Inpatient outcomes of mechanical circulatory support devices and heart transplantation in hypertrophic cardiomyopathy.

INTRODUCTION: The pathophysiology of HCM presents unique challenges for the management of cardiogenic shock and the use of mechanical circulatory support devices (MCSD). However, outcomes investigations for MCSD and HT in HCM patients is limited to case reports. The present study investigated MCSD and HT outcomes in HCM patients in a large retrospective cohort. METHODS: The National Inpatient Sample (2016-2019) was used for the retrospective analysis of patients hospitalized for MCSD and HT using ICD-10 codes. Patients with implantation of more than one device category were excluded. These patients were divided into two cohorts, with and without HCM, and compared in terms of in-hospital mortality, trends in mortality rates, hospitalization costs and mean length of stay. RESULTS: Among 267,780 patients hospitalized for MCSD and HT, 1155 patients had underlying HCM. Underlying HCM was associated with increased odds of mortality in patients receiving left ventricular assist devices (LVAD) (OR 3.4, 95% CI 1.03-11.2, p = 0.04) and temporary MCSD (OR 2.5, CI 1.8-3.6, p < 0.001). HCM was not associated with increased mortality in patients hospitalized for HT (OR 0.67, CI 0.15-2.85, p = 0.6). Patients with HCM undergoing MCSD and HT had a longer mean length of stay (22.1 vs 13.2 days, p = 0.004), and higher mean hospitalization charges ($830,103 vs $460,383, p < 0.0001) as compared to non-HCM patients. CONCLUSION: Underlying HCM is associated with increased in-hospital mortality in patients undergoing LVAD and temporary MCSD placement. Further prospective studies are required to expand our understanding of prognosis among HCM patients undergoing MCSD and establish management guidelines.

Geographical and socioeconomic disparities in post-transcatheter aortic valve replacement pacemaker placement.

INTRODUCTION: Pacemaker (PPM) implantation is indicated for conduction abnormalities which can develop post-transcatheter aortic valve replacement (TAVR). However, whether post-TAVR PPM risk is associated with the geographical location of the hospital and socioeconomic status of the patient is not well established. Our goal was to explore geographical and socioeconomic disparities in post-TAVR PPM implantation. METHODS: A retrospective cohort analysis was conducted using the National Inpatient Sample 2016-2020 with respective ICD-10 codes for TAVR and PPM implantation. A weighted multivariate logistic regression model was used to analyze prognostic outcomes. RESULTS: The number of patients hospitalized for undergoing TAVR was 296,740, out of which 28,265 patients had PPM implantation (prevalence 9.5 %). Patients' demographics including sex, ethnicity, household income, and insurance were not associated with risk of post-TAVR PPM except age (OR 1.01, CI 1.07-12.5, p < 0.001). Compared to rural hospitals, urban non-teaching hospitals were associated with a higher risk of post-TAVR PPM (OR 2.09, 1.3-3.43, p = 0.003). Compared to New England hospitals (ME, NH, VT, MA, RI, CT), middle Atlantic hospitals (NY, NJ, PA) were associated with highest post-TAVR PPM risk (OR 1.54, CI 1.2-1.98, p < 0.001), followed by Pacific (AK, WA, OR, CA, HI), mountain (ID, MT, WY, NV, UT, CO, AZ, NM) and east north central US. CONCLUSION: Patients' demographics including sex, ethnicity, household income, and insurance were not associated with the risk of post-TAVR PPM except for age. Compared to New England hospitals, Middle Atlantic hospitals were associated with the highest post-TAVR PPM risk followed by Pacific, Mountain, and East North Central US. Prospective studies with data on TAVR wait times, expertise of the interventional staff, and post-TAVR management and discharge planning are required to further explore the observed regional distribution of TAVR outcomes.

Social Stigmatization of Drug Abusers in a Developing Country: A Cross-Sectional Study.

INTRODUCTION:  Stigma is a label that differentiates a person from others and associates them with unenviable attributes. There are various forms of stigma: enacted stigma, perceived stigma, and self-stigma manifesting as stereotyping and harboring negative thoughts about the stigmatized group. Stigmatization of the drug abuser leads to effects such as low self-esteem, depression, and personality changes in the stigmatized.  Objectives: The purpose of the study is to know the impact of stigma on patients receiving substance abuse treatment in the Psychiatry Department, Mayo Hospital Lahore, Pakistan. DESIGN: Cross-sectional study.  Place: Psychiatry Department, Mayo Hospital, Lahore, Pakistan Study Period: Six months (February 22, 2020, to July 18, 2020). SUBJECTS AND METHODS: A population-based cross-sectional study was conducted in a tertiary care hospital. A total of 100 patients were recruited in the study. The selection was made on laid down criterion after taking due consent. Interviews were conducted through a pretested questionnaire. Data were collected, compiled, and analyzed through SPSS version 20 (IBM Corp., Armonk, USA), and relevant frequency tables were drawn.  Results: On analyzing the data, various forms of stigma were observed: enacted stigma (81% as considered less capable), perceived stigma (99% as having difficulties in the job seeking and relationships), and self-stigma (94% in having devaluation thoughts). Self-esteem was maintained (73% were content). Social support was present (76% from family). Moderate depression was seen in 17% of participants. Over 83% of our study population is aged 21 to 40 years, 15% between ages 41 and 60 years, and only 2% ranging between ages 1 and 20. A total of 80% of the population belonged to a low socioeconomic status, and 55% of participants abused opium, heroin, or brown sugar, followed by white crystal use in 37% of the study population. The majority reported the drug abuse duration of 1-5 years (70%). CONCLUSION:  Stigma in its various forms affects the drug abuser undergoing treatment. It results in low self-esteem and mild depression. Individuals from the broader socioeconomic range can be added in future studies, and a larger population can be studied by collecting data from other tertiary care hospitals and mental healthcare facilities. They can be assessed for factors contributing to their addiction and the challenges they had to go through to get the help they needed.