOFS organ failure POA, ICU admission on day 0 to +2, receipt of remdesivir, corticosteroids, and tocilizumab). The primary outcome was in-hospital mortality or discharge to hospice;secondary outcomes included need for mechanical ventilation on day2+, and rates of non-POA-acute kidney injury (AKI). Results. At 221 hospitals between March-December 2020, 39,517 (74%) of 53,431 stable COVID-19 admits received IEAT. Patient and encounter characteristics are shown in Table 1. The crude mortality rates were 12.2% in IEAT recipients and 10.9% in controls. In adjusted analysis of patients who survived beyond admission day, mortality was 11.57% (95% CI 11.24-11.90%) in IEAT recipients and 11.23% (95% CI 10.72-11.74) in controls, for a difference of 0.34% (95% CI -0.23-0.91%, p = 0.24). Subsequent mechanical ventilation occurred similarly between groups (5.72% vs. 5.77%, p=0.83). The adjusted rate of AKI was 2.47% (95% CI 2.31-2.64%) in IEAT recipients, and 3.04% (95% CI 2.74-3.35%) in controls, for a difference of -0.57% (95% CI -0.92-0.22%, p = 0.0014). Conclusion. In patients with COVID19 initially admitted to the ward, IEAT was not associated with a reduction in mortality or deterioration requiring mechanical ventilation, but with a clinically insignificant reduction in AKI. Empiric antibiotics can likely be safely withheld in this population.

Changes in the management of myelopathy during the COVID- 19 pandemic in a nationwide hospital network in Germany

Introduction: The Covid-19 pandemic has negatively impacted the management of spinal pathologies. Since, so far, the pandemic's effects specifically on the management of myelopathy in Germany have not been examined, we aim to do so in this analysis. Method(s): We used administrative data from a nationwide Network of 76 hospitals for this retrospective analysis and compared the first 5 pandemic waves (Jan 1, 2020 - May 17, 2022) to corresponding periods from the last year prior to the pandemic (2019). We included all patients hospitalized with the main diagnosis "myelopathy" (ICD-10-Codes: M47.11-15, G95.2, G99.2) and examined baseline characteristics and rates of different treatment types and in-hospital mortality. Result(s): We included 4,167 cases with myelopathy: 2,001 hospitalized during the pandemic, and 2,166 in 2019. Compared to pre-pandemic levels, the mean daily admissions for myelopathy decreased only in wave 1 (from 2.8 auf 1.7;p<0.01), while no changes in admissions were registered in any of the later waves. There were no alterations in patient age (range: 64.5-66.1 years), distribution of sex (female, range: 39.3%-50.4%), or rates of comorbidities, measured by the Elixhauser Comorbidity Index (range: 4.3-6.5). In contrast, we observed significant changes in the analysis of treatment modalities. Except in wave 1, there was a significant increase in rates of spinal decompression procedures throughout the pandemic, from a range of 43.3-47.0% before the pandemic to 55.6%-62.5% (p<0.01). Also, compared to prepandemic levels, the rates of disc hernia resections increased during waves 4 and 5 from a range of 29.8-30.4% to 37.1-41.1% (p<0.01). Furthermore, the rates of spinal fusion procedures increased in waves 3, 4, and 5 from a range of 32.7-40.5% to 45.0- 50.4% (p<0.01). No changes were observed throughout the pandemic for rates of kyphoplasty (0.2-1.0%), transfer to intensive care unit (22.9-30.7%), and in-hospital mortality (1.1-2.7%). Discussion(s): We present the largest analysis, to date, on the effects of the COVID-19 pandemic on the management of myelopathy in Germany. Our findings suggest that, in subjects with myelopathy, the pandemic did not lead to a selection for older or sicker patients. The fact that hospital admissions for myelopathy dropped off only during the wave 1 suggests a certain normalization over time. This is why it is worth discussing why rates of surgery increased in later phases of the pandemic, both for fusion and non-fusion procedures.

Changes in frailty among patients with spinal pathologies during the first 5 waves of the COVID-19 pandemic in a nationwide hospital network in Germany

Introduction: In patients with degenerative spinal disease, higher degrees of fraily, as measured by the Hospital Frailty Risk Score (HFRS), are associated with poor treatment outcomes. The COVID-19 pandemic has led to significant increases in frailty among hospitalized patients. We present the first nationwide analysis of the impact the COVID-19 pandemic has been having on frailty among spine patients. Method(s): In this retrospective study we examined administrative data from a nationwide network of 76 hospitals in Germany with emphasis on HFRS, types of treatment and outcomes. We compared data from the last year prior to the pandemic (2019) to the first 5 waves of the pandemic (Jan 1, 2020 - May 17, 2022). All patients with a primary diagnosis of degenerative, traumatic or infectious spinal disease were included. The following HFRS groups were compared to each other: low (< 5 points), intermediate (5-15 points), and high (>15 points). Result(s): Of the 379,910 included cases with spine pathologies 168,481 were hospitalized during the pandemic, and 194,722 in 2019. Compared to pre-pandemic levels, hospital admissions for spinal pathologies decreased significantly during all 5 waves of the pandemic and the proportion of spine patients with high HFRS increased from a range of 5.8-6.1% to 6.5-8.8% (p<0.01). Analogously, during all 5 waves, there was a significant increase in patient age (from 65.3-65.5 years to 65.8-66.5 years;p<0.01). The rate of comorbidities increased significantly, as well, with a rise in the Elixhauser Comorbidity Index from a range of 4.2-4.3 to 4.7- 5.9 (p<0.01). Throughout the pandemic, there was a significant increase in the rate of spinal fusion procedures among patients with low HFRS (from a range of 6.4-6.8% to 8.4-10.3%;p<0.01), as well as in the intermediate HFRS group (from 5.8-6.0% to 6.9- 7.8%;p<0.01). No changes in rates were observed for decompressive spine procedures, disc hernia resections, or kyphoplasty. Throughout all 5 pandemic waves, patients of the high HFRS group displayed significantly higher in-hospital mortality rates (8.6-13.6%) compared to patients in the low HFRS group (0.1-0.4%;p<0.01). Discussion(s): We present the largest study, to date, on frailty among patients with spinal pathologies in Germany. Our findings suggest that the COVID-19 pandemic has led to decreased numbers of hospital admissions for spinal pathologies but increased frailty among those hospitalized. This type of "negative selection" may be due to younger and healthier spine patients avoiding hospitalization out of fear of hospital-acquired COVID-19 infection. Among hospitalized spine patients with low or intermediate levels of frailty, the rate of spinal fusion procedures increased during the pandemic, while rates of non-fusion procedures were not impacted.

Multiple sclerosis, rituximab, SARS-CoV-2 vaccination, and COVID-19 severity

Introduction: Rituximab (RTX) and other B-cell depleting therapies increase the risk of more severe COVID-19 among unvaccinated persons with multiple sclerosis (pwMS) and reduce humoral but not T-cell immune responses to SARS-CoV-2 vaccinations. Objective/Aims: To determine whether RTX increases the risk of hospitalization for COVID-19 compared to pwMS who were untreated or treated with disease-modifying therapies (DMTs) that do not reduce vaccine efficacy (interferon-betas, glatiramer acetate, natalizumab or dimethyl fumarate) and identify modifiable factors among RTX-treated pwMS (RTX-MS). Method(s): We conducted a retrospective cohort study in Kaiser Permanente Southern California from 1.1.2020 to 15.2.2022. Logistic regression models were adjusted for age, sex, race and ethnicity, Elixhauser comorbidly index and advanced MS-related disability (requiring a walker, wheelchair or worse). Analyses restricted to RTX-MS were additionally adjusted for cumulative dose, dose at last infusion and time since last infusion. Result(s): Among SARS-CoV-2 vaccinated pwMS, RTX-MS (n=1495) were more likely to be hospitalized (n=16) but not die (n=0) compared to the 2682 pwMS on no or other DMTs (no/other DMT, n=5 and n=0, respectively;adjusted odds ratio, AOR=6.27, 95% confidence interval CI=2.09-18.85). Receiving a SARSCoV2 vaccine type other than mRNA (AOR=5.06, p=0.001) and not receiving a booster vaccination (AOR=2.85, p=0.026) were independent predictors of COVID-19 severity. The absolute risk of hospitalization for COVID-19 was low in both groups (RTX-MS 1.4 per 100 person-years and 0.21 among no/other DMT). Among vaccinated RTX-MS, receiving the first vaccination dose more than 6 months after the last RTX infusion significantly reduced the risk of COVID-19 hospitalization (AOR=0.08, 95%CI=0.02-0.35) and advanced MS-related disability increased it (AOR=3.71, p=0.045). Unvaccinated RTX-MS (n=573) were at significantly higher risk of COVID hospitalization (n=30 including n=2 deaths) compared to vaccinated RTX-MS (AOR=5.56, p<0.0001). Conclusion(s): Rituximab-treated pwMS should be strongly encouraged to receive mRNA SARS-CoV-2 vaccination series and boosters, ideally >6 months since their last RTX infusion. While the absolute risk of severe COVID-19 is low among vaccinated RTX-MS, the odds of hospitalization is significantly higher compared to no/other DMT. The marginal benefits of B-cell depleting therapies in persons with advanced MS-related disability should be weighted against the additional increased risk of severe COVID in this group.

PRIMARY CARE REFERRAL PATTERNS FOR PATIENTS WITH URINARY INCONTINENCE IN AN ACADEMIC HEALTH SYSTEM FROM 2018-2020

Introduction: While an estimated 50% of adult women experience urinary incontinence (UI), the majority will never receive treatment. Most studies of incontinence care delivery have been limited to administrative (billing) data following treatment. Much less is known about earlier steps in evaluation, including primary care intentions to refer to specialty care. Objective: To better understand the gaps and barriers to receiving care, we examined referral patterns from primary care providers for patients with new diagnoses of urinary incontinence between 2018-2020 and the extent to which such referrals changed during the COVID-19 pandemic. Methods: Electronic health records (EHR) from 24 primary care practices within a single academic medical system were queried to identify a cohort of adult (18 - 90-year-old) female patients first diagnosed with urinary incontinence during primary care (family or general internal medicine) outpatient visits between January 2018 and December 2020. Demographics were determined from appropriate EHR fields, and diagnoses pulled from problem lists, past medical histories, and office visit diagnosis fields. EHR referral fields were utilized to ascertain referral dates, types, and associated diagnoses. Electronic prescription fields were used to record treatment information including medication class, name, and prescription dates. Subjects were excluded if there was EHR evidence of urinary tract infection at diagnosis, UI in the prior year based on diagnosis or medication usage (anticholinergic, B3 agonists), or presence of conditions for which incontinence management might differ substantially in the prior year (pregnancy, spinal cord injury). Referrals to specialty physicians (urology/urogynecology) and pelvic floor physical therapy (PFPT) were examined for the year after UI diagnosis. Logistic regression was then used to assess for associations between referrals and patient demographics, comorbidity, and diagnosis dates (pre-vs during-COVID-19). Results: The study identified 514 women with a newly diagnosed urinary incontinence diagnosis (Table 1). In the year following UI diagnosis, 31.91% were referred to specialty care for management -29.0% to urology/urogynecology and 3.5% to pelvic floor physical therapists. Women diagnosed with UI during the COVID-19 pandemic, starting January 2020, were less likely to be referred with an odds ratio of 0.29 (95% CI 0.19, 0.45) compared to those diagnosed before (Table 2). There was no association of referrals with patient age, race, or number of comorbidities (Elixhauser Comorbidity Index), but confidence intervals were wide. Patterns were similar for models that examined specialty physician or PFPT referral separately. Conclusions: Less than 1 in 3 women were referred to specialty care for UI by their primary care provider with less than 1 in 25 referred to PFPT. There was a significant decrease in likelihood of referrals during 2020 suggesting that the COVID-19 pandemic interfered with UI patients receiving quality care. Future studies aiming to improve incontinence care should examine other aspects of nonsurgical UI care delivery, including barriers to behavioral self-management, medication use, and completion of specialty referrals.

Application of Artificial Intelligence to Predict Survival in Patients With Chronic Kidney Disease (CKD) Stage 4-5

Patients with advanced chronic kidney disease (CKD) stage 4-5 face unknown progression rates to End Stage Renal Disease (ESRD) with elevated baseline mortality. Hemodialysis preparation requires surgical planning months in advance, and many patients may pass away before reaching ESRD. Improved understanding of survival probability in the near future could help physicians and patients in the shared decision making on the risks and benefits of dialysis vs conservative care. Patients from Kaiser Southern California Electronic Health Record (EHR) with CKD Stage 4-5 between 1/1/2010 – 12/31/2018 were selected for our initial training population. We picked an XGBoost model as it offered the best combination of accuracy and interpretability. Our features included aggregations of demographics, comorbidities calculated based on the Elixhauser comorbidity index, common labs, vitals, and past utilization data. On March 10, 2020, 16,267 current Stage 4-5 CKD patients at Kaiser Southern California were scored with the model . From March 11, 2020 to March 10, 2021, a 1-year prospective study was performed to assess the accuracy of the predictive model. At the conclusion of the 1-year observation, we assessed the model’s predictions against the actual survival data. The machine learning survival model achieved an AUC of .73 in the prospective study. We computed an optimal cut-point based on the probability prediction threshold that maximized the sum of sensitivity and specificity. At this level, the model achieved an accuracy of 70%, sensitivity of 63%, specificity of 72%, and precision of 25%, in predicting 12 month survival for individuals with advanced CKD stage 4-5. Despite unforeseen COVID-19 pandemic, our model achieved predictive accuracy for 1-year survival in CKD stage 4-5 patients prospectively. Machine learning based probabilistic forecasting can be used to better inform decisions regarding CKD management.

READMISSION RATES AMONG PATIENTS AMONG PATIENTS EXPERIENCING HOMELESSNESS IN AN INTEGRATED HEALTHCARE SYSTEM

BACKGROUND: Homelessness is a significant public health concern in the United States and is an important risk factor for poor health outcomes. There is limited data regarding the hospital utilization by this vulnerable population, especially inmanaged care settings. Historically, it has been difficult to identify patients experiencing homelessness at the population health level. In 2019, due to the passage of state law SB1152, hospitals across California now need standardized documentation policies for patients experiencing homelessness. This study assessed hospital readmission rates among hospitalized patients experiencing homelessness as identified through documentation in the electronic health record (EHR) as compared to the general hospitalized population within a large integrated health system. METHODS: This was a retrospective cohort study following adult patients (age≥18 years) hospitalized in Kaiser Permanente Northern California (KPNC) Medical Centers between 1/1/2019 through 12/1/2020. Patients were identified as homeless or housing insecure if they had SB1152 documentation, a homeless diagnosis code, or address history indicating homelessness within the extensive integrated KPNC EHR. A control group was created using 1:2 propensity score matching using Elixhauser comorbidities and demographics. Sensitivity analyses were performed to compare patients with an index hospitalization occurring during the COVID-19 shelter-in-place period between March 2020 and December 2020 with those whose index hospitalization occurred before this period. The primary outcome was 30-day readmission rate to the hospital or ED, and secondary outcomes included length of index hospitalization, and time to inpatient (IP) readmission. RESULTS: A total of 12,909 patients were included with 4,303 patients in the homeless group. Patients experiencing homelessness had increased odds for any 30-day readmission (OR 1.59;95% CI: 1.44-1.76), for inpatient readmission (OR 1.36;95% CI: 1.17-1.57), for ED readmission (OR 1.63;95% CI: 1.47-1.80), and had longer stays during their index hospitalization (IRR 1.12;95% CI: 1.04-1.21). The COVID-19 shelter-in-place period was not associated with any changes in the primary or secondary outcomes studied. CONCLUSIONS: Patients experiencing homelessness are at an increased risk for readmissions and longer hospitalizations compared to the general hospitalized population. Documentation of housing status following SB1152 has improved the ability to study hospital utilization among patients experiencing homelessness. Understanding patterns of hospital utilization in this vulnerable group will help providers to identify timely points of intervention for further social and healthcare support.

DOES ACCESS TO TELEHEALTH IN PRIMARY CARE AFFECT PRIMARY CARE UTILIZATION IN A LARGE, PUBLIC HEALTHCARE SYSTEM?

BACKGROUND: Telehealth services may improve access to care by removing certain barriers to care. But, health systems and payors may be hesitant to provide or cover telehealth at the same rate as in-person services in part due to concerns around potential to increase overall healthcare utilization. During the coronavirus disease pandemic, many regulatory restrictions on telehealth were paused, allowing more widespread usage of telehealth. We sought to investigate whether patients engaged in telehealth had increased primary care (PC) utilization relative to those not engaged in telehealth. METHODS: We conducted an observational study of electronic health record data for patients with PC visits from July 1, 2020 to June 30, 2021 at 23 adult PC clinics at New York City Health + Hospitals, the nation's largest public healthcare system. This period represents when local COVID cases were past initial peak and telehealth visits were available to patients electively instead of preferentially. The primary outcome was the average number of annual completed PC visits per patient. We collected patient age, sex, race/ethnicity, language, insurance, and number of Elixhauser comorbidities and compared them between groups using χ2 tests. Then, we stratified patients by quintiles of comorbidity count and compared the average number of completed PC visits per patient between telehealth users and non-users using two-sided Welch's ttests. RESULTS: There were 569,724 visits by 225,147 patients. Of these patients, 133,830 (59.4%) were telehealth users. Compared to telehealth non-users, telehealth users were more likely to be older, female, Asian, Medicare beneficiaries, and have more comorbidities and less likely to be Black, commercially insured, or uninsured (p<0.001). The average (SD) number of PC visits were 2.9 (1.7) for telehealth users and 1.9 (1.3) for non-users. Compared to telehealth non-users, telehealth users had 1more PC visit per patient regardless of comorbidity count (Table;p<0.001). Among telehealth users, the average proportion of visits that were conducted via telehealth was 0.68 (0.28). CONCLUSIONS: Availability of telehealth may increase PC utilization in safety-net clinics. Differences in utilization may relate to decreases in barriers to care, lower efficacy of telehealth, or differences in propensity to engage in care not accounted for by comorbidity count. More research on outcomes, costs of care, patient and clinician experiences is essential to better inform policymakers' and payors' decisions around coverage of telehealth services.

LONGITUDINAL CLINICAL TRAITS OF HEART FAILURE PATIENTS READMITTED POST COVID-19 INDEX HOSPITALIZATION

BACKGROUND: Severe acute respiratory syndrome-coronavirus-2 (SARSCoV- 2) has substantial morbidity and mortality in patients with heart failure (HF). Hospital mortality exceeds 30% in the American Heart Association's COVID-19 Cardiovascular Disease registry. We characterized clinical traits associated with progression to critical illness (PCI, ICU admission or hospital death) during index and subsequent hospitalizations in SARS-CoV-2 infected patients with extant HF. METHODS: Electronic health records underwent extraction of demographics, anthropometrics, vital signs, laboratory tests, and ICD-10-CM-based Elixhauser comorbidity categories. Univariate logistic regression was used to identify features associated with PCI. Continuous data summarized with median [IQR] were compared using Kruskal-Wallis test and discrete data with chi-squared test. Confounders statistically balanced included age, sex, race, COVID-19 directed treatment, and 4-waves of pandemic. RESULTS: Among HF patients admitted between March 14, 2020 and September 30, 2021, 530 underwent index COVID-19 hospitalization. Among those, 111 were readmitted once, and 43 readmitted at least twice. Index admission median age was 75 [65-84] years, body mass index (BMI) 29.5 [24.9-35.3], and time to readmission 247.7 [44.7-784.1] days. Subsequent time to readmission was 34.7 [5.7-92] days. Most common admission comorbidities were hypertension (81%), diabetes (43%), renal failure (42%), obesity (38%), chronic pulmonary disease (36%), and deficiency anemia (32%). The most common comorbidities at second readmission were renal failure (60%), deficiency anemia (53%), diabetes (40%), and chronic pulmonary disease (40%). PCI occurred in 32% of index admissions, 21% of first readmissions, and 14% of second readmissions. Hospital death or discharge to hospice occurred in 28%, 18%, and 23% of readmissions respectively. CONCLUSIONS: Days to readmission declined revealing impact of inflammation and immunomodulation caused by SARS-CoV-2. Although hypertension was the most common comorbidity at index admission it was the least common at subsequent readmissions. This may represent improved control or death of those poorly controlled. Renal failure being the most common comorbidity at second readmission may represent worsening function due to SARS-CoV-2 infection and injury or worsening HF syndrome. Progressively worsening pBNP and hsTnI likely reflect direct myocyte injury by heightened entry of SARS-CoV-2 viral particle due to expression of angiotensinconverting enzyme 2. HF patients should be urged to undergo SARS-CoV-2 vaccination with apropos boost.

Perioperative morbidity and readmission rate in all spine patients in the COVID era

Introduction: The coronavirus (COVID-19) pandemic has presented healthcare workers with one of the most significant global health crises to date. Prior studies have not identified an increase in complications or readmissions in COVID-19 negative patients undergoing emergency or essential surgery during the pandemic. Similar findings have been found in the urgent and elective surgery population. However, no study has shown the risks of all spine surgeries during this time period. Therefore, the purpose of this study is to measure the rates of complications and readmissions for all patients who underwent spine procedures (elective, urgent, and emergent) since the beginning of the COVID-19 pandemic compared to historical averages. Material and Methods: A retrospective review was performed on patients who underwent any spine procedure performed by one of our fellowship-trained spine surgeons at a single tertiary academic center from January 1st, 2019 to June 22nd, 2021. Patients were split into Pre-COVID or Post-COVID cohorts based on the timing of their surgery. March 23, 2020 was designated as the bifurcation based on the first issuance of a Stay at Home Order for COVID-19 in our city. Inpatient complications, 90-day readmission, and inpatient mortality were compared between the two cohorts. Secondary analysis included multiple logistic regression to determine independent predictors of inpatient complications, 90-day readmission, and inpatient mortality. Results: A total of 2,978 patients were included in the final analysis with 1,702 patients receiving designation as Pre-COVID and 1,276 as Post-COVID. The two groups differed with regards to lower Elixhauser scores (1.47 vs 1.65, p = 0.001), lower preoperative diagnoses of stenosis (57.8% vs 62.5%, p = 0.010) and radiculopathy (23.7% vs 31.2%, p < 0.001), fewer revision surgeries (16.8% vs 21.9%, p < 0.001), and fewer patients discharged home (84.5% vs 88.2%, p = 0.011) in the Pre-COVID cohort. The two cohorts had similar inpatient complications (36.6% vs 36.3%, p = 0.893) and inpatient mortality (0.1% vs 0.2%, p = 0.193). The Post-COVID cohort had fewer 90-day readmission (6.1% vs 3.9%, p = 0.008). On regression, being a Post-COVID patient was an independent predictor of decreased 90-day readmission (OR 0.63, p = 0.011). Similarly, surgery in the cervical region was associated with decreased readmission (ref: lumbar, OR 0.28, p = 0.001). Elixhauser (OR 1.12, p = 0.032), fusion surgeries (ref: decompression, OR 1.80, p = 0.027), and being discharged to an inpatient rehab facility (ref: home, OR 1.87, p = 0.021) were all associated with increased 90-day readmissions. Age (OR 1.01, p = 0.036), female sex (OR 1.33, p = 0.001), Elixhauser (OR 1.11, p < 0.001), length of stay (OR1.24, p < 0.001), anterior approach (ref: posterior, OR 2.33, p < 0.001), and combined approach (ref: posterior, OR 1.52, p < 0.001) were independent predictors of increased inpatient complications. Conclusion: Since COVID-19, patients undergoing spine surgery have an increased number of medical comorbidities, but a similar rate of inpatient complications and mortality. Patients are also being readmitted less frequently during the COVID-19 pandemic.

CLINICAL PATTERNS OF OBSTRUCTIVE SLEEP APNEA PATIENTS IN COVID 19

Introduction: Recent studies indicate Obstructive Sleep Apnea (OSA) patients have higher severity of respiratory compromise after COVID19 infection due to their sleep related hypoxemic burden. The pro-inflammatory state associated with OSA, sympathetic excitation, and recurrent hypoxemia may predispose to poorer post-COVID19 outcomes. We compared COVID19 infection outcomes in a cohort of hospitalized Veterans with and without OSA. Methods: We used Jesse Brown Veteran Affairs Medical Center (JBVAMC) Registry for Research on Risk Factors and Outcomes of Veterans Evaluated for COVID19. The registry includes all patients who received a test for COVID19 at JBVAMC through November 8th,2021. Data are from the VA COVID19 Shared Data Resource and chart review, and include demographic data, pharmacological and non-pharmacological interventions, clinical outcomes, and preexisting conditions. The study was approved by the Institutional review board (IRB). STATA v16 was used for data analysis. Results: Of the 13,385 patients included in the registry, 1890 patients were found to have a positive COVID19 test, of which 625 were hospitalized and included in our study. The sample was older (mean age of 66.8 years), predominantly men (583, 93.3%) and African Americans (461, 73.8%). 18.7% (117, 18.7%) were European American, and (47, 7.5%) were of other race categories. The group with OSA was 37.8% (n=236) and without OSA was 62.2% (n=389) of the total sample. Elixhauser comorbidity index was higher in OSA group compared to those without OSA (p:0.00001, mean (SD): 16.73(14.6) vs. 12.03 (13.1)). Univariate analysis demonstrated a higher rate of readmission at 60 days (p=0.02, Odds ratio (95% CI): 1.69 (1.1-2.6)) and use of mechanical ventilation (p=0.05, Odds ratio (95% CI): 1.65 (0.99-2.75) in OSA vs. without OSA. These associations were attenuated in multivariate logistic regression models including age, gender, race, Elixhauser index and body mass index. OSA did not affect the length of stay or inpatient mortality. Conclusion: In hospitalized COVID19 patients, OSA increases the probability of readmission and risk of mechanical ventilation, but this effect is likely due to higher comorbidity and obesity rates in OSA. In the future, we plan to examine larger samples of Veterans hospitalized with COVID19 and assess the effect of positive airway pressure treatment to understand the impact of OSA on COVID19 outcomes.

COVID-19 case fatality and Alzheimer's disease

Objective: Our objective was to determine whether AD increases COVID-19 case fatality rate (CFR). Background: Previous studies have identified dementia as a risk factor for death from coronavirus disease 2019 (COVID-19). However, it is unclear whether Alzheimer's disease (AD) is an independent risk factor for COVID-19 mortality. Design/Methods: In a retrospective cohort study, we identified 387,841 COVID-19 patientes through TriNetX, and performed a multivariable logistic regression to determine the odds ratio of dying from COVID-19 between patients with and without AD. We accounted for differences between cohorts in three ways. First, we included age, gender, race, ethnicity, and 30 comorbidities from the Elixhauser comorbidity index in our regression. Second, we matched each AD COVID-19 case to control COVID-19 cases with the same age, gender, race, and Elixhauser Comorbidity Index, and then performed conditional logistic regression to account for residual confounding. Third, we performed propensity score matching followed by conditional logistic regression. We extended this analysis to vascular dementia, dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). Results: We found that AD patients had higher odds of dying from COVID-19 compared to patients without AD (Odds Ratio(OR): 1.20, 95% confidence interval(CI): 1.09-1.32, p<0.001). This result is corroborated by conditional logistic regression analyses with exact-matching and propensity score matching. Interestingly, we did not observe increased mortality from COVID-19 among patients with vascular dementia (OR: 0.99, 95% CI: 0.88-1.10, p=0.83), DLB or FTD. Conclusions: AD increases CFR associated with COVID-19, though vascular dementia does not. These data are relevant to the evolving global COVID-19 pandemic and future pandemics.

“I depend on her for everything”: A mixed-methods analysis of the role of home care workers caring for medically and socially complex patients during the COVID-19 pandemic

Background: The devastating impact of the COVID-19 pandemic on long-term care facilities has illustrated the need for quality home-based care. Home care workers (HCWs) have played critical roles in meeting the medically and socially complex needs of homebound adults during COVID-19, yet their essential work is often undervalued and understudied. Our purpose was to explore the association between patients' medical and social circumstances and HCW services during COVID-19. Methods: In this mixed-methods study, we collected demographic and clinical data and performed a thematic analysis of medical records from 53 homebound patients with HCWs in a home-based primary care program in New York City. We ed unstructured clinical notes from 12/1/19 - 12/31/20 into a priori and emergent categories, including patient medical and social risk and changes to HCW responsibilities. Core themes were identified via team meeting discussions. Results: Of the 53 patients, 24.5% died during the initial COVID surge, 34% lived alone, and 41.5% had 24-hour HCWs. 50.9% of the patients lived with dementia and the mean Elixhauser Comorbidity Index was 3.66. Three themes emerged from our analysis: 1) Among this high-risk, high-need population, patients with certain risks (i.e. dementia diagnosis, living alone) had more intense and dynamic medical and social needs than others, 2) Patient medical status and risk factors influenced HCW tasks in meeting patient needs, such as managing progressing dementia behaviors or helping food-insecure patients obtain food, and 3) The combined effect of COVID-19 and HCW disruptions (i.e. unstable schedules, aide turnover) created difficult situations for patients and their caregivers, including increased risk of hospitalization and nursing home placement. Conclusions: During COVID-19, HCWs were essential in meeting the existing and new needs of homebound older adults. HCW disruptions were particularly challenging for patients who had more complex medical and social needs, leading to risk of hospitalization. This analysis can inform policies to better integrate HCWs on medical teams, further develop HCW training to identify social as well as medical risks, and address workforce shortages to expand access to adequate HCW services for homebound older adults and their caregivers.

Estimating SARS-CoV-2 Seroprevalence from Spent Blood Samples, January-March 2021

Background. Measuring SARS-CoV-2 antibody prevalence in spent samples at serial time points can determine seropositivity in a diverse pool of individuals to inform understanding of trends as vaccinations are implemented. Methods. Blood samples collected for clinical testing and then discarded ("spent samples") were obtained from the clinical laboratory of a medical center in Atlanta. A convenience sample of spent samples from both inpatients (medical/surgical floors, intensive care, obstetrics) and outpatients (clinics and ambulatory surgery) were collected one day per week from January-March 2021. Samples were matched to clinical data from the electronic medical record. In-house single dilution serological assays for SARSCoV-2 receptor binding domain (RBD) and nucleocapsid (N) antibodies were developed and validated using pre-pandemic and PCR-confirmed COVID-19 patient serum and plasma samples (Figure 1). ELISA optical density (OD) cutoffs for seroconversion were chosen using receiver operating characteristic analysis with areas under the curve for all four assays greater than 0.95 after 14 days post symptom onset. IgG profiles were defined as natural infection (RBD and N positive) or vaccinated (RBD positive, N negative). Single dilution serological assays for SARS-CoV-2 nucleocapsid antibodies were validated using pre-pandemic and PCR-confirmed COVID-19 patient serum and plasma samples. ELISA optical density (OD) cutoffs for seroconversion were chosen using receiver operating characteristic (ROC) analysis with areas under the curve (AUC) for all four assays greater than 0.95 after 14 days post symptom onset. Results. A total of 2406 samples were collected from 2132 unique patients. Median age was 58 years (IQR 40-70), with 766 (36%) ≥ 65 years. The majority were female (1173, 55%), and 1341 (63%) were Black. Median Elixhauser comorbidity index was 5 (IQR 2-9). 210 (9.9%) patients ever had SARS-CoV-2 detected by PCR, and 191 (9.0%) received a COVID-19 vaccine within the health system. Nearly half (1186/2406, 49.3%) of samples were collected from inpatient units, 586 (24.4%) from outpatient labs, 403 (16.8%) from the emergency department, and 231 (9.6%) from infusion centers. Overall, 17.0% had the IgG natural infection profile, while 16.2% had a vaccination profile. Prevalence estimates for IgG due to natural infection ranged from 24.0% in week 2 to 9.7% in week 5, and for IgG due to vaccine from 4.4% in week 2 to 32.0% in week 6 (Table, Figure 2). Conclusion. Estimated SARS-CoV-2 IgG seroprevalence among patients at a medical center from January-March 2021 was 17% by natural infection, and 16% by vaccination. Weekly trends likely reflect community spread and vaccine uptake.