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Background/Objective: The primary objective was to quantify the role of the number of Centers of Disease Control and Prevention (CDC) risk factors on in-hospital mortality. The secondary objective was to assess the associated hospital length of stay (LOS), intensive care unit (ICU) bed utilization, and ICU LOS with the number of CDC risk factors. Methods: A retrospective cohort study consisting of all hospitalizations with a confirmed COVID-19 diagnosis discharged between March 15, 2020 and April 30, 2020 was conducted. Data was obtained from 276 acute care hospitals across the United States. Cohorts were identified based upon the number of the CDC COVID-19 risk factors. Multivariable regression modeling was performed to assess outcomes and utilization. The odds ratio (OR) and incidence rate ratio (IRR) were reported. Results: Compared with patients with no CDC risk factors, patients with risk factors were significantly more likely to die during the hospitalization: One risk factor (OR 2.08, 95% CI, 1.60–2.70; P < 0.001), two risk factors (OR 2.63, 95% CI, 2.00–3.47; P < 0.001), and three or more risk factors (OR 3.49, 95% CI, 2.53–4.80; P < 0.001). The presence of CDC risk factors was associated with increased ICU utilization, longer ICU LOS, and longer hospital LOS compared to those with no risk factors. Patients with hypertension (OR 0.77, 95% CI, 0.70–0.86; P < 0.001) and those administered statins were less likely to die (OR 0.54, 95% CI, 0.49–0.60; P < 0.001). Conclusions: Quantifying the role of CDC risk factors upon admission may improve risk stratification and identification of patients who may require closer monitoring and more intensive treatment.

PurposeThis study quantified the overall effects of aortic valve disease (AVD) and mitral valve disease (MVD) by disease severity on direct health-care costs to insurers and patients.Materials and methodsBased on 1996–2011 data from the Medical Expenditure Panel Survey (MEPS), a large, nationally representative US database, multivariate analyses were performed to assess the relationship between AVD and MVD and direct annual health-care costs to insurers and patients, at individual and US-aggregate levels. Adults aged 18 years and over with diagnosis codes for AVD or MVD based on International Classification of Diseases (ninth revision) diagnosis codes were identified. Subjects were further classified as symptomatic AVD, asymptomatic AVD, symptomatic MVD, and asymptomatic MVD. These classifications were determined with clinical assistance and based in part on data availability in the MEPS.ResultsThe MEPS database included 148 patients with AVD: 53 patients with symptomatic AVD, 95 patients with asymptomatic AVD, and 1,051 with MVD, including 315 patients with symptomatic MVD and 736 patients with asymptomatic MVD. Symptomatic AVD had the largest incremental effect on annual per patient health-care expenditure: $12,789 for symptomatic AVD, $10,816 for asymptomatic AVD, $5,163 for symptomatic MVD, and $1,755 for asymptomatic MVD. When aggregated to the US population, heart-valve disease accounted for an incremental annual cost of $23.4 billion. The largest aggregate annual costs were incurred by patients with symptomatic MVD ($7.6 billion), followed by symptomatic AVD ($5.6 billion), asymptomatic MVD ($5.6 billion), and asymptomatic AVD ($4.6 billion).ConclusionThe annualized incremental costs of heart-valve disease were substantial for all groups examined, and greatest for patients with symptomatic MVD. This reflects the relatively high prevalence associated with this group. With a growing and aging population, the prevalence of heart-valve disease is expected to rise, increasing the burden on public health.

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is an employee of, and Diana Frame and Peter J. Mallow are consultants of, CTI Clinical Trial and Consulting Services, which is a consultant to Biosense Webster, the study sponsor. Mark M. Gallagher has received research funding from Attune Medical and has acted as a consultant and paid speaker for Boston Scientific and Cook Medical. Lisa W. M. Leung has received research support from Attune Medical.

Background To determine the cost-effectiveness of In-Home Cognitive Behavioral Therapy (IH-CBT) for low-income mothers enrolled in a home visiting program. Methods A cost-utility analysis was conducted using results from a clinical trial of IH-CBT and standard of care for depression derived from the literature. A probabilistic, patient-level Markov model was developed to determine Quality Adjusted Life Years (QALYs). Costs were determined using the Medical Expenditure Panel Survey. A three-year time horizon and payer perspective were used. Sensitivity analyses were employed to determine robustness of the model. Results IH-CBT was cost-effective relative to standard of care. IH-CBT was expected to be cost-effective at a three-year time horizon 99.5%, 99.7%, and 99.9% of the time for willingness-to-pay thresholds of US$25,000, US$50,000, and US$100,000, respectively. Patterns were upheld at one-year and five-year time horizons. Over the three-year time horizon, mothers receiving IH-CBT were expected to have 345.6 fewer days of depression relative to those receiving standard home visiting and treatment in the community. Conclusions IH-CBT is a more cost-effective treatment for low-income, depressed mothers than current standards of practice. These findings add to the growing literature demonstrating the cost-effectiveness of CBT for depression, and expand it to cover new mothers. From a payer perspective, IH-CBT is a sound option for treatment of depressed, low-income mothers. Limitations include a restricted time horizon and estimating of standard of care costs.

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