Objectives: To determine whether Telemedicine intervention can affect hospital mortality, length of stay, and direct costs for progressive care unit patients. Design: Retrospective observational. Setting: Large healthcare system in Florida. Patients: Adult patients admitted to progressive care unit (PCU) as their primary admission between December 2011 and August 2016 (n = 16,091). Interventions: Progressive care unit patients with telemedicine intervention (telemedicine PCU [TPCU]; n = 8091) and without telemedicine control (nontelemedicine PCU [NTPCU]; n = 8000) were compared concurrently during study period. Measurements and Main Results: Primary outcome was progressive care unit and hospital mortality. Secondary outcomes were hospital length of stay, progressive care unit length of stay, and mean direct costs. The mean age NTPCU and TPCU patients were 63.4 years (95% CI, 62.9–63.8 yr) and 71.1 years (95% CI, 70.7–71.4 yr), respectively. All Patient Refined-Diagnosis Related Group Disease Severity (p < 0.0001) and All Patient Refined-Diagnosis Related Group patient Risk of Mortality (p < 0.0001) scores were significantly higher among TPCU versus NTPCU. After adjusting for age, sex, race, disease severity, risk of mortality, hospital entity, and organ systems, TPCU survival benefit was 20%. Mean progressive care unit length of stay was lower among TPCU compared with NTPCU (2.6 vs 3.2 d; p < 0.0001). Postprogressive care unit hospital length of stay was longer for TPCU patients, compared with NTPCU (7.3 vs 6.8 d; p < 0.0001). The overall mean direct cost was higher for TPCU ($13,180), compared with NTPCU ($12,301; p < 0.0001). Conclusions: Although there are many studies about the effects of telemedicine in ICU, currently there are no studies on the effects of telemedicine in progressive care unit settings. Our study showed that TPCU intervention significantly decreased mortality in progressive care unit and hospital and progressive care unit length of stay despite the fact patients in TPCU were older and had higher disease severity, and risk of mortality. Increased postprogressive care unit hospital length of stay and total mean direct costs inclusive of telemedicine costs coincided with improved survival rates. Telemedicine intervention decreased overall mortality and length of stay within progressive care units without substantial cost incurrences.

Background: Although palliative care services are increasing in the United States, disparities exist in access and utilization. Hence, we explored these factors in hospitalized patients with advanced cancers using the National Inpatient Sample (NIS). Methods: This was a retrospective analysis of NIS data, 2005 to 2014, and included patients ≥18 years with advanced cancers with and without palliative care consultations. Both χ ² and independent t tests were used for categorical and continuous variables. Multivariate logistic regressions were used for identifying factors associated with palliative care consultations. Results: Palliative care consultations were recorded in 9.9% of 4 732 172 weighted advanced cancer hospitalizations and increased from 3.0% to 15.5% during 2005 to 2014 (relative increase, 172.2%, P _trend < .01). Factors associated with higher palliative care consultations were increasing age, ≥80 years (odds ratio [OR]: 1.47; 95% confidence interval [CI]: 1.38-1.56); black race (OR: 1.21; 95% CI: 1.14-1.28); private insurance coverage (OR: 1.10; 95% CI: 1.02-1.18); West region (OR: 1.15; 95% CI: 1.01-1.33); large hospitals (OR: 1.19; 95% CI: 1.02-1.34); high income (OR: 1.08; 95% CI: 1.08-1.17); do-not-resuscitate (dying patients) status (OR: 10.55; 95% CI: 10.14-10.99); and in-hospital radiotherapy (OR: 1.13; 95% CI: 1.06-1.21). Palliative care consultations were lower in patients with chemotherapy (OR: 0.71; 95% CI: 0.60-0.84). Conclusion: Many demographic, socioeconomic, health-care, and geographic disparities were identified in palliative care consultations. Additionally, palliative care resources were underutilized by hospitalized patients with advanced cancers and commonly utilized by patients who are dying. Health-care providers and policy makers should focus on these disparities in order to improve palliative care use.

Objectives: To examine the trends in hospitalization rates, mortality, and costs for sepsis during the years 2005 to 2014. Methods: This was a retrospective serial cross-sectional analysis of patients ≥18 years admitted for sepsis in National Inpatient Sample. Trends in sepsis hospitalizations were estimated, and age- and sex-adjusted rates were calculated for the years 2005 to 2014. Results: There were 541 694 sepsis admissions in 2005 and increased to 1 338 905 in 2014. Sepsis rates increased significantly from 1.2% to 2.7% during the years 2005 to 2014 (relative increase: 123.8%; P _trend < .001). However, the relative increase changed by 105.8% ( P _trend < .001) after adjusting for age and sex and maintained significance. Although total cost of hospitalization due to sepsis increased significantly from US$22.2 to US$38.1 billion ( P _trend < .001), the mean hospitalization cost decreased significantly from US$46,470 to US$29,290 ( P _trend < .001). Conclusions: Hospitalizations for sepsis increased during the years 2005 to 2014. Our study paradoxically found declining rates of in-hospital mortality, length of stay, and mean hospitalization cost for sepsis. These findings could be due to biases introduced by International Classification of Diseases, Ninth Revision, Clinical Modification coding rules and increased readmission rates or alternatively due to increased awareness and surveillance and changing disposition status. Standardized epidemiologic registries should be developed to overcome these biases.

Lipids represent a valuable target for metabolomic studies since altered lipid metabolism is known to drive the pathological changes in cardiovascular disease (CVD). Metabolomic technologies give us the ability to measure thousands of metabolites providing us with a metabolic fingerprint of individual patients. Metabolomic studies in humans have supported previous findings into the pathomechanisms of CVD, namely atherosclerosis, apoptosis, inflammation, oxidative stress, and insulin resistance. The most widely studied classes of lipid metabolite biomarkers in CVD are phospholipids, sphingolipids/ceramides, glycolipids, cholesterol esters, fatty acids, and acylcarnitines. Technological advancements have enabled novel strategies to discover individual biomarkers or panels that may aid in the diagnosis and prognosis of CVD, with sphingolipids/ceramides as the most promising class of biomarkers thus far. In this review, application of metabolomic profiling for biomarker discovery to aid in the diagnosis and prognosis of CVD as well as metabolic abnormalities in CVD will be discussed with particular emphasis on lipid metabolites.