Citations

Abstract Background Right ventricular (RV) systolic function is an independent predictor of outcome, but a robust automated method of quantitation is lacking. Purpose To develop and validate a deep learning model for quantifying RV systolic function from 2D echo clips and assess its prognostic value in various loading states and left-heart disease. Methods A deep learning convolutional neural network (CNN) was developed to quantitate RV systolic function using all available apical 4 chamber (A4C) views from 13,039 patients (61,187 A4C video clips) in a US institution. Videos were converted to frames of 256x256 grayscale pixels, with graphics, including the ECG, removed. The model used the S3D architecture, a 3D-CNN with many of the spatial and temporal convolutions separated. RV free wall longitudinal strain (RVFWLS) was used to define RV function: normal (≤-25%); mild (-20% to –24%); moderate (-15% to –19%) and severe RV dysfunction (0% to –14%). The AI-estimate was the average of multiple 32-frame segments for each clip identified as an A4C, including both standard and RV-focused variations. The model was validated in four distinct clinical cohorts from independent data sources: 1) 1365 patients referred to an external diagnostic echocardiography lab in a different US state; 2) 569 patients recruited prospectively with known or suspected pulmonary hypertension (PH); 3) 416 patients with moderate or greater tricuspid valve regurgitation (TR); 4) 872 patients imaged at an Eastern European University with left-sided cardiac diseases (valvular disease, cardiomyopathies, etc.), athletes, or healthy volunteers. Results Model output was strongly correlated with the presence of RV dysfunction by manual measurement [AUC 0.907 (95% CI: 0.888-0.926)] in the internal validation set. Results were similar in an external validation US cohort [N=1365; AUC 0.919 (95% CI: 0.899-0.939)]. When the model was applied to 569 patients with known or suspected PH, presence and severity of the AI measures of RV dysfunction were strongly associated with functional class, 6 min walk distance, NT-proBNP levels and right heart failure (p<0.001). The presence and severity of RV dysfunction (as categorized by the AI model) was strongly associated with all-cause mortality in patients with PH (Figure 1A) and in patients with significant TR (Figure 1B). The European cohort was a geographically and institutionally distinct cohort with a low prevalence of >mild TR (10.8%) or PH (6.4%). In this cohort the AI model predicted a reduced RVEF (< 45%) with an AUC of 0.864 (95% CI: 0.831-0.898) and associated with both all-cause mortality (Figure 2A) and a composite endpoint of heart failure hospitalization or death (Figure 2B). Conclusions A fully automated, AI-based assessment of RV systolic function, using 2D apical 4 chamber echo views alone, is highly feasible and can accurately categorize disease severity and predict outcome across a wide spectrum of cardiovascular conditions.Figure 1 Figure 2

Resistant hypertension (RH) is a high-risk phenotype characterized by blood pressure readings ≥130/80 mmHg despite maximally tolerated therapy with three antihypertensive agents, including a diuretic, or controlled blood pressure requiring four or more medications. The diagnosis of RH requires a structured evaluation that confirms accurate blood pressure measurement, excludes pseudoresistance—particularly nonadherence and white coat hypertension—and identifies secondary causes such as obstructive sleep apnea, primary aldosteronism, renovascular disease, pheochromocytoma, and Cushing syndrome. RH arises from overlapping mechanisms, including activation of the renin–angiotensin–aldosterone system (RAAS), sympathetic overactivity, arterial stiffness, volume expansion, and immune-mediated pathways. Management begins with lifestyle modification and optimized triple therapy, followed by mineralocorticoid receptor antagonists as the preferred fourth-line treatment. Emerging pharmacological options, such as sodium–glucose cotransporter-2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, endothelin receptor antagonists, aldosterone synthase inhibitors, and angiotensin receptor and neprilysin inhibitors (ARNIs), offer additional therapeutic potential; meanwhile, device-based interventions, including renal denervation and baroreflex activation therapy, have shown sustained blood pressure reductions in selected patients. Future directions highlight precision medicine, digital health technologies, and artificial intelligence as methods to improve diagnosis, guide individualized therapy, and enhance long-term blood pressure control.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Objective: Epidemiological data have suggested that late-life depression (LLD) occurs as a consequence of cerebrovascular and neurodegenerative disorders, but there is also some evidence suggesting that the relationship may occur in the other direction, namely that LLD may be a risk factor for cerebrovascular and neurodegenerative disorders. However, the neurobiological basis of these associations remain unclear. This study investigated the associations of LLD with markers of cerebrovascular pathology, brain volumes, and cortical thickness from 3-Tesla brain magnetic resonance imaging (MRI). Methods: Participants from the Atherosclerosis Risk in Communities Study received brain MRI scans in late-life (ages 67-90). The following neuroimaging outcomes were assessed: cortical infarcts, lacunar infarcts, any microhemorrhages, lobar microhemorrhages, subcortical microhemorrhages, white matter hyperintensity volume, total and regional brain volumes (z-scores), and total average and regional cortical thickness (z-scores). At the same visit, LLD was evaluated with the 11-item Center for Epidemiological Studies Depression Scale (CES-D) and defined as CES-D score≥9. Associations between LLD and neuroimaging outcomes were examined using logistic and linear regression models, and were adjusted for age, race-center, sex, education level, vascular risk factors, stroke, cognitive status, APOE e4 carrier status, and total intracranial volume when assessing volumes. Results: Among 1,857 participants, the median age was 76 years, 59.5% were female, 28.3% were Black, and 6.8% had LLD. LLD was not associated with infarcts or microhemorrhages. There was no evidence of an association between LLD and total white matter hyperintensity volume or total average cortical thickness. However, LLD was independently associated with smaller volume (SD) of the rostral anterior cingulate (b 1 : -0.18; 95% CI: -0.33, -0.04) and greater cortical thickness (SD) in the medial orbitofrontal cortex (b 1 : 0.19; 95% CI: 0.01, 0.38), though effect sizes were small and did not survive correction for multiple comparisons. Conclusion: Findings from this study suggest LLD is not cross-sectionally associated with neuroimaging markers of cerebrovascular disease. While LLD may be linked to subtle volume and cortical thickness changes in specific regions of interest, future longitudinal research is warranted to validate and clarify these associations and explore their potentially bidirectional relationship.

Introduction: Optimizing patient selection and time-to-intervention will be crucial to the success of future clinical trials seeking to implement therapies and improve intracerebral hemorrhage (ICH) patient outcomes. Automated and accurate ICH and perihematomal edema (PHE) volumetry carries significant potential to strengthen trials targeting ICH and PHE expansion. Aims: The Quantification of Hematoma and Perihematomal Edema Volumes in Intracerebral Hemorrhage (QUANTUM) trial was designed with aims of (1) validating a fully automated artificial intelligence (AI) method for supratentorial, spontaneous ICH and PHE volumetry against the manual and semiautomated quantification methods and (2) establishing a model framework for the translation of AI technology through conduct of a clinical trial under the equivalence hypothesis paradigm. Methods: This trial was a prospective, randomized, clinical study with blinded outcome assessment. Six independent raters were randomized in a 1:1 ratio to ICH and PHE volumetry from non-contrast CT scans in the Virtual International Stroke Trials Archive with either the semiautomated or manual quantification method. The primary outcomes were equivalence between (1)ICH volume measurements on admission (<24h from symptom onset) for the manual versus the fully automated or the sem-automated quantification methods, and (2)PHE volume measurements on day 3 (72±12h from symptom onset) for the manual versus the fully automated or the semiautomated quantification methods. The required sample size was 126 ICH and 126 PHE measurements, based upon a significance level of 0.025 to account for the two equivalence tests. Results: The geometric mean relative discrepancies between the fully automated and the manual ICH and PHE volume measurements did not cross the pre-specified 10% equivalence margin. The geometric mean relative discrepancies between the semiautomated and the manual ICH and PHE volume measurements did cross the pre-specified 10% equivalence margin. The fully automated method (mean 10.0±2.7s/scan) was significantly faster than the manual (mean 189±199 s/scan; P <0.001) and semiautomated (mean 79±68s/scan; P <0.001) methods. Conclusions: ICH and PHE volumes quantified by AI could replace clinician measurements within a 10% error margin and with substantially greater efficiency. The semiautomated method could not replace manual measurements. This trial demonstrated feasibility of the equivalence hypothesis framework for AI validation studies.

Background: In patients with irritable bowel syndrome with constipation (IBS-C), rapid, sustained relief from constipation and abdominal symptoms, such as pain, discomfort, and bloating, can improve quality of life. Objective: This post hoc analysis evaluates the time to constipation and abdominal symptom relief achieved with tenapanor. Design: Post hoc analysis of data pooled from three randomized placebo-controlled studies (phase IIb, T3MPO-1, and T3MPO-2) of tenapanor 50 mg twice daily in patients with IBS-C. Methods: The time to first response for complete spontaneous bowel movement (CSBM) frequency, abdominal pain, discomfort, bloating, and 3-item abdominal score (AS3) were assessed. The AS3 was derived as the average of the weekly scores for abdominal pain, discomfort, and bloating. Cumulative incidences of response over time were estimated using the Kaplan–Meier method. A Cox proportional hazards model was used to assess the effect of baseline and demographic characteristics on the time to first response. Results: Among 1372 patients with IBS-C (684 tenapanor; 688 placebo), median time to first CSBM response was 2 weeks, and median time to abdominal pain, discomfort, bloating, or AS3 response was 4–5 weeks in those treated with tenapanor, with 67.8%–76.7% achieving first response in CSBM frequency and abdominal symptoms by week 12. These time frames were shorter than those observed with the placebo (4 weeks for CSBM and 6–8 weeks for pain, discomfort, bloating, and AS3), of whom 59.1%–69.4% achieved the first response in CSBM and abdominal symptoms by week 12. Higher weekly response rates were observed with tenapanor than with placebo for all endpoints in each week of the 12-week treatment period. Conclusion: This novel post hoc analysis demonstrates that, compared with placebo, tenapanor reduces the time to first response in CSBM frequency and abdominal symptoms and consistently increases the weekly response rate during 12 weeks of treatment. Trial registration: NCT01923428; NCT02621892; NCT02686138.

Abstract Purpose Professional identities impact professional boundaries and hierarchies, influencing how physicians approach collaboration. Despite the growing emphasis on developing students to become effective collaborators, little is known about how other health professionals (OHPs) shape students' professional identity formation (PIF). This study explored how interacting with OHPs during clinical care contributed to medical students' construction of what it means to be a physician. Methods For this constructivist grounded theory study, researchers conducted 20 semi‐structured interviews with medical students during clinical clerkships. Students drew rich pictures representing their interactions with OHPs and described these pictures during their interviews. Interviews were iteratively conducted and analysed, enabling the research team to theorize how interacting with OHPs contributed to medical students' PIF. Results Participants expressed a strong desire to contribute to patient care and described how interprofessional interactions provided opportunities to do so in ways aligned with their current capabilities. These opportunities were often more accessible than the roles and responsibilities of physicians, and participating alongside OHPs fostered participants' sense of their own developing capabilities and belonging on healthcare teams. Interactions with OHPs helped participants to see the expertise of OHPs and the value of collaborating with them in ways that shifted their focus away from becoming independent. Conceptually, participants' interactions with OHPs became both a mirror reflecting their present readiness to meaningfully contribute and a prism through which they could envision their future identities as physicians in new ways. Conclusions Interprofessional interactions influenced medical students' current and future professional identities, enabling students to see themselves as contributors on health care teams and highlighting collaboration and interdependence as core attributes of the physician profession. These findings highlight opportunities to amplify the impact of interprofessional interactions on the PIF of medical students and the need for research into how OHPs view their roles in these processes.

Background Patients with anti-leucine-rich glioma-inactivated 1 (anti-LGI1) autoimmune encephalitis (AIE) frequently present with faciobrachial dystonic seizures (FBDS), which are often under-detected due to their subtle motor features and lack of consistent EEG correlates. Conventional in-hospital monitoring and patient-reported seizure diaries are limited, particularly during nocturnal periods. In this pilot feasibility study, we evaluated the use of a wearable device (Empatica E4) to objectively monitor FBDS-related motor and autonomic activity in seven patients with anti-LGI1 AIE and four control subjects. Methods Wearable recordings included accelerometry (ACC), electrodermal activity (EDA), photoplethysmography (PPG) and skin temperature. A support vector machine-based algorithm was developed to identify disorder-related events using ACC and EDA features. Analyses were restricted to sleep periods to minimise confounding from voluntary movements. Results Pretreatment recordings from two patients (P1 and P2) showed significantly elevated motor event frequency, ACC magnitude and EDA activity compared to controls. Post-treatment recordings demonstrated marked reductions in these metrics, consistent with patient-reported clinical improvement. Other patients showed variable results depending on treatment timing and signal quality. Conclusion Our pilot study demonstrates the feasibility of using wearable technology for objective, real-world monitoring and assessment of patient status in anti-LGI1 AIE. Nocturnal monitoring offers a low-noise baseline for detecting seizure-related activity and may support earlier diagnosis, more accurate evaluation of treatment response and reduced reliance on resource-intensive inpatient evaluations. Future studies should expand monitoring to daytime periods and validate findings against conventional modalities such as video-EEG and electromyography polygraphy.

Abstract Hypoparathyroidism is an endocrine disease caused by insufficient levels of PTH, which acts directly on bone and kidney and indirectly on the intestine to regulate calcium and phosphate balance. In clinical trials, palopegteriparatide (TransCon PTH) treatment enabled independence from conventional therapy (no active vitamin D, ≤600 mg/d calcium) and maintained serum biochemistries within normal ranges. The current analyses describe patterns of change in BMD, serum bone turnover markers, and serum and urine calcium in adults with chronic hypoparathyroidism treated with palopegteriparatide through 3 years of the PaTH Forward trial. Baseline BMD Z-scores for the LS, TH, FN, and 1/3 distal radius were above zero, indicating bone mass exceeding age-adjusted normative values. BMD decreased from these elevated baseline levels with palopegteriparatide treatment, with larger reductions during the first 26 weeks and modest declines thereafter. Mean BMD Z-scores at week 162 remained above zero for all 4 sites. Participants with lower baseline BMD (Z-scores below −1 and T-scores below −2.5) generally exhibited lesser declines in BMD versus those with higher baseline BMD. Palopegteriparatide treatment was associated with early increases in bone resorption (serum C-terminal telopeptide of type I collagen, CTx) and bone formation (serum procollagen type 1 N-terminal propeptide, P1NP) that peaked at weeks 12 and 26, respectively, followed by declines to levels moderately higher than baseline at week 162. Mean CTx and P1NP in the overall population and the subgroup of postmenopausal women were below their upper limits of normal from weeks 58-162. At week 162, mean serum and median urine calcium remained within normal ranges and 91% of participants were independent from conventional therapy. These results suggest that long-term palopegteriparatide therapy in adults with chronic hypoparathyroidism gradually returns the skeleton toward its natural state thereby enhancing the skeleton’s contribution to calcium homeostasis.

Humility is one of the most powerful and sometimes least understood virtues we can possess. It is often misinterpreted as a sign of weakness, especially today, where self-promotion is encouraged and celebrated. Many people view humility as “thinking less of ourselves.” In truth, humility is not thinking less of oneself; rather it is appropriately thinking less about oneself. Our ability as caregivers in putting the needs of the patient at the center of all we do is enhanced through our humility. A steady focus on the needs of the patient helps us gain an honest assessment of both our strengths and limitations. Studies have shown that patient outcomes and experiences are strongly associated with provider humility. This article aims to shine a light on the power of humility and its impact on patient experience, psychological and cultural safety, and the provider-patient relationship.