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Objectives: As transgender individuals age, they are at risk for neurocognitive disorders which pose not only medical but also bioethical questions. We present a case study of a transgender older adult with dementia who experienced changes in gender identity and explore the bioethical implications of identity over time, including end-of-life care. Methods: We reviewed clinical notes and relevant medical history to describe the transition and detransition process and examined ethical frameworks related to autonomy, psychological continuity, and transgender care. Results: The individual transitioned as a transgender woman in mid-life but detransitioned shortly before being diagnosed with dementia. This case highlighted conflicts between precedent autonomy and current gender identity in the context of neurocognitive decline and end-of-life care. Conclusions: The case underscores the complexity of managing gender identity in transgender older adults with dementia, emphasizing the need for personalized and ethically sound care plans. Clinical Implications: Clinicians should be vigilant about the impact of neurocognitive disorders on gender identity, balancing respect for patients' prior decisions with their current values, and develop personalized end-of-life care plans that honor the evolving identities and preferences of transgender individuals with dementia. [ABSTRACT FROM AUTHOR] more...

Objectives Methods Results Conclusion Interpatient variability in bipolar I depression (BP‐D) symptoms challenges the ability to predict pharmacotherapeutic outcomes. A machine learning workflow was developed to predict remission after 8 weeks of pharmacotherapy (total score of ≤8 on the Montgomery Åsberg Depression Rating Scale [MADRS]).Supervised machine learning models were trained on data from BP‐D patients treated with olanzapine (N = 168) and were externally validated on patients treated with olanzapine/fluoxetine combination (OFC; N = 131) and lamotrigine (LTG; N = 126). Top predictors were used to develop a prognosis rule informing how many symptoms should change and by how much within 4 weeks to increase the odds of achieving remission.An AUC of 0.76 (NIR:0.59; p = 0.17) was established to predict remission in olanzapine‐treated subjects. These trained models achieved AUCs of 0.70 with OFC (NIR:0.52; p < 0.03) and 0.73 with LTG (NIR:0.52; p < 0.003), demonstrating external replication of prediction performance. Week‐4 changes in four MADRS symptoms (reported sadness, reduced sleep, reduced appetite, and concentration difficulties) were top predictors of remission. Across all pharmacotherapies, three or more of these symptoms needed to improve by ≥2 points at Week‐4 to have a 65% chance of achieving remission at 8 weeks (OR: 3.74, 95% CI: 2.45–5.76; p < 9.3E‐11).Machine learning strategies achieved cross‐trial and cross‐drug replication in predicting remission after 8 weeks of pharmacotherapy for BP‐D. Interpretable prognoses rules required only a limited number of depressive symptoms, providing a promising foundation for developing simple quantitative decision aids that may, in the future, serve as companions to clinical judgment at the point of care. [ABSTRACT FROM AUTHOR] more...

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. [ABSTRACT FROM AUTHOR] more...

Background: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them. Aims: To (i) correlate speech features with manic-depressive symptom severity in BD, (ii) develop predictive models for diagnostic and treatment outcomes, and (iii) determine the most relevant speech features and tasks for these analyses. Methods: This naturalistic, observational study involved longitudinal audio recordings of BD patients at euthymia, during acute manic/depressive phases, and after-response. Patients participated in clinical evaluations, cognitive tasks, standard text readings, and storytelling. After automatic diarization and transcription, speech features, including acoustics, content, formal aspects, and emotionality, will be extracted. Statistical analyses will (i) correlate speech features with clinical scales, (ii) use lasso logistic regression to develop predictive models, and (iii) identify relevant speech features. Results: Audio recordings from 76 patients (24 manic, 21 depressed, 31 euthymic) were collected. The mean age was 46.0 ± 14.4 years, with 63.2% female. The mean YMRS score for manic patients was 22.9 ± 7.1, reducing to 5.3 ± 5.3 post-response. Depressed patients had a mean HDRS-17 score of 17.1 ± 4.4, decreasing to 3.3 ± 2.8 post-response. Euthymic patients had mean YMRS and HDRS-17 scores of 0.97 ± 1.4 and 3.9 ± 2.9, respectively. Following data pre-processing, including noise reduction and feature extraction, comprehensive statistical analyses will be conducted to explore correlations and develop predictive models. Conclusions: Automated speech analysis in BD could provide objective markers for psychopathological alterations, improving diagnosis, monitoring, and response prediction. This technology could identify subtle alterations, signaling early signs of relapse. Establishing standardized protocols is crucial for creating a global speech cohort, fostering collaboration, and advancing BD understanding. [ABSTRACT FROM AUTHOR] more...

Major depressive disorder (MDD) is a severe illness that afflicts about 16.6% of people over their lifetime. MDD is highly correlated with suicidality, and often first presents in adolescence. Unfortunately, many pediatric patients suffering from MDD go undiagnosed, and current evidence-based treatment options in the U.S. are limited to psychotherapy and two selective serotonin reuptake inhibitors approved by the United States Food and Drug Administration. Molecular mechanisms have been shown to play a role in MDD pathogenesis, progression, and response to medication, yet few studies have explored the role of these pathways in pediatric MDD. In this review, we outline the gravity and importance of MDD in pediatric patients, some challenges in diagnosis and treatment, current treatments available for pediatric patients, and research to investigate differences between pediatric and adult MDD. We hope that this review will provide an outline of the current understanding and treatment of MDD in pediatric patients, and provide thoughtful insights for future work that could advance our understanding of MDD in pediatric populations, and also identify new therapeutic strategies. [ABSTRACT FROM AUTHOR] more...

Pyomyositis due to Gram negative bacteria is rare. Here we describe two cases in immunocompromised hosts . Both were bacteremic with a Gram-negative bacterium and had impaired immunity related to prolonged and ongoing chemotherapy for hematologic malignancies. Both eventually cleared the infection with a combination of local drainage and systemic antibiotics. This unusual diagnosis should be considered in an immunocompromised patient with muscle pain and fever., Competing Interests: None., (© 2023 The Authors.) more...

Tissue engineering endeavors to create replacement tissues and restore function that may be lost through infection, trauma, and cancer. However, wide clinical application of engineered scaffolds has yet to come to fruition due to inadequate vascularization. Here, we fabricate hydrogel constructs using Pluronic(®) F127 as a sacrificial microfiber, creating microchannels within biocompatible, biodegradable type I collagen matrices. Microchannels were seeded with human umbilical vein endothelial cells (HUVEC) or HUVEC and human aortic smooth muscle cells (HASMC) in co-culture, generating constructs with an internal endothelialized microchannel. Histological analysis demonstrated HASMC/HUVEC-seeded constructs with a confluent lining after 7 days with preservation and further maturation of the lining after 14 days. Immunohistochemical staining demonstrated von Willebrand factor and CD31(+) endothelial cells along the luminal surface (neointima) and alpha-smooth muscle actin expressing smooth muscle cells in the subendothelial plane (neomedia). Additionally, the deposition of extracellular matrix (ECM) components, heparan sulfate and basal lamina collagen IV were detected after 14 days of culture. HUVEC-only- and HASMC/HUVEC-seeded microchannel-containing constructs were microsurgically anastomosed to rat femoral artery and vein and perfused, in vivo. Both HUVEC only and HUVEC/HAMSC-seeded constructs withstood physiologic perfusion pressures while their channels maintained their internal infrastructure. In conclusion, we have synthesized and performed microvascular anastomosis of tissue-engineered hydrogel constructs. This represents a significant advancement toward the generation of vascularized tissues and brings us closer to the fabrication of more complex tissues and solid organs for clinical application. more...