Citations

The iStent series constitutes a range of trabecular bypass minimally invasive glaucoma surgery (MIGS) devices, which offers intraocular pressure (IOP) reduction with favourable safety profiles, in patients with open-angle glaucoma (OAG). Having undergone significant evolution since its initial US FDA-approval in 2012, successive generations address previous limitations, while enhancing IOP-lowering efficacy through device and delivery system design iterations. Longer-term and real-world iStent data demonstrate the durability of IOP- and medication-lowering outcomes with minimal complications, while preliminary studies across a wider spectrum of glaucoma subtypes and severities provide limited evidence of successful outcomes beyond mild-to-moderate OAG, both with and without concomitant cataract surgery. Aqueous humour outflow assessment and novel intra-operative techniques may further facilitate more accurate and effective iStent positioning. Despite typically higher upfront costs, results from both cost-effectiveness and patient-reported outcome studies are encouraging. Combination MIGS with the iStent, leveraging on the multiple mechanisms of actions of various procedures, may provide greater IOP-lowering efficacy without compromising safety. With expanding clinical data and progressive enhancements, iStent technology is likely to remain a key component of the evolving MIGS landscape.

BACKGROUND & OBJECTIVE Sleep-disordered breathing (SDB) may be a remediable contributor to abnormal cognitive outcomes for children with myelomeningocele. We investigated the frequency of SDB among neonates with fetal vs postnatal myelomeningocele repair. METHODS In this nine-center, prospective, observational study, neonates with myelomeningocele born at more than 30 weeks gestational age underwent a 10-hour bedside polysomnogram at at least 35 weeks postmenstrual age, before hospital discharge. The primary outcome was SDB severity, reflected by the apnea-hypopnea index (AHI; number of respiratory events per hour of sleep). Decisions regarding surgical timing (fetal vs postnatal), technique (open fetal vs fetoscopic approach), and SDB treatment were made by the clinical teams. RESULTS Among 173 infants, 92/173 (53%) had SDB (median AHI 22.5, IQR 12.2–44.2). In unadjusted analysis, AHI was higher among the 90 neonates with fetal repair vs 83 with postnatal surgery (median 29, IQR 14–49, vs 19, IQR 10–36, P = .008). In propensity-adjusted multivariable models, prematurity was independently associated with AHI, whereas surgical timing (fetal vs postnatal) was not. Hindbrain herniation, myelomeningocele level, and clinical need for ventriculoperitoneal shunt did not predict AHI in adjusted models. Supplemental oxygen was commonly prescribed, for 44% of fetal vs 39% of postnatal myelomeningocele repair infants (P = .5). CONCLUSIONS SDB affects more than half of neonates with myelomeningocele. The higher AHI after fetal surgery could stem from the elevated incidence of prematurity in this group. As SDB is treatable and has a potential impact on neurodevelopment, routine screening could become an integral part of a strategy to optimize long-term medical and neurodevelopmental outcomes.

Abstract Background Interindividual variation in systolic blood pressure (SBP)–heart rate (HR) coupling reflects differences in autonomic and vascular regulation. The primary objective of this study was to determine whether SBP–HR synchronization identifies distinct hemodynamic phenotypes associated with demographic characteristics and blood pressure (BP) profiles in hypertensive and normotensive individuals. Methods We conducted a cross-sectional cohort analysis of 1,122 adults who underwent continuous 24-hour ambulatory monitoring of SBP, diastolic blood pressure (DBP), and HR in an outpatient clinical setting. Participants were classified as hypertensive or normotensive using guideline-based criteria. The primary exposure variable was SBP–HR synchronization, quantified using zero-lag cross-correlation coefficients. The primary outcomes were demographic characteristics (age, sex, stature) and BP phenotypes, including isolated systolic hypertension (ISH). Unsupervised partitioning around medoids clustering was used to identify synchronization-based phenotypes. Group comparisons were performed using Welch’s ANOVA and χ² testing, with multivariable adjustment for age and sex where applicable. Results All 1,122 participants were included in the final analysis (mean age 60.7 years; 52% female). Three synchronization phenotypes were identified: low, moderate, and high. Compared with the low-synchronization phenotype, the high-synchronization phenotype was younger (55.2 ± 15.0 vs. 66.6 ± 13.9 years), taller (170.4 ± 9.4 vs. 167.4 ± 10.5 cm), more frequently male (56% vs. 38%), and had lower baseline SBP (131.8 ± 17.5 vs. 136.7 ± 24.2 mmHg). Overall hypertension prevalence did not differ across phenotypes; however, ISH was less frequent in the high-synchronization phenotype (15.7% vs. 23.4%). Cluster assignments were robust across sensitivity analyses. Conclusions SBP–HR synchronization identifies distinct hemodynamic phenotypes associated with age, sex, stature, and BP characteristics. Stronger synchronization reflects a physiological profile consistent with preserved autonomic–vascular integration and lower prevalence of isolated systolic hypertension, supporting its potential role in refined cardiovascular phenotyping.

Abstract Generative artificial intelligence (AI) is rapidly populating medical records with synthetic or partially AI-generated content, creating a feedback loop where future models are increasingly at risk of training on uncurated AI-generated data. However, the clinical consequences of this AI-generated data contamination remain unexplored. Here, we show that in the absence of mandatory human verification, this self-referential cycle drives a rapid erosion of pathological variability and diagnostic reliability of medical data at population scale. By analysing more than 800,000 synthetic data points across clinical text generation, vision–language reporting, and medical image synthesis, we find that models progressively converge toward generic phenotypes regardless of the model architectures. Specifically, rare but critical findings, including pneumothorax and effusions, vanish from the synthetic content generated by AI models, while demographic representations skew heavily toward middle-aged male phenotypes. Crucially, this degradation is masked by false diagnostic confidence. Models continue to issue reassuring reports while failing to detect life-threatening pathology, with false reassurance rates tripling to 40%. Blinded physician evaluation confirms that this decoupling of confidence and accuracy renders AI-generated documentation clinically useless after just two generations. We systematically evaluate three mitigation strategies that can be easily integrated into existing clinical workflows, finding that while synthetic volume scaling fails to prevent collapse, mixing real data with quality-aware filtering effectively preserves diversity. Ultimately, our results suggest that without policy-mandated human oversight, the deployment of generative AI threatens to degrade the very healthcare data ecosystems it relies upon.

Abstract Background The Alzheimer's disease (AD) Braak staging is a key framework for classifying tau pathology progression in AD based on histopathological post‐mortem brain examinations. However, adapting it to PET imaging can be challenging due to differences in tracer uptake patterns and binding properties, which affect sensitivity, specificity, and regional staging. This study compares Braak staging across four tau PET tracers: Flortaucipir, MK6240, PI2620, and RO948. Methods We assessed 90 participants across the AD spectrum (46 CU, 31 MCI, 13 dementia; mean age 66.1 ± 7.8) using Aβ PET and four tau PET tracers: (Flortaucipir, MK6240, PI2620, and RO948). Braak positivity was defined based on Aβ− CU individuals (mean +2.5 SD, SUVR). To evaluate systematic bias and agreement between tracers, we computed pairwise differences at corresponding Braak stage estimates and applied the Bland‐Altman method to assess mean bias and limits of agreement. Additionally, Tau PET Braak region trajectories were modeled as functions of Aβ burden (Centiloid scale) using the Lowess method. Results Braak stage trajectories as a function of Aβ differ depending on the tracer and the sequential order of abnormality is highly variable. For instance, while for MK6240, RO948 and PI2620, Braak I is the first region to became abnormal, for Flortaucipir the earliest region to became abnormal is Braak IV (Figure 1). This variable pattern of abnormality impacts in the concordance of Braak staging between tracers with the highest Braak staging agreement resulting in concordance levels of approximately 70%. The highest levels of agreement between tracers usually happen at Braak 0 or Braak IV‐V, with intermediate stages showing very low concordance (Figure 2). The Bland‐Altman analysis identified wide limits of agreement, suggesting high variability and high tracer‐specific differences (Figure 3). On the other hand, it also identified that mean differences between tracers were small, indicating minimal systematic bias. Conclusion These preliminary findings reveal discrepancies in Braak staging when comparing Flortaucipir, MK6240, PI2620 and RO948. These findings suggest that while the tracers provide comparable stages on average, they may not be fully interchangeable in individual cases.