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Objectives: Malnutrition is a prevalent condition affecting 30-50% of hospitalized patients. Malnutrition is linked to impairments in health outcomes and increased economic burden on healthcare systems. We assessed the prevalence and burden of malnutrition by examining demographic characteristics, Disease Related Group (DRG) payments and associated claims among Medicare inpatients (65+ years) with and without COVID-19. Method(s): Hospital inpatient COVID-19 claims from the Centers for Medicare & Medicaid Services (CMS) Inpatient Prospective Payment System (IPPS) between October 2020 - September 2021 were analyzed. The International Classification of Diseases, Tenth Revision, and Clinical Modification (ICD-10-CM) were used for malnutrition diagnoses. Demographic variables were compared based on the COVID-19 status;economic burden was analyzed by DRG payment of malnutrition cases with and without COVID-19. Result(s): Among 7,394,657 Medicare inpatient claims, only 12% had a documented malnutrition diagnosis. Of these patients, 1.2% had COVID-19. Regardless of COVID-19 status, malnourished patients averaged 75 years of age, and were predominantly female (54%) and White (78%) followed by Black (14%), and Hispanic (2%). Sepsis, kidney failure, and urinary tract infection (UTI) were the most common primary diagnoses in malnourished patients, regardless of COVID-19 status. Malnourished patients with COVID-19 had significantly higher DRG payments ($27,407 vs. $18,327) and increased cost of outlier payment ($3,208 vs. $2,049) compared to those without COVID-19, regardless of other diagnoses. Conclusion(s): Malnutrition diagnosis was confirmed in only 12% of the Medicare inpatients, thus suggesting that malnutrition continues to be underdiagnosed and undertreated - evidenced by high rates of hospitalizations/claims and payments in both COVID-19 and non-COVID-19 cases. It is imperative for hospitals to implement nutrition-focused protocols to identify, diagnose and address malnutrition among all Medicare inpatients regardless of COVID-19 status (and especially among patients with sepsis, kidney failure, and UTI). Nutrition-focused protocols can effectively improve patient health outcomes and reduce healthcare costs.Copyright © 2023
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Objectives: This analysis was conducted to develop a comprehensive list of ICD-10 CM codes for underlying conditions identified by the CDC as being associated with high-risk of developing severe COVID-19 and assessed the consistency of these codes when applied to large US based datasets. Method(s): The comprehensive list of ICD 10-CM codes for CDC-defined high-risk underlying conditions were mapped from CDC references and FDA Sentinel code lists. These codes were subsequently applied to Optum's de-identified Clinformatics Data Mart Database (claims) and the Optum de-identified Electronic Health Record (EHR) database across 3 years (2018, 2019 and 2020) among continuously enrolled subjects >= 12 years of age to determine the performance and consistency in identifying these high-risk underlying conditions annually over these years. Result(s): A total of 10,276 ICD-10 codes were mapped to 21 underlying conditions. Within the claims data, 62.7% of subjects >= 12 years had >= 1 CDC-defined high-risk condition (excluding age) with 26.6% of patients >= 65 years while in the EHR data 38% had >= 1 high-risk underlying condition (excluding age) with 14.4% >= 65 years. These results were similar and consistent in both datasets across all years. Patients aged 12-64 years in the claims data had a higher rate of >=1 high risk underlying condition relative to the EHR data, 49.3% and 34%, respectively. The top 5 conditions among the >= 65 were identical across both databases: hypertension, immunocompromised status, heart conditions, diabetes (type 1 or 2), and overweight/obesity. The top 5 conditions among the 12-64 age group were also similar among the databases and included: immunocompromised status, hypertension, overweight/obesity, smoking (current or former), and mental health conditions. Conclusion(s): These findings present a comprehensive list of codes that can be used by researchers, clinicians and policy makers to identify and characterize patients that may be at high-risk for severe COVID-19 outcomes.Copyright © 2023
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Objectives: Post-COVID conditions (PCC) are increasingly reported in people who had COVID. Certain racial or socioeconomic groups may be at greater risk for PCC and less likely to seek care. We examined the uptake of the new ICD-10-CM diagnosis code for PCC in routine clinical practice in the United States and how it varied by race and payer group. Method(s): Using the Optum de-identified Electronic Health Record (EHR) dataset, we identified patients with an ICD-10-CM code for PCC (U09.9) between October 1, 2021, through March 31, 2022, with 6 months of prior EHR activity. The earliest diagnosis defined the index date. All concurrent diagnoses were measured on the index date. Prior COVID diagnosis was assessed using all available data before the index date. Result(s): There were 23,647 patients: 9.9% were African American, 12.1% had Medicaid, and 2.4% were uninsured. There was an overrepresentation of white patients among those with PCC (78.6% compared with 69.6% of the overall EHR in 2021). More African American (24.1%), Medicaid (23.1%), and uninsured (27.5%) patients were diagnosed in the inpatient setting or emergency department than whites (14.0%) and commercially insured patients (10.0%). Among racial groups, African Americans had the highest percentage of documented prior COVID diagnosis at 63.6%. Of concurrent diagnoses, shortness of breath and acute respiratory failure with hypoxia were higher among African Americans (13.9% and 6.1%, respectively) than whites (11.5% and 4.3%, respectively). The same pattern was seen when comparing Medicaid and uninsured to commercial payors. Conclusion(s): The PCC code was used differently across racial groups and payor types and captures varying manifestations of PCC. The differences in diagnosis locations underscore the importance of using data capturing all care settings when conducting studies using this code. Subgroup analyses are important for future studies using U09.9 due to variability in code application.Copyright © 2023
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Objectives: To describe the use of extracorporeal membrane oxygenation (ECMO) among hospitalized coronavirus disease 2019 (H-COVID-19) patients in a linked closed claims (CC) and open claims (OC) database. Method(s): This analysis identified H-COVID-19 patients between April 2020 (Q2 2020) and June 2022 (Q2 2022) in CHRONOS, a linked CC and OC database. The index event was the date of hospitalization, defined as an inpatient claim within 21 days of a COVID-19 diagnosis in the CC. The occurrence of ECMO 30 days after index was identified using CC data alone and then CC and OP data in combination to assess missing data. Study exclusions included patients under the age of 18, a first COVID-19 diagnosis that did not result in hospitalization, and less than 12-months of continuous enrollment in the CC before index. Study criteria were defined by the presence of an ICD-10-CM, ICD-10-PCS, or CPT code on a claim. Results are reported as percentages and 95% confidence intervals. Result(s): Of 321,687 patients with H-COVID-19, the mean age was 50.1 (SD:12.8) with the highest proportion of hospitalizations occurring in Q3 2021 (19.4%). Overall, 0.50% (0.48%-0.52%) of patients in the CC data received ECMO, increasing to 0.61% (0.58%-0.64%) with the inclusion of OC data. The use of ECMO to treat H-COVID-19 patients decreased between Q2 2021 and Q2 2022, with the highest rates occurring in Q2 of 2020 (0.78%) and Q2 2021 (0.80%). The addition of OC data increased rates to 1.12% and 0.89% in Q2 of 2020 and Q2 2021. Conclusion(s): Although use of ECMO decreased in the later months of the pandemic, it represents a substantial burden. The current analysis demonstrates that CC data, often sourced from payers, may underestimate the use of ECMO in real-world settings. Opportunities exist to mitigate issues of missing data by linking CC, OC, and other real-world data sources.Copyright © 2023
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Objectives: Assess real-world evidence data on the prevalence and impact of long COVID (LC) to establish a baseline for the value of potential therapeutic interventions. Method(s): This study was a retrospective, longitudinal analysis of administrative claims from multiple payer channels spanning 4/1/2020-6/30/2022. Inclusion criteria: 1) ICD-10-CM diagnosis code of COVID-19 (U07.1) on or after 4/1/2020 (COVID-19 diagnosis date=index date), 2) 18+ years of age on index, and 3) at least -365/+30 days of continuous plan enrollment surrounding index. Employing a conservative LC definition, patients were classified as LC if they presented at least 1 claim >= 28 days following the index date which included both a COVID-19 diagnosis and >=1 of 8 LC-related symptoms. LC and non-LC patients were compared on demographics, COVID-19 symptoms, healthcare utilization, and medical costs. Descriptive statistics were presented for outcomes, and bivariate tests of significance were used to assess differences between cohorts. Result(s): Of 4,938,801 medically attended COVID-19 patients meeting inclusion criteria, 386,153 (7.8%) qualified as LC. The LC patients were older (Mean(SD) = 67.0(19.0) vs. 51.0(20.7)), were more likely to be female (65.1% vs. 60.4%), were in poorer health (Deyo-Charlson Comorbidity Index=3.51(3.24) vs. 1.47(2.45)), and presented greater baseline total medical expenditures ($39,769($60,401) vs. $15,275($35,640);p < 0.0001). On index, LC patients had a higher rate of LC-related symptoms, and in the 180-day post-index period, LC patients incurred increased total medical costs ($38,874($54,098) vs. $7,319($18,439);p < 0.001) and greater use of inpatient and outpatient medical services. Conclusion(s): Patients with LC presented elevated rates of symptoms and incurred 5-fold greater medical costs post-index compared to non-LC patients. This study is one of the first to longitudinally quantify the cost and symptom burden of LC in a real-world setting and helps to establish a baseline for the value of potential therapeutic interventions.Copyright © 2023
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Background: Although over 100 million pregnant women worldwide are at risk of infection with SARS-CoV-2, little data exists on the impact of COVID-19 and related treatments on maternal/neonatal health. Objective(s): (1) To quantify the prevalence of medication use in pregnancy to treat COVID-19, and (2) To quantify and compare the risk of adverse pregnancy/neonatal outcomes in those with and without COVID-19. Method(s): In the Canadian Mother-Child population-based cohort (CAMCCO), two sub-cohorts were identified using prospective data collection of medical services, prescription drugs, hospitalization archives data, and COVID-19 surveillance testing program (02/28/2020- 2021). The first cohort included all pregnant women during the study period regardless of pregnancy status (delivery, induced/planned or spontaneous abortion);this cohort was further stratified on COVID-19 status. The second cohort included all nonpregnant women (aged 15-45) with a positive COVID-19 test. COVID-19 in pregnant or nonpregnant women was assessed using COVID-19 test results or ICD-10CM code U07.1 from hospital data. COVID-19 severity was categorized based on hospital admission. Women were considered exposed to COVID-19 medications if they filled at least one prescription for a medicine included in the WHO list in the 30 days pre- or 30 days post-COVID-19 positive test/diagnosis. Considering potential confounders, association between COVID-19 during pregnancy, treated vs not, and perinatal outcomes were quantified using log-binomial regression models. Result(s): 150,345 pregnant women (3,464 (2.3%) had COVID-19), and 112,073 nonpregnant women with COVID-19 diagnoses were included. Pregnant women with COVID-19 were more likely to have severe infections compared to nonpregnant women with COVID-19 (11.4% vs 1.6%, p<0.001). The most frequent medications used in pregnancy to treat COVID-19 were antibacterials (13.96%), psychoanaleptics (7.35%), and medicines for obstructive airway disease (3.20%). In pregnancy COVID-19 was associated with spontaneous abortions (adjRR 1.76, 95%CI 1.37, 2.25), gestational diabetes (adjRR 1.52, 95%CI 1.18, 1.97), prematurity (adjRR 1.30, 95%CI 1.01, 1.67), NICU admissions (adjRR 1.32, 95%CI 1.10, 1.59);COVID-19 severity was increasing these risks but exposures to COVID-19 medications reduced all risks. Conclusion(s): COVID-19 severity was higher in pregnancy. Antibacterials, psychoanaleptics, and medicines for obstructive airway disease were the most used overall. COVID-19 was associated with adverse outcomes for mothers and newborns.
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Objectives: Clinical Practice Research Datalink (CPRD) Aurum captures primary care electronic healthcare records for ~28% of the population in England. From August 2020-;March 2022, all SARS-CoV-2 polymerase chain reaction (PCR) tests performed were reported back to the patient's general practitioner (GP), making the CPRD a closed system uniquely positioned to answer COVID research questions. Method(s): We defined persons with COVID as those recorded in primary care with a positive PCR test from August 1, 2020-March 31, 2021. We required continuous registration with their GP practice for >=365 days prior to diagnosis to establish comorbid conditions, and eligibility for linkage to Hospital Episode Statistics (HES) Admitted Patient Care data. Hospitalizations for COVID were defined as persons admitted with a primary diagnosis of COVID (ICD-10-CM U07.1) within 12 weeks of the initial primary care diagnosis record. Result(s): Our cohort included 535,453 persons diagnosed in primary care with COVID, with 2% later hospitalized. The hospitalized group was 57% male, 42% current/former smokers, 35% obese46% with a Charlson Comorbidity Index >1 and 98% had never received any COVID vaccine. Hospitalizations increased with age;<0.1% of patients aged 1-17, 1% aged 18-49, 4% aged 50-64, 9% aged 65-74, 13% aged 74-84, and 11% of COVID cases aged >=85 were hospitalized. Persons living in socially disadvantaged areas were overrepresented in the hospitalized cohort (25% in the Index of Multiple Deprivation's most deprived quintile). Conclusion(s): Consistent with other studies, hospitalized COVID patients were disproportionately those with male sex, smoking history, high body mass index, comorbidity and unvaccinated status. Hospitalizations were more common with age, and for individuals living in socially and economically deprived communities. Understanding the demographic and clinical characteristics of this cohort can help contextualize future work describing healthcare resource utilization and costs, as well as the impact of vaccines, associated with COVID in England.Copyright © 2023
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Background: Severe outcomes of COVID-19 are associated with advancing age, and multiple medical comorbidities. The impact of COVID-19 on the clinical course of patients with cirrhosis has not been well studied. We determined the effect of SARS-CoV-2 infection on the hospitalization and survival rates of patients with cirrhosis. Method(s): Using ICD-10-CM codes, we identified all Veterans with a diagnosis of cirrhosis in the VA Corporate Data Warehouse and COVID-19 Shared Data Resource. Study cohort included Veterans who were tested for SARS-CoV-2 and had no history of organ transplantation or malignancies. Each SARS-CoV-2 positive case was propensity-score matched by demographics and comorbidities with up to two SARS-CoV-2 negative controls. The primary endpoints were acute care hospitalization, admission to intensive care, respiratory support, or death. Result(s): Of 1,115,037 individuals tested for SARS-CoV-2, 31,680 were noted to have cirrhosis and among them 5,047 (16%) were SARS-CoV-2 positive. After exclusions and propensity-score matching, 5,047 SARS-CoV-2 positive and 9,913 propensity score matched SARS-CoV-2 negative individuals were included in the analysis cohort. Median age was 67 years, 95% were men and 25% were of black race. Median BMI was 30 and history of hypertension, diabetes, cardiovascular and chronic pulmonary disease was noted among 81%, 54%, 56% and 32% respectively. Among all cirrhotic individuals, SARS-CoV-2 positive individuals less frequently progressed to hepatic decompensation (3.1% vs 4.8%, P< 0.0001) or hospitalization (35.7% vs 38.2%, P=0.002), but more frequently required ICU admission 15% vs 12.2%, P< 0.0001) or respiratory support (7.3% vs 8.4%, P=0.01). Among those admitted, length of hospital stay was longer among SARS-CoV-2 positive individuals (7 vs 4 days, P< 0.0001). In Cox regression analysis, SARS-CoV-2 positivity was associated with a higher risk of all-cause mortality (HR 1.37, 95% CI 1.19,1.56). Conclusion(s): Although patients with cirrhosis and COVID-19 were less often hospitalized, they had longer duration of hospitalization and were at higher risk of severe or critical illness and death. (Figure Presented).
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Background: Given effectiveness of SARS-CoV-2 vaccines and outpatient antiviral and monoclonal antibody therapy for reducing progression to severe COVID-19, we sought to estimate the impact of these interventions on risk of hospitalization following SARS-CoV-2 infection in a large US healthcare system. Method(s): All patients >=18 of age in the UNC Health system, with first positive SARS-CoV-2 RT-PCR test or U07.1 ICD-10-CM (diagnosis date) during 07/01/2021- 05/31/2022, were included. The outcome was first hospitalization with U07.1 ICD-10-CM primary diagnosis <=14 days after SARS-CoV-2 diagnosis date. SARS-CoV-2 vaccinations were included if received >=14 days prior to diagnosis. Outpatient therapies were included if administered after diagnosis date and before hospital admission. Age, gender, race, ethnicity, and comorbidities associated with COVID-19 (using ICD-10-CM, if documented >=14 days prior to diagnosis date) were also evaluated. Risk ratios for hospitalization were estimated using generalized linear models, and predictors identified using extreme gradient boosting using feature influence with Shapley additive explanations algorithm. Result(s): The study population included 54,886 patients, 41% men and 27% >=60 years of age. One-third of SARS-CoV-2 diagnoses occurred July-December 2021 and 67% December-May 2022 (predominantly Delta and Omicron variants, respectively). Overall 7.0% of patients were hospitalized for COVID-19, with median hospitalization stay of 5 days (IQR: 3-9). 32% and 12% of patients received >=1 SARS-CoV-2 vaccine dose and outpatient therapy, respectively. Unadjusted and age-adjusted hospitalization risk decreased with vaccination and outpatient therapy (TABLE). Comparing patients who received 3 vaccine doses versus none we observed a 66% relative reduction in risk, with stronger association for more recent vaccination. For patients who received nirmatrelvir/ ritonavir versus no therapy we observed a 99% relative reduction in risk. In predictive models, older age was the most influential predictor of being hospitalized with COVID-19, while vaccination and outpatient therapy were the most influential factors predicting non-hospitalization. Conclusion(s): The impact of recent SARS-CoV-2 vaccination and outpatient antiviral and monoclonal antibody therapy on reducing COVID-19 hospitalization risk was striking in this large healthcare system covering Delta and Omicron variant timeframes. SARS-CoV-2 vaccinations and outpatient therapeutics are critical for preventing severe COVID-19. Unadjusted and age-adjusted risk ratios for hospitalization among patients with SARS-CoV-2.
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Background: Long COVID, also known as post-acute sequelae of COVID (PASC), affects more than 144 million people globally. While there is no broadly accepted consensus on a definition for the term "long COVID," studies have found symptoms persist or begin weeks or months after the end of SARS-CoV-2 infection. This study assessed the incidence of codes found in medical claims and hospital chargemasters that were consistent with long COVID symptoms commonly found in the literature. Method(s): Using the HealthVerity database, which provides closed claims and linked hospital chargemaster data on more than 25 million US patients, we examined patients aged 12 and above hospitalized between May 1, 2020 and September 30, 2021 with a diagnosis of COVID-19 who had at least 365 days of closed medical claims enrollment prior to index hospitalization admission and 90 days after admission, and did not have a long COVID diagnosis (ICD-10- CM U09.9) prior to the index hospitalization. Patients were allowed to have symptoms prior to hospitalization. The assessment period for the outcomes, which included 10 symptoms, was 90 days to 270 days after the date of hospitalization. Incidence rate per 100 person-years was calculated as the number of patients with the outcome divided by total person-time contributed (90 days after admission to the minimum of the following: outcome, inpatient death, disenrollment, end of data (April 30, 2022), or 270 days after admission). Result(s): The dataset included 3,661,303 patients with an inpatient hospitalization during the study period. The final study cohort included 44,922 patients hospitalized with COVID-19, 20,627 of whom experienced at least one of the long COVID symptoms. Anosmia and dysgeusia were the rarest events captured in medical claims. More commonly found symptoms were joint pain, fatigue and breathlessness (see table). Conclusion(s): This study examined diagnosed symptoms commonly found posthospitalization among COVID-19 patients and reported the incidence of these symptoms in a representative population. The start period of long COVID used in this study (90 days post hospitalization) is consistent with the WHO definition of long COVID. In the absence of an understanding of the pathophysiology of long COVID, the use of diagnosed symptoms to define long COVID has the advantage of ease of use and availability of data. Further studies of additional symptoms and predictors of long COVID are needed. (Figure Presented).
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INTRODUCTION: Coronavirus disease 2019 (COVID-19) has affected hospitalization of cardiac patients, both in terms of number of hospitalizations as well as hospital outcomes. In this study, we intended to understand the effects of COVID-19 pandemic on heart failure hospitalizations in the state of California. HYPOTHESIS: We hypothesized that adverse hospital outcomes such as in-hospital mortality, mechanical ventilation, mechanical circulatory support, vasopressor use, and acute respiratory distress syndrome (ARDS) would be higher among heart failure hospitalizations during 2020, compared to 2019. METHOD(S): The current study was a retrospective analysis of data collected and stored in California State Inpatient Database (SID) during March to December of 2019 and 2020. All adult (>=18 years of age) hospitalizations with heart failure were included for the analysis. ICD-10-CM diagnosis and procedure codes were used for identifying hospitalizations and procedures. We used propensity score matching and conditional logistic regressions to find the association between hospitalizations during 2019 versus 2020 with respect to outcome variables. RESULT(S): There were 101,032 (56.0%) heart failure hospitalizations during March to December of 2019, compared to 79,637 (44.0%) during March to December of 2020 (relative decrease, 21.2%). Hospitalizations for COVID-19 increased from 2,252 to 46,217 during the same period (relative increase, 19521.3%). Adverse hospital outcomes such as in-hospital mortality rates (2.9% versus 2.7%, P=0.003), mechanical ventilation (2.9% versus 2.2%, P<0.001), mechanical circulatory support (0.7% versus 0.5%. P<0.001), vasopressor use (1.3% versus 1.0%, P<0.001), and ARDS (0.1% versus 0.06%, P=0.007) were significantly higher in 2020, compared to 2019. Conditional logistic regression analysis showed that the odds of adverse clinical outcomes such as in hospital mortality (OR, 1.09;95% CI, 1.06-1.11), mechanical ventilation (OR, 1.07;95% CI, 1.05-1.09), vasopressor use (OR, 1.07;95% CI, 1.04-1.10), and ARDS (OR, 1.74;95% CI, 1.58-1.91) were significantly higher among heart failure hospitalizations in 2020. However, the odds of mechanical circulatory support did not differ between the two-time frames. CONCLUSION(S): Our study found that patients with heart failure hospitalized during the COVID-19 pandemic had greater in-hospital adverse events such as greater in-hospital mortality, mechanical ventilation use, vasopressor use, and ARDS. These findings warrant that heart failure requires prompt hospitalization and aggressive treatment irrespective of restrictive mandates during COVID-19 pandemic.Copyright © 2022
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Introduction: Myocarditis commonly results from viral infections, which causes inflammation of the heart muscles. This could lead to adverse outcomes such as prolonged hospitalizations, cardiogenic shock, cardiac arrest, and event death. Studies have shown that COVID-19 could lead to myocarditis. However, the differences between COVID-19 myocarditis and non-COVID-19 myocarditis have not been explored. Hypothesis: We hypothesized that adverse hospital outcomes such as in-hospital mortality, cardiogenic shock, cardiac arrest, mechanical ventilation, and acute respiratory distress syndrome would be higher among hospitalizations for COVID-19 myocarditis, compared to non-COVID-19 myocarditis. Method(s): We conducted a retrospective analysis of data collected in California State Inpatient Database (SID) during 2019 and 2020. We included data from all hospitalizations for COVID-19 myocarditis during 2020 and compared with data from all hospitalizations for non-COVID-19 myocarditis during 2019. ICD-10-CM diagnosis codes were used to identify procedures and conditions. Cox proportional and logistic regression analyses were done to compare the outcomes between the two groups. Result(s): A total of 1,165 non-COVID-19 myocarditis and 575 COVID-19 myocarditis hospitalizations were included for the analysis. Nearly 45% of COVID-19 myocarditis hospitalizations were >=65 years, while 52.3% of non-COVID-19 myocarditis hospitalizations were between 18-44 years of age. The rates of in-hospital mortality (4.2% versus 31.5%, P<0.001), cardiac arrest (2.0% versus 8.8%, P<0.001), mechanical ventilation (10.4% versus 41.2%, P<0.001), and acute respiratory distress syndrome (0.3% versus 17.5%, P<0.001) were significantly higher among COVID-19 myocarditis hospitalizations, compared to non-COVID-19 myocarditis hospitalizations. Kaplan Meier survival analysis showed that survival rates among COVID-19 myocarditis hospitalizations were significantly lower than non-COVID-19 myocarditis hospitalizations, compared to non-COVID-19 myocarditis hospitalizations (logrank P<0.001). Cox proportional regression analysis showed that in-hospital mortality (hazard ratio [HR], 2.15;CI: 1.41-3.28) was significantly higher among COVID-19 myocarditis hospitalizations. Logistic regression analysis showed that the odds of cardiac arrest (odds ratio [OR], 3.23;95% CI: 1.75-5.94), mechanical ventilation (OR, 5.65 95% CI: 4.09-7.81), and acute respiratory distress syndrome (OR, 72.56;95% CI: 21.52-244.68) were significantly higher among COVID-19 myocarditis hospitalizations. Conclusion(s): Our study using a large administrative database found that COVID-19 myocarditis compared to non-COVID 19 myocarditis affected older individuals and was associated with greater rates of in-hospital mortality and adverse hospital outcomes. These findings highlight the different nature of COVID related myocarditis compared to other forms of acute myocarditis.Copyright © 2022
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INTRODUCTION: Patients with COVID-19 can develop myocarditis due to respiratory hypoxemia, hyperinflammation, as well as direct injury due to binding of the virus to the angiotensin-converting enzyme 2 receptors in myocyte. In this study we examined the association between myocarditis among COVID-19 hospitalizations and adverse hospital outcomes. HYPOTHESIS: We hypothesized that adverse hospital outcomes such as in-hospital mortality, cardiac arrest, cardiogenic shock, mechanical ventilation, and acute respiratory distress syndrome would be higher among COVID-19 hospitalizations with myocarditis. METHOD(S): The current study was a retrospective analysis of data collected in California State Inpatient Database (SID) during 2020. All hospitalizations for COVID-19 were included for the analysis. ICD-10-CM diagnosis was used to identify COVID-19 (U07.1) and myocarditis hospitalizations and other procedures and conditions. Propensity score match analysis, survival analysis, and conditional logistic regression were done to compare adverse clinical outcomes between COVID-19 patients with and without myocarditis. RESULT(S): A total of 164,368 COVID-19 hospitalizations were included for the analysis. Among them, 575 (0.4%) hospitalizations had myocarditis. Prior to propensity score matching, the rate of in-hospital mortality was significantly higher among COVID-19 hospitalizations with myocarditis (29.8% versus 14.0%, P<0.001). Even after propensity score matching, the rate of in-hospital mortality was significantly higher among the myocarditis group (30.0% versus 17.5%, P<0.001). Supporting this finding, survival analysis with log-rank test also showed that 30-day survival rates were significantly lower among those with myocarditis (39.5% versus 46.3%, P<0.001). Conditional logistic regression analysis showed that the odds of cardiac arrest (OR,1.90;95% CI, 1.16-3.14), cardiogenic shock (OR,4.13;95% CI, 2.14-7.99), mechanical ventilation (OR,3.30 (2.47-4.41), and acute respiratory distress syndrome (OR, 2.49;95% CI, 1.70-3.66) were significantly higher among those with myocarditis. CONCLUSION(S): Our study using a large administrative database found that myocarditis was associated with greater rates of in-hospital mortality and adverse hospital outcomes among COVID-19 patients. Early suspicion is important for prompt diagnosis and timely management.Copyright © 2022
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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
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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
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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
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Objectives: Postpartum depression (PPD) has been described as "the thief that steals motherhood" by depriving women of the anticipated joy of a new infant. Through this study, we intend to see the incidence, treatment rates (TR), relative-treatment rate (TRR), absolute treatment rate (ATR), and number needed to treat (NNT) pre- and post-COVID-19 on treatment of women with PPD. Method(s): This retrospective cohort study included newly diagnosed patients with PPD in 2019 (1st Jan - 31st Dec [pre-pandemic]) and 2020 (1st Jan - 31st Dec [pandemic]) using ICD-10-CM codes from Optum's de-identified Clinformatics Data Mart. Only the patients having continuous eligibility between 12 months before (baseline period) to 12-months post (follow-up period) the first diagnosis of PPD (index date) were included in study. During the follow-up period, patients were then checked for pharmacological treatment received (SSRI, SNRI's and other anti-depressants) using NDC codes. To measure effects, percentages of patients getting treatment, TRR (TR in pandemic/TR in pre-pandemic), ATR (TR in pre-pandemic - TR in a pandemic), and NNT (1/ATR) were calculated before and during COVID. The significance of categorical variables was examined using the Chi-square test. Result(s): We observed 39% increase in incidence of PPD patients during pandemic (n=16,095) vs pre-pandemic (n=11,565). Only 51% TR (risk ratio) was observed during pandemic vs 60% TR (risk ratio) in pre-pandemic with any SSRI, SNRI, and anti-depressants (p<.01). Compared to patients receiving treatment during pandemic vs pre-pandemic: TRR was found to be 85% (relative risk) and ATR was 9% (absolute risk reduction). The NNT comparing pre- and during pandemic was 11. Conclusion(s): The results of the study demonstrated that treatment of women with PPD was impacted during pandemic vs pre-pandemic (9% women did not receive treatment during pandemic). Alternative methods or non-pharmacological treatments may be required to further alleviate non-treated patients and improve their condition. Copyright © 2022
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Objectives: This study aimed to explore the impact of COVID-19 on patients with PTSD and the burden of resource utilization in the pre- and during the COVID-19 pandemic. Method(s): This retrospective observational study included patients diagnosed with PTSD between 1st January 2018 to 31st December 2020 using ICD-10-CM codes from Optum's de-identified Clinformatics Data Mart database. In the study duration, distinct patients were identified and further classified by age, gender, and location of service. To determine the influence in pre- and during COVID-19 for each of the stratification variables, a year-wise comparison was done. Chi-square was performed as test of significance for categorical variables. Result(s): Overall we observed the number of PTSD patients increased by 7% (n=206,741) during the pandemic (1st January 2020 - 31st December 2020) vs pre-pandemic (1st January 2019 - 31st December 2019). A significant increase was seen across all age groups (p<.05). In the case of teenagers, PTSD was found to have increased by 22% whereas in adults and the elderly an 8% and 3% increase was seen respectively. When broken down by gender, a significant increase was observed. Females (+9% [n=143,032]) were seen to have been affected more compared to males (+4% [n=63,625]) during the pandemic vs pre-pandemic. In healthcare resources utilization overall, there was an observed 24% increase. For both inpatients and office, PTSD decreased significantly (-3% and -4% respectively) (p<.05);while ER visits, increased only by 1% (p<.05). A significant increase in outpatient and telehealth services was observed (122% and 454% respectively) (p<.05). Conclusion(s): An increased exacerbation in PTSD was observed during the pandemic with respect to burden across various stratification and resource utilization;especially in outpatient and telehealth services. Better treatment, psychotherapy and alternative care programs may be required to curb this impact and decrease the overall burden across various care setting. Copyright © 2022
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Objectives: This study aimed to explore the impact of COVID-19 on patients with SSA and the burden of resource utilization in the pre- and during the COVID-19 pandemic. Method(s): This retrospective observational study included patients diagnosed with SSA between 1st January 2019 to 31st December 2020 using ICD-10-CM codes from Optum's de-identified Clinformatics Data Mart. In the study duration, distinct patients were identified and further classified by age, gender, and location of service. To determine the influence in pre- and during COVID-19 for each of the stratification variables, a year-wise comparison was done. Chi-square test was performed to check the significance of categorical variables. Result(s): Overall we observed the number of SSA patients increased by 2% (n=266,329) during the pandemic (1st January 2020 - 31st December 2020). A significant increase was seen across all age groups (p<.01). In the case of teenagers, SSA was found to have increased by 80% whereas in adults and elderly an 15% and 8% increase was seen respectively during pandemic (p<.01). When stratified by gender, a significant increase was observed only in females (+9% [n=174,647]) where in males (-3% [n=91,573]) decrease was observed during pandemic. In healthcare resources utilization overall, there was an observed 12% increase during pandemic. For inpatients, office, and outpatient, SSA decreased significantly (-4%, -8%, and -1% respectively) during pandemic (p<.01). A significant increase in outpatient and telehealth services was observed (34% and 1,299% respectively) (p<.01). Conclusion(s): An increased exacerbation in SSA was observed during the pandemic with telehealth and outpatient services being impacted the highest. This may be attributed to facing near-death scenarios, and the loss of loved ones amongst other factors. With the increase in cases, health care resource utilization across various settings is pressed. Better treatment and programs may be required to curb this impact and decrease the overall burden. Copyright © 2022
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Objective To determine cumulative incidence and point prevalence of neuromyelitis optica spectrum disorder (NMOSD), multiple sclerosis (MS), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) in Thailand using population-based data of Chumphon province. Background CNS inflammatory demyelinating diseases (CNSIDDs) have a great interracial heterogeneity. The epidemiology of CNSIDDs in Thailand, a Mainland Southeast Asian country, is unknown. Design/Methods Searching for CNSIDD patients at a public secondary care hospital in Chumphon from January 2016 to December 2021 was performed using relevant ICD-10-CM codes. All neurology patients were systematically referred to this hospital as it was the only hospital in the province with a neurologist. Diagnoses were individually ascertained by retrospective chart review. Cumulative incidence over 2016-2021, point prevalence on December 31st, 2021, attack rate, mortality rate, and disabilityadjusted life years (DALYs) were calculated. Population data were obtained from the National Statistical Office of Thailand. As of December 31st, 2021, the population census of Chumphon was 509,479. Results NMOSD was the most prevalent CNSIDD in adult Thai population at 3.33 per 100,000 persons (crude prevalence 2.55). The age-adjusted prevalence of aquaporin-4 antibody-positive NMOSD alone was 3.08 per 100,000 persons. Age-adjusted incidence rate of NMOSD was 1.65 per 100,000 persons/year (crude incidence rate 0.20). Age-adjusted prevalence of MS followed at 0.77 and MOGAD at 0.51 per 100,000 persons (crude prevalence 0.59 and 0.39, respectively). Although most had a fair recovery, disability was worst amongNMOSD with a DALY of 3.47 years per 100,000 persons. Mortality and attack rates were highest in NMOSD as well. No increase in incidence or attack rate were observed during the COVID-19 pandemic. Conclusions CNSIDDs are rare diseases in Thailand. The prevalence is comparable to that of East Asian countries. NMOSD caused the highest DALYs among CNSIDDs.