Hedges, Mary S

Objectives: Psychological health changes are known to occur during perimenopause, but the extent to which these differ from premenopause remains unclear. This study aimed to assess psychological symptoms during perimenopause compared with premenopause and evaluate differences by country. Methods: Flo app users aged 35 years or above not taking hormonal contraception or hormone therapy were included. The psychological domain of the Menopause Rating Scale (range 0-16) and symptoms within this domain of depressive mood, irritability, anxiety, and exhaustion (range 0-4 each) were evaluated. Participants in perimenopause were compared with those in premenopause (self-reported not in perimenopause or postmenopause). Results: A total of 7,975 women were included, with 2,353 in perimenopause (mean age 45 years [SD±4.5]) and 5,622 in premenopause (39 y [SD±4.0]). Psychological Menopause Rating Scale scores in the perimenopause group were significantly higher (7.3 [SD±3.56]) than in the premenopause group (4.8 [SD±3.56]; P <0.001). The individual symptoms of depressive mood, irritability, anxiety, and exhaustion were also higher in the perimenopause group ( P <0.001, for all respectively), with the largest difference being exhaustion. These findings remained after adjusting for known confounders, including an existing diagnosis of anxiety or depression. Geographic analysis included 20 countries across 6 continents, with significant differences identified between countries for the overall psychological symptom domain score and all individual symptoms. Conclusion: Significantly greater psychological symptom burden was identified in the perimenopause group compared with the premenopause group, with the greatest difference noted for the individual symptom of exhaustion. Differences in symptom burden were also identified by country.

Objective: Perimenopause is the time leading up to a woman’s last menstrual cycle and includes the 12 months afterward. Studies that systematically compare perimenopause symptoms across diverse cultural and geographic settings are lacking. This study, utilizing data from Flo, an international mobile health application, aimed to assess global knowledge and symptom experiences related to perimenopause. Methods: This cross-sectional survey was conducted via the Flo application, offered to users aged 18 years and above. The primary endpoints were knowledge of perimenopause symptoms from all survey participants, and self-reported perimenopause symptoms for survey participants aged 35 years and above. Secondary analyses compared knowledge scores and symptoms across geographic regions. Results: A total of 17,494 women from 158 countries were included. Commonly recognized perimenopause symptoms included hot flashes (71%), sleep problems (68%), and weight gain (65%). Of the participants, 12,681 were aged 35 years or above, with the most common self-reported symptoms being fatigue (83%), physical and mental exhaustion (83%), irritability (80%), depressive mood (77%), sleep problems (76%), digestive issues (76%), and anxiety (75%). This pattern of symptoms was similar among those who self-reported being in perimenopause, though higher than in those not in perimenopause. International variation in perimenopause symptom knowledge and symptoms experienced was noted ( P <0.001). Conclusions: This survey highlights a discordance between perimenopause knowledge and actual symptoms experienced across diverse global populations. While hot flashes were the most widely recognized symptom, respondents aged 35 years or above most commonly reported experiencing fatigue, physical and mental exhaustion, and irritability.

Background: Home telemetry has been shown to reduce 30-day readmissions in patients at high risk for readmission. It remains unclear whether this finding is due to the telemetry itself or the nurse contact that follows detection of an abnormal parameter. Purpose: This study was a subgroup analysis from a prior trial comparing patients on home telemetry for 30 days to usual care after discharge to determine if nurse contact affected readmission rates. Methods: Patients randomized to telemetry who had at least 1 nurse contact were compared to those who had none to see if the contact reduced the rate of readmissions. Results: Of 449 home telemetry patients, 292 (65.0%) received 1 or more nurse contacts. Single and multivariable logistic regression models exploring the association of contact with 30-day readmission did not find any statistically significant associations of nurse contact with readmission (all unadjusted P ≥ .13, all adjusted P ≥ .18). Conclusion: Our subset analysis did not show that the nurse contact was the factor that reduced readmission in patients on home telemetry.

Abstract Objective Metabolic dysfunction–associated steatotic liver disease (MASLD) and vasomotor symptoms (VMS) are associated with increased cardiovascular disease risk. Although visceral adiposity has been linked to MASLD and VMS independently, this study aimed to evaluate associations between the two in midlife women. Methods A cross-sectional study of women aged 45-60 years receiving primary care at one of four sites was conducted from March 1 through June 30, 2021. MASLD diagnosis was obtained utilizing the International Classification of Diseases , Ninth Revision and Tenth Revision codes. VMS burden was evaluated with the Menopause Rating Scale and categorized as severe/very severe versus none/mild/moderate. Logistic regression models were used to assess the association between VMS and diagnosed MASLD both univariately and after individually adjusting for several risk factors. Results A total of 4,599 women were included in the final analysis, 304 (7%) of whom had an MASLD diagnosis. On univariate analysis, women with an MASLD diagnosis were more likely to have severe/very severe VMS (odds ratio [OR], 1.50; 95% CI, 1.08-2.08; P = 0.015). However, the association between MASLD diagnosis and severe/very severe VMS was no longer statistically significant after individually adjusting for body mass index (adjusted OR, 1.36; 95% CI, 0.97-1.92) and hypertension (adjusted OR, 1.38; 95% CI, 0.99-1.93). Conclusions The relationship between MASLD and VMS appears to be best explained by other variables including BMI and hypertension. Although they do not appear to be directly linked, given the prevalence of bothersome VMS in midlife women, addressing VMS may enable greater adherence to lifestyle modifications as part of MASLD management.

Abstract Pharmacogenomic (PGx) biomarkers integrated using machine learning can be embedded within the electronic health record (EHR) to provide clinicians with individualized predictions of drug treatment outcomes. Currently, however, drug alerts in the EHR are largely generic (not patient‐specific) and contribute to increased clinician stress and burnout. Improving the usability of PGx alerts is an urgent need. Therefore, this work aimed to identify principles for optimal PGx alert design through a health‐system‐wide, mixed‐methods study. Clinicians representing multiple practices and care settings ( N = 1062) in urban, rural, and underserved regions were invited to complete an electronic survey comparing the usability of three drug alerts for citalopram, as a case study. Alert 1 contained a generic warning of pharmacogenomic effects on citalopram metabolism. Alerts 2 and 3 provided patient‐specific predictions of citalopram efficacy with varying depth of information. Primary outcomes included the System's Usability Scale score (0–100 points) of each alert, the perceived impact of each alert on stress and decision‐making, and clinicians' suggestions for alert improvement. Secondary outcomes included the assessment of alert preference by clinician age, practice type, and geographic setting. Qualitative information was captured to provide context to quantitative information. The final cohort comprised 305 geographically and clinically diverse clinicians. A simplified, individualized alert (Alert 2) was perceived as beneficial for decision‐making and stress compared with a more detailed version (Alert 3) and the generic alert (Alert 1) regardless of age, practice type, or geographic setting. Findings emphasize the need for clinician‐guided design of PGx alerts in the era of digital medicine.