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ObjectiveTo compare clinical characteristics, treatment patterns, and 30-day all-cause readmission and mortality between patients hospitalized for heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic.Patients and methodsThe study was conducted at 16 hospitals across 3 geographically dispersed US states. The study included 6769 adults (mean age, 74 years; 56% [5033 of 8989] men) with cumulative 8989 HF hospitalizations: 2341 hospitalizations during the COVID-19 pandemic (March 1 through October 30, 2020) and 6648 in the pre-COVID-19 (October 1, 2018, through February 28, 2020) comparator group. We used Poisson regression, Kaplan-Meier estimates, multivariable logistic, and Cox regression analysis to determine whether prespecified study outcomes varied by time frames.ResultsThe adjusted 30-day readmission rate decreased from 13.1% (872 of 6648) in the pre-COVID-19 period to 10.0% (234 of 2341) in the COVID-19 pandemic period (relative risk reduction, 23%; hazard ratio, 0.77; 95% CI, 0.66 to 0.89). Conversely, all-cause mortality increased from 9.7% (645 of 6648) in the pre-COVID-19 period to 11.3% (264 of 2341) in the COVID-19 pandemic period (relative risk increase, 16%; number of admissions needed for one additional death, 62.5; hazard ratio, 1.19; 95% CI, 1.02 to 1.39). Despite significant differences in rates of index hospitalization, readmission, and mortality across the study time frames, the disease severity, HF subtypes, and treatment patterns remained unchanged (P>0.05).ConclusionThe findings of this large tristate multicenter cohort study of HF hospitalizations suggest lower rates of index hospitalizations and 30-day readmissions but higher incidence of 30-day mortality with broadly similar use of HF medication, surgical interventions, and devices during the COVID-19 pandemic compared with the pre-COVID-19 time frame.

Objectives: To identify patient characteristics, health concerns, and barriers to care based on overweight or obesity. Methods: A 50-question anonymous survey was administered to patients. Data were compared by body mass index (BMI). Results: Among 3976 distributed surveys, 899 were returned and 682 were analyzed. Most respondents were women (60%), White (94%), and married/partnered (65%) and had some college education (80%). Younger and unmarried persons had higher BMI (P <.001). Concern for quality of life (P <.001) and importance of lifestyle changes (P =.006) increased with BMI, but confidence in making changes decreased as BMI increased (P <.001). Perceived good health decreased with increasing BMI (P <.001), whereas depression and other comorbid conditions increased. Self-esteem decreased and stigma increased with higher BMI (both P <.001). Weight discussions with clinicians (P <.001) and belief that clinicians should be involved in weight management (P =.002) increased with BMI, yet self-perception of being judged by clinicians also increased (P <.001). As BMI increased, delays in seeking health care increased (P <.001). Conclusions: This survey study highlights perceived health concerns and barriers to care among persons with overweight and obesity. With higher BMI, self-esteem decreased, and stigma, self-perception of poor health, perception of being judged by clinicians, and delay in seeking medical care increased. [ABSTRACT FROM AUTHOR]

Background and Objectives: Proteomics encompasses the exploration of protein composition, regulation, function, and pathways. Its influence spans diverse clinical fields and holds promise in addressing various women's health conditions, including cancers, osteoporosis, and cardiovascular disorders. However, no comprehensive summary of proteomics and menopausal health exists. Our objective was to summarize proteomic profiles associated with diseases and disorders in peri- and postmenopausal women. Materials and Methods: We conducted a comprehensive search of databases including PubMed, Google Scholar, the Cochrane database, Elsevier, and ScienceDirect until 2022. A total of 253 studies were identified, and 41 studies met the inclusion criteria to identify data of interest. These included the study design, disease, and proteomics/proteins of significance, as described by the authors. Results: The 41 studies covered diverse areas, including bone disorders (10 studies), cardiovascular diseases (5 studies), oncological malignancies (10 studies), and various conditions, such as obesity, nonalcoholic liver disease, the effects of hormone replacement therapy, and neurological diseases (16 studies). The results of our study indicate that proteomic profiles correlate with heart disease in peri- and postmenopausal women, with distinct sex differences. Furthermore, proteomic profiles significantly differ between women with and without osteoporosis. Additionally, patients with breast, ovarian, and endometrial cancer exhibit notable variations in proteomic profiles compared to those without these conditions. Conclusions: Proteomics has the potential to enhance risk assessment and disease monitoring in peri- and postmenopausal women. By analyzing unique protein profiles, clinicians can identify individuals with heightened susceptibility to specific diseases or those already affected by established conditions. This review suggests that there is sufficient preliminary data related to proteomics in peri- and postmenopausal women for early identification of cardiovascular disease, osteoporosis, and cancers, disease monitoring, and tailoring individualized therapies. Rigorous validation studies involving large populations are essential before drawing definitive conclusions regarding the clinical applicability of proteomic findings. [ABSTRACT FROM AUTHOR]

Background: Before the COVID-19 pandemic began, medical staff and academic department workers reported increasing levels of stress and burnout because of strain on the health care system. The COVID-19 pandemic exacerbated this strain and introduced several novel stressors, which included transitioning to remote work. Safe and scalable strategies are needed to help health care workers cope with these stressors. Aromatherapy may help address this need. Objectives: To assess the effect of 2 aromatherapy interventions (essential oil blends termed STILL and FOCUS) on perceived mental/psychological health parameters for academic department workers working from home during the COVID-19 pandemic. Methods: Participants were advised to use STILL for 5 days (Monday through Friday). After a 2-day washout period (Saturday and Sunday), participants were instructed to use FOCUS for 5 days (Monday through Friday). Participants completed a visual analog scale survey evaluating restlessness, fatigue, anxiety, stress, happiness, energy, relaxation, calmness, and well-being before and after each of the 2 intervention periods. Results: Twenty academic department remote workers participated in the study. Mental/psychological health surveys were completed by 6 participants before and after using STILL and by 10 before and after using FOCUS. Five participants answered all survey questions before and after both interventions. Although mean (SD) perceived stress scores improved after both the STILL (4.3 [2.3] vs 1.8 [1.7], P =.03) and FOCUS (2.9 [2.3] vs 1.5 [1.4], P =.02) interventions, this improvement was not statistically significant after Bonferroni correction (adjusted α =.006). Most participants (73.3%) reported that participating in the study was worthwhile, and 81.3% indicated that they would recommend aromatherapy to others. Conclusions: The STILL and FOCUS aromatherapy interventions did not significantly improve mental/psychological health parameters for remote academic department workers, although perceived stress was marginally improved and participants reported a perceived benefit from using aromatherapy. [ABSTRACT FROM AUTHOR]

BACKGROUND Uncertainty remains over the relationship between blood pressure (BP) variability (BPV), measured in hospital settings, and clinical outcomes following acute ischemic stroke (AIS). We examined the association between within-person systolic blood pressure (SBP) variability (SBPV) during hospitalization and readmission-free survival, all-cause readmission, or all-cause mortality 1 year after AIS. METHODS In a cohort of 862 consecutive patients (age [mean ± SD] 75 ± 15 years, 55% women) with AIS (2005–2018, follow-up through 2019), we measured SBPV as quartiles of standard deviations (SD) and coefficient of variation (CV) from a median of 16 SBP readings obtained throughout hospitalization. RESULTS In the cumulative cohort, the measured SD and CV of SBP in mmHg were 16 ± 6 and 10 ± 5, respectively. The hazard ratios (HR) for readmission-free survival between the highest vs. lowest quartiles were 1.44 (95% confidence interval [CI] 1.04–1.81) for SD and 1.29 (95% CI 0.94–1.78) for CV after adjustment for demographics and comorbidities. Similarly, incident readmission or mortality remained consistent between the highest vs. lowest quartiles of SD and CV (readmission: HR 1.29 [95% CI 0.90–1.78] for SD, HR 1.29 [95% CI 0.94–1.78] for CV; mortality: HR 1.15 [95% CI 0.71–1.87] for SD, HR 0.86 [95% CI 0.55–1.36] for CV). CONCULSIONS In patients with first AIS, SBPV measured as quartiles of SD or CV based on multiple readings throughout hospitalization has no independent prognostic implications for the readmission-free survival, readmission, or mortality. This underscores the importance of overall patient care rather than a specific focus on BP parameters during hospitalization for AIS. [ABSTRACT FROM AUTHOR]

Aims: To know the distribution and antifungal susceptibility pattern of Candida species in neonatal septicemia cases. Materials and Methods: In a prospective analysis blood samples from 825 clinically suspected cases of neonatal septicemia, collected aseptically, were cultured to look for the role of Candida spp. in septicemia. Candida isolates were speciated by germ tube test, Hi-CHROME agar, sugar fermentation, and sugar assimilation tests using standard protocol. All the Candida isolates were tested for antifungal susceptibility to fluconazole by the Disk Diffusion (DD) method and broth micro dilution-minimum inhibitory concentration (BMD-MIC) method using NCCLS guidelines. Results: Isolation rate of Candida from neonatal septicemia cases was 8.1%. Most common isolate was C. tropicalis (61.19%), followed by C. albicans (19.40%), C. glabrata (11.94%), C. parapsilosis (5.97%) and C. guillermondii (1.49%). Low birth weight and previous antibiotic prophylaxis was found in 100% cases. Crude mortality rate was 50.1%. By DD method, 95.53% of the Candida isolates were sensitive to fluconazole. A discrepancy between DD method and BMD-MIC method was noted in 4.47% strains. One isolates each of C. tropicalis, C. albicans, and C. glabrata showed discrepancy. Conclusion: Nonalbicans Candida has emerged as an important cause of neonatal septicemia. Routine susceptibility testing of Candida isolates by DD method should be confirmed by BMD-MIC method. Fluconazole can be used as empirical therapy for neonatal candidemia at our center.

Background: Despite malnutrition being associated with increased mortality and morbidity, there continues to be great difficulty in defining criteria and implementing widespread screening. Tools used to diagnose decreased fat‐free mass (FFM [sarcopenia]) should be easy to use, relatively inexpensive, and safe. Bioelectrical impedance analysis (BIA) has the potential to meet these criteria, but reliability across body mass index (BMI) classes is a concern. Methods: A total of 176 healthy ambulatory participants (aged 18–65 years) were recruited equally (n = 44) in 4 BMI categories: (1) 18.5–24.9, (2) 25.0–29.9, (3) 30–34.9, and (4) ≥35.0. Participants were fasting overnight and had S‐MFBIA (InBody 770) measurements the next morning, with DXA being performed subsequently within 30 minutes. Results: The measurement (mean ± SD) for FFM with DXA was 52.8 ± 11.0, and BIA was 53.6 ± 11.0. Delta (S‐MFBIA vs DXA) was 0.8 ± 2.2 (5% limits of agreement −3.5 to +5.2), and concordance correlation coefficient (CCC) was 0.98 (95% CI, 0.97–0.98). The measurements (mean ± SD) for PBF with DXA was 37.5 ± 10.6% and S‐MFBIA was 36.6 ± 11.3%. Delta (S‐MFBIA vs DXA) was −0.9 ± 2.6 (5% limits of agreement 6.0 to +4.2), and CCC was 0.97 (95% CI, 0.96–0.98). The CCC according to the 4 BMI groups for FFM and PBF was between 0.96–0.98 and 0.90–0.94, respectively. Conclusions: FFM and PBF measured by S‐MFBIA had good agreement with DXA across all BMI categories measured in the current study of ambulatory participants. [ABSTRACT FROM AUTHOR]

Purpose: Experiential learning has been suggested as a framework for planning continuing medical education (CME). We aimed to (1) determine participants' learning styles at traditional CME courses and (2) explore associations between learning styles and participant characteristics. Materials and methods: Cross-sectional study of all participants (n = 393) at two Mayo Clinic CME courses who completed the Kolb Learning Style Inventory and provided demographic data. Results: A total of 393 participants returned 241 surveys (response rate, 61.3%). Among the 143 participants (36.4%) who supplied complete demographic and Kolb data, Kolb learning styles included diverging (45; 31.5%), assimilating (56; 39.2%), converging (8; 5.6%), and accommodating (34; 23.8%). Associations existed between learning style and gender (p = 0.02). For most men, learning styles were diverging (23 of 63; 36.5%) and assimilating (30 of 63; 47.6%); for most women, diverging (22 of 80; 27.5%), assimilating (26 of 80; 32.5%), and accommodating (26 of 80; 32.5%). Conclusions: Internal medicine and psychiatry CME participants had diverse learning styles. Female participants had more variation in their learning styles than men. Teaching techniques must vary to appeal to all learners. The experiential learning theory sequentially moves a learner from Why? to What? to How? to If? to accommodate learning styles. [ABSTRACT FROM AUTHOR]

Background: Asthma is one of the most common chronic diseases of childhood and a major health problem not only in India but globally. Despite multifold increase in prevalence, there is paucity of data on bronchial asthma from non‑metro cities. The objectives were to find prevalence of bronchial asthma and various risk factors that are associated in this age group and determine the extent of under diagnosis. Materials and Methods: A cross‑sectional study involving 927 students from four government and three private schools was conducted using International Study of Asthma and Allergies in Childhood questionnaire. Results: Prevalence of bronchial asthma in adolescents was 13.1% (n = 121) of which 10.3% had episodes in the past 1 year. Prevalence was higher among males (8.77%) compared to females (4.33%). About 77.7% of total asthmatics were newly diagnosed cases. Prevalence was significantly higher among those having pets at home (P < 0.001), belonging to higher socioeconomic status (P = 0.021), using smoke‑producing fuel at home (firewood/cow dung/kerosene; P = 0.032), and with history of smoking among family members (P = 0.035). Among current asthmatics, 72.3% reported cold/rhinitis (54.6% in March–May duration), 63.6% nocturnal dry cough, 50.5% sleep disturbances, and 38.9% speech disturbances in the past 1 year. Conclusion: The study shows higher prevalence of bronchial asthma in school‑going population (11–16 years) compared to other parts of Northern India possibly attributable to rapid industrialization and post harvesting season when the study was carried out. Preventive interventions need to be taken to reduce disease burden at community level. [ABSTRACT FROM AUTHOR]