Utility of the HScore for Predicting COVID-19 Severity.

BACKGROUND: Cytokine release syndrome is a life-threatening condition known to cause fever and multiple organ dysfunction and is suspected to be related to the severity of coronavirus disease 2019 (COVID-19). We sought to examine the utility of the HScore and non-cytokine markers of inflammation for predicting COVID-19 outcomes. We hypothesized that cytokine storm, assessed by a modified HScore, would be linked to more severe COVID-19 symptoms and higher mortality. METHODS:  A retrospective review of records from a large, private hospital system was conducted on patients with hemophagocytic lymphohistiocytosis (HLH) (2014-2019) and compared to a large cohort of COVID-19-positive patients (2020). Patients with a sufficient number of elements in their record for a modified HScore calculation (n=4663), were further subdivided into population 1 (POP1, n=67; HLH, n=493 COVID-19), which had eight HScore elements, and population 2 (POP2) with six available HScore elements (POP2, n=102; HLH, n=4561 COVID-19). RESULTS: Modified HScore predicted COVID-19 severity in POP1 and POP2 as measured by higher odds of being on a ventilator (POP2 OR: 1.46, CI: 1.42-1.5), ICU admission (POP2 OR: 1.38, CI: 1.34-1.42), a longer length of stay (p<0.0001), and higher mortality (POP2 OR: 1.34, CI: 1.31-1.39). C-reactive protein (CRP) and white blood cell (WBC) count were the most consistent non-cytokine predictors of COVID-19 severity. CONCLUSION:  Cytokine storm, evaluated using a modified HScore, appeared to play a role in the severity of COVID-19 infection, and selected non-cytokine markers of inflammation were predictive of disease severity.

Analysis of Emergency Department Utilization in Medicaid Expansion and Non-expansion States.

Introduction The Affordable Care Act has been debated since its initial enactment over a decade ago. One of the primary topics for discussion has been Medicaid expansion, which has created a schism across the United States. The effects of Medicaid expansion largely remain unclear. The purpose of this report is to elucidate how Medicaid expansion has impacted emergency department (ED) utilization by analyzing Medicaid expansion and non-expansion states to determine who visited the ED and the reason for the visit. Methods We conducted a retrospective analysis using de-identified electronic medical record (EMR) data from 56,423 patients and 33 different hospitals (18 Medicaid non-expansion and 15 Medicaid expansion) who visited the ED in 2019. We used geographical demographics and insurance status to categorize patients who visited the ED and ambulatory care sensitive conditions (ACSC) to identify the reasons for the visit. Logistic regression and chi-square analysis were used to analyze the data. Results We observed a significant relationship between Medicaid expansion and geographic region such that patients living in rural or semirural regions likely resided in Medicaid non-expansion states. Patients using self-pay were more likely to live in a Medicaid non-expansion state than a Medicaid expansion state (32.3% vs. 21.5%, p-value < 0.0001). Finally, there were no significant differences between the top five ACSC for Medicaid expansion and Medicaid non-expansion states but living in an expansion state was significantly (p < 0.01) related to being diagnosed with an ACSC (OR, 1.056; 95% CI, 1.013-1.100). Conclusion In conclusion, Medicaid expansion was associated with differences in the use of medical resources. Patients using Medicaid insurance who reside in Medicaid expansion states preferentially use the ED. Geographical location does play a role in ED utilization and ambulatory care sensitive condition diagnoses in patients. Despite these findings, the full effects of Medicaid expansion on ED utilization require further investigation. However, our research indicates that Medicaid expansion is not the singular solution in decreasing ED utilization and healthcare costs.

Obesity, Race, and COVID-19 Mortality: Results from a Large Cohort Early in the Pandemic.

Background: Obesity has increased progressively in the United States and is a known risk factor for several diseases such as type 2 diabetes, coronary artery disease, stroke and hypertension. Amid the current pandemic, concerns have been raised about obesity as a risk factor for COVID-19 positive patients. The primary goal of this study was to explore the association between obesity and hospital mortality in COVID-19 patients. Our secondary objective was to explore the relationship between obesity and race on hospital mortality in COVID-19 patients. Methods: This was a cross-sectional, retrospective analysis using data from 186 hospitals from across the United States and the United Kingdom during the first quarter of 2020. Extraction provided data from 25,894 patients who were tested for COVID-19, of whom 2,977 were positive. Patients were stratified into standard WHO categories for BMI and by race. Results: Bivariate analysis revealed significant relationships between mortality and sex (p<0.001) When BMI was analyzed as a continuous variable, multivariate analysis revealed a significant influence of BMI on mortality (odds ratio=1.291, p<0.05). Conclusion: COVID-19 mortality was significantly related to BMI, age and select co-morbidities, but race/ethnicity was not a predictor of mortality when controlling for other variables.

Utilization of Patient-Controlled Analgesia Reduces Length of Stay of Sickle Cell Crisis Hospitalizations.

Background: Sickle cell crisis hospitalizations are emotionally and financially burdensome to patients and healthcare systems, and processes to decrease the frequency or length of stay of these crises should be examined. Methods: This is a multicenter retrospective hospital record review of sickle cell crisis hospitalizations as defined by ICD-10 codes (D57.1-4), from January 2016 through December 2019, examining inpatient medication administration records and length of stay among admitted adults aged 18-65 years. Patient controlled analgesia orders using morphine, hydromorphone, fentanyl and/or merperidine at any point of an admission (n=188) were compared to admissions without any patient-controlled analgesia orders (n=2,159). The primary end point was hospital length of stay in days. A secondary analysis examining patients with or without greater than four admissions was also conducted. Results: The 1,675 patients who met criteria comprised 2,347 sickle cell hospitalizations during the four years examined. Of those admissions, 188 had at least one patient-controlled analgesic documented in their chart and had an average length of stay of 4.54 days (SD 3.34). The 2,159 admissions without any patient-controlled analgesia had an average length of stay of 5.74 days (SD 4.64). The difference of 1.2 days between the groups was statistically significant (p≤0.0001) using a Wilcoxon signed-rank test. Conclusion: Among patients with sickle cell crises who required inpatient hospitalizations, the use of patient-controlled analgesia demonstrated a statistically significant reduction of 1.2 days in their total length of stay. These findings support potentially changing hospital protocols to increase patient-controlled analgesia utilization.