Tag: pubmed

J Neuroophthalmol. 2026 Jun 1;46(2):271-278. doi: 10.1097/WNO.0000000000002481.

ABSTRACT

BACKGROUND: The Idiopathic Intracranial Hypertension Treatment Trial’s (IIHTT) objective was to evaluate the efficacy and safety of acetazolamide, combined with a low-sodium weight-reduction diet, in improving visual function in patients with idiopathic intracranial hypertension (IIH) and mild visual loss.

METHODS: To accomplish this, a NEI-sponsored multicenter, double-blind, randomized, placebo-controlled clinical trial was performed at 38 North American clinical sites. A total of 165 participants (161 women; mean age 29 years) meeting the modified Dandy criteria with reproducible mild visual loss (perimetric mean deviation [PMD] -2 to -7 dB) were enrolled. Participants were randomized to acetazolamide or placebo, each combined with a structured dietary program. Acetazolamide was initiated at 1 g/day and titrated weekly to a maximum of 4 g/day. The primary outcome was change in PMD at 6 months. Treatment failure was defined by prespecified reproducible PMD worsening criteria. Secondary outcomes included papilledema grade, OCT metrics, cerebrospinal fluid (CSF) pressure, quality of life, weight change, and headache disability.

RESULTS: Acetazolamide produced greater PMD improvement than placebo (1.43 dB vs 0.71 dB; treatment effect 0.71 dB; P = 0.05) and the result was independent of weight loss. Participants with high-grade papilledema had the greatest benefit (2.27 dB). Acetazolamide significantly improved papilledema grade and OCT optic disc volume and reduced CSF pressure by an additional 60-mm H2O compared with placebo (P = 0.002). Quality-of-life scores improved significantly with improvement in vision being the most important factor. Seven participants experienced treatment failure (6 placebo, 1 acetazolamide). Risk factors for treatment failure were high-grade papilledema, more than 30 transient visual obscurations per month, visual acuity loss, and male sex. Compliance of study drug was high (89% vs 93%). Tolerability was excellent when the maximal tolerated dosage was used with no permanent morbidity.

CONCLUSIONS: Acetazolamide plus diet gave statistically significant improvements of visual function, papilledema, CSF pressure, and quality of life in patients with IIH with mild visual loss. A maximally tolerated dose up to 4 g/day is recommended.

PMID:42133960 | DOI:10.1097/WNO.0000000000002481

Obstet Gynecol. 2026 May 15. doi: 10.1097/AOG.0000000000006320. Online ahead of print.

ABSTRACT

OBJECTIVE: The New York State Safe Motherhood Initiative, a statewide quality-improvement effort, developed a bundle to optimize management of obstetric hemorrhage that was then disseminated and implemented by many hospitals in New York State. The purpose of this study was to evaluate trends in statewide outcomes related to postpartum hemorrhage (PPH) before, during, and after Safe Motherhood Initiative obstetric hemorrhage bundle implementation.

METHODS: Delivery hospitalizations in the 2007-2022 New York State Inpatient Database were analyzed for this repeated ecologic cross-sectional analysis that evaluated outcomes before and after implementation of the Safe Motherhood Initiative obstetric hemorrhage bundle from 2013 to 2015. The New York State Inpatient Database includes discharge data for all inpatient acute care hospitalizations in New York. Trends analysis of PPH diagnoses among all delivery hospitalizations over the study period was first performed. Then, among deliveries complicated by PPH, the rate of the following adverse outcomes was determined by year: 1) transfusion, 2) nontransfusion severe maternal morbidity (SMM), 3) disseminated intravascular coagulation (DIC), and 4) hysterectomy. Analyses were performed with joinpoint regression to determine the average annual percent change (AAPC). Adjusted logistic regression models were additionally performed for each of the adverse outcomes.

RESULTS: Among 3,563,885 delivery hospitalizations, PPH increased continuously from 22 per 1,000 in 2007 to 59 per 1,000 in 2022 (AAPC 6.9%, 95% CI, 6.5-7.5%). In joinpoint analysis, transfusion among delivering patients with PPH increased from 192 per 1,000 in 2007 to 212 per 1,000 in 2013 (AAPC 2.1%, 95% CI, 0.6-6.6%) but then decreased to 174 per 1,000 in 2016 (AAPC -6.8%, 95% CI, -9.5% to -2.1%) before increasing again to 212 per 1,000 in 2022 (AAPC 2.8%, 95% CI, 1.2-8.1%). Severe maternal morbidity increased from 88 per 1,000 in 2007 to 122 per 1,000 in 2014 (AAPC 2.8%, 95% CI, 0.7-7.6%) before decreasing to 76 per 1,000 in 2017 (AAPC -16.3%, 95% CI, -20.8% to -8.4%) before rising again to 88 per 1,000 in 2022 (AAPC 4.4%, 95% CI, 0.1-18.5%). Disseminated intravascular coagulation increased from 54 per 1,000 in 2007 to 90 per 1,000 in 2014 (AAPC 4.5%, 95% CI, 1.3-12.6%), decreased to 53 per 1,000 in 2017 (AAPC -19.3%, 95% CI, -25.3% to -8.9%), and increased without a significant statistical association to 88 per 1,000 in 2022 (AAPC 4.2%, 95% CI, -2.0% to 24.5%). Hysterectomy decreased significantly from 26 per 1,000 in 2013 to 9 per 1,000 in 2022 (AAPC -10.2%, 95% CI, -14.3% to -8.7%). In logistic regression analysis, adjusted odds of severe morbidity from 2016 to 2022 were decreased compared with 2007 after accounting for patient- and hospital-level factors.

CONCLUSION: The initiation of the New York Safe Motherhood Initiative obstetric hemorrhage bundle coincided with decreased risk for a range of adverse outcomes among deliveries complicated by PPH. Decreases in risk continued for approximately 3-4 years after initiation of the program for SMM, DIC, and transfusion. In comparison, hysterectomy decreased continuously until the end of the study period. Case mix and worsening comorbidity may have accounted for later study trends given that adjusted regression models for SMM demonstrated decreased odds of peripartum hysterectomy over the later portion of the study.

PMID:42133948 | DOI:10.1097/AOG.0000000000006320

JMIR Form Res. 2026 May 14;10:e73445. doi: 10.2196/73445.

ABSTRACT

BACKGROUND: US Latine and Hispanic communities face a 1.5 times greater risk of developing Alzheimer disease and related dementia (ADRD) with limited access to culturally and linguistically congruent primary prevention education. The COVID-19 pandemic exacerbated the digital divide, highlighting a need to focus on alternative digital methods for delivering brain health and ADRD primary prevention education. Social media emerged as a promising tool.

OBJECTIVE: The objective of this paper is two-fold. We first describe the development and pilot study of our social media-based Latine-Hispanic Digital Brain Health Program guided by evidence-based frameworks in ADRD. We then present the quantitative and qualitative results from the first 14 months of the program (October 2023-December 2024).

METHODS: We used human-centered design to develop the Digital Alzheimer Health Education Model, which was implemented via 3 social media platforms-Facebook, Instagram, and X (formerly known as Twitter). Our bilingual and bicultural team implemented the model by creating and disseminating tailored educational content in English and Spanish for the resulting Latine-Hispanic Digital Brain Health Program, emphasizing consistency and rapport, storytelling, cultural relevance, linguistic inclusivity, and visual representation. A mixed methods analysis (descriptive statistics and sentiment analysis) was conducted using social media data analytics and users’ comments to guide program evaluation and refinement.

RESULTS: From October 2023 to December 2024, we retained 857 followers across our social media platforms (Instagram: n=534; Facebook: n=124; and X: n=199). Growth in follows, consistent reach and engagement, and positive sentiment were observed on Facebook and Instagram. X was not included in the analysis due to data access limitations.

CONCLUSIONS: The development and pilot study of the Latine-Hispanic Digital Brain Health Program have demonstrated potential in leveraging social media to disseminate brain health and ADRD prevention education to the US Latine and Hispanic communities in English and Spanish. Our preliminary findings demonstrate that culturally and linguistically congruent social media-based approaches hold potential to improve engagement with brain health and ADRD primary prevention education among US Latine and Hispanic populations.

PMID:42133941 | DOI:10.2196/73445

JMIR Ment Health. 2026 May 14;13:e92187. doi: 10.2196/92187.

ABSTRACT

BACKGROUND: Digital mental health interventions (DMHIs) have been widely promoted to improve access to mental health care within the UK National Health Service (NHS), particularly following the COVID-19 pandemic. In 2015, a total of 48 technologies were reportedly used in NHS services in England, but over the past decade, substantial changes to regulatory requirements, evidence standards, and procurement processes have reshaped the digital mental health landscape. There is limited clarity regarding which DMHIs are currently being formally procured and funded by NHS mental health services across the United Kingdom.

OBJECTIVE: This study aimed to identify and describe the DMHIs currently procured, contracted, or paid for by NHS mental health service providers in England, Scotland, and Wales for adult common mental health problems and to compare current procurement practices with findings reported in 2015.

METHODS: Freedom of Information requests were submitted to all NHS mental health trusts in England and all health boards in Scotland and Wales. Responses were collated and screened to provide an updated and extended record of which technologies are reportedly procured or paid for by services.

RESULTS: In total, 19 different DMHIs were identified as being procured across mental health service providers for adult common mental health problems at the time of data collection. This demonstrates a substantial reduction in the number of technologies being adopted into practice compared to the 48 reported in England in 2015. The findings reveal several key insights, including that only 2 technologies have remained in use for a decade, and they shed light on the types of technologies being selected and the variations in procurement practices among the 3 national health services.

CONCLUSIONS: Despite the expansion of the digital mental health marketplace, the number of DMHIs formally procured by NHS mental health services has markedly decreased over the past decade. This consolidation may reflect increased selectivity and the adoption of higher-quality products, driven by strengthened regulatory oversight, evidence standards, and national guidance. Although these developments may enhance safety and quality assurance, they also raise important questions about innovation, market sustainability, and equitable access to digital mental health care. Ongoing monitoring of procurement practices is needed to inform policy, service design, and the future development of DMHIs.

PMID:42133938 | DOI:10.2196/92187

JMIR Mhealth Uhealth. 2026 May 14;14:e58908. doi: 10.2196/58908.

ABSTRACT

BACKGROUND: Over the past 2 decades, global rates of cannabis use have risen significantly, especially among young adults. This has corresponded to an increase in cannabis-related problems and hospitalizations. Thus, there has been significant interest in developing new interventions that can help facilitate cannabis cessation and reduce hospitalization rates. Specifically, mobile apps have emerged as scalable and accessible stand-alone or adjunct interventions that can help individuals with cannabis use disorders.

OBJECTIVE: This study aimed to evaluate the quality of free cannabis cessation apps available on both the Apple App Store and Google Play Store, focusing on the analysis of their features, content, and adherence to evidence-based practices.

METHODS: A systematic search was conducted in April 2023 using a variety of keywords. The apps were deemed eligible if they were free, available in English, accessible on both the Apple App Store and the Google Play Store, and related to cannabis cessation. Eligible apps were used for at least 1 month and were rated on the Mobile App Rating Scale by 2 reviewers. Interrater reliability was excellent, with a weighted Cohen κ of 0.893 (95% CI 0.835-0.943).

RESULTS: Four apps were included in the analysis, namely, “Grounded-Quit Weed,” “Quit Weed,” “Marijuana Addiction Calendar,” and “Marijuana Anonymous.” The mean overall quality score of the apps was 3.4 out of 5, indicating poor to acceptable quality. The apps scored the highest on the “functionality” section and the lowest on the “information” section. Of the 4 apps, 3 focused on tracking cannabis use and duration of abstinence, whereas 1 focused on peer support. A limited number of cannabis cessation apps were identified, and those that were available were of low quality due to a lack of evidence-based information.

CONCLUSIONS: This study is the first to evaluate the current availability and quality of mobile apps designed for cannabis cessation. Unlike previous research that broadly assessed cannabis-related mobile apps, this study focuses on the limited number of free cannabis cessation tools, reflecting what is most available to the general population. The findings highlight a significant gap between the growing demand for virtual cessation tools and the quality of existing options. With the rising global prevalence of cannabis use disorders, there is an increasing need for robust, accessible, and evidence-based therapeutic options. While mobile health apps may be a viable option to support cannabis cessation, the current landscape is limited by poor quality apps and a lack of evidence-based information. From a real-world perspective, this study highlights the need for users to exercise caution when relying on current cannabis cessation apps and underscores the urgent need for the development and evaluation of new evidence-based digital interventions.

PMID:42133935 | DOI:10.2196/58908

JMIR Form Res. 2026 May 14;10:e91260. doi: 10.2196/91260.

ABSTRACT

BACKGROUND: Difficulty understanding speech in noisy environments is a primary challenge of hearing impairment, inadequately addressed by hearing aids alone. While auditory training can enhance selective attention and speech perception, current digital programs face poor user adherence and lack realistic 3D spatial audio.

OBJECTIVE: This pilot study evaluated the feasibility, usability, and preliminary efficacy of ARIA (Augmented Reality Immersive Auditory training), a handheld mobile intervention that provides gamified at-home auditory training to middle-aged adults via earbud-delivered spatial audio.

METHODS: In this single-arm, pre-post-follow-up pilot study, 11 adults (mean age 53.0, SD 3.0 y) with functional hearing not requiring amplification completed a 4-week at-home training program using ARIA on provided devices (iPhone 14 Pro, AirPods Pro 2). Speech-in-noise perception was assessed via the Korean Matrix Sentence Test at baseline, 4 weeks, and 8 weeks at 3 signal-to-noise ratios (SNRs; 0 dB, -6 dB, and -9 dB, respectively). Feasibility, usability (System Usability Scale), user experience (Player Experience of Need Satisfaction), in-game performance, and qualitative feedback were collected.

RESULTS: Protocol completion was 100% (11/11), demonstrating technical feasibility. Exploratory efficacy analyses revealed statistically significant speech-in-noise improvements posttraining across all conditions (0 dB: t10=3.43, P=.02; -6 dB: t10=5.34, P<.001; -9 dB: t10=4.34, P=.004). Gains were maintained at the 8-week follow-up. In-game localization improvements correlated significantly with speech perception gains at -6 dB SNR (ρ=0.639; P=.03) and -9 dB SNR (ρ=0.612; P=.045). User experience showed mixed results: the mean System Usability Scale score was 70.2 (SD 19.6; range 47.5-92.5), reflecting substantial individual differences in usability perception. While 72% (n=8) reported difficulties with the augmented reality (AR) environmental setup, 63% reported genuine mastery-driven engagement with core gameplay. Thematic analysis revealed a dissociation between peripheral usability challenges (setup friction, “homework” characterization due to protocol structure) and successful engagement with the training paradigm itself.

CONCLUSIONS: This pilot demonstrated the feasibility of AR-based audio-motor training for at-home delivery and revealed encouraging preliminary efficacy signals, warranting progression to controlled efficacy trials. Formative findings identified specific usability refinements needed for broader implementation, particularly streamlining AR setup while preserving the core gameplay elements that successfully fostered competence and engagement. These insights provide clear guidance for platform optimization and randomized controlled trial design.

PMID:42133934 | DOI:10.2196/91260

Pharm Dev Technol. 2026 May 14:1-23. doi: 10.1080/10837450.2026.2673037. Online ahead of print.

ABSTRACT

Topical administration of non-steroidal anti-inflammatory drugs (NSAIDs) is often limited by poor skin permeability and a short duration of action. Solid lipid nanoparticles (SLNs) represent a promising carrier system capable of enhancing dermal drug delivery while sustaining local therapeutic effects. The present study aimed to formulate and optimize ketoprofen (KP)-loaded SLNs to enhance the drug’s therapeutic efficacy in topical inflammatory conditions. Modeling and optimization of formulation components were performed using a mixture design (MD) approach. SLNs were prepared using two methods: hot melting and solvent evaporation. The prepared formulations were characterized in terms of particle size, zeta potential, entrapment efficiency, and in vitro drug release profiles. Pharmacodynamic evaluation was conducted in rats using the carrageenan-induced paw edema model and compared with a marketed formulation (FASTUM® gel 2.5%).The optimized SLNs exhibited a particle size of 51.9 ± 4.55 nm, a polydispersity index (PDI) of 0.398 ± 0.02, and a zeta potential of -14.2 ± 0.61 mV, indicating acceptable colloidal stability. The optimized KP-SLN formulation produced a significant reduction in paw edema volume (57.65%) in pre-treated rats (P < 0.05), along with significant decreases in inflammatory mediators prostaglandin E₂ (PGE₂) and tumor necrosis factor-α (TNF-α) levels by 55.6% and 58.4%, respectively, compared with the carrageenan control group. Furthermore, the SLN-based gel demonstrated markedly higher bioadhesion (+81%) and a two-fold increase in permeation flux compared with the pure drug gel.Overall, the optimized ketoprofen SLN gel achieved enhanced bioadhesion, skin permeation, and anti-inflammatory efficacy, confirming the potential of lipid nanoparticle-based systems for topical NSAID delivery. This strategy provides a rational, statistically optimized platform for improving localized therapy while minimizing systemic adverse effects.

PMID:42133922 | DOI:10.1080/10837450.2026.2673037

J Med Internet Res. 2026 May 14;28:e84844. doi: 10.2196/84844.

ABSTRACT

BACKGROUND: Machine learning (ML) and deep learning (DL) show promise for fall risk prediction, but prior reviews focused mainly on real-time fall detection, in-hospital falls, or conventional statistical models. The performance of ML-DL-based models for predicting future falls in community-dwelling older adults remains unclear.

OBJECTIVE: This study aimed to review ML-DL studies for predicting future falls among community-dwelling older adults and meta-analyze discrimination where feasible.

METHODS: Six databases were searched from inception to September 23, 2024, with updates on August 31, 2025, and February 28, 2026. We included longitudinal studies developing or validating ML-DL models to predict future falls in community-dwelling adults aged ≥60 years and excluded real-time detection, simulated or no fall, and inpatient studies. Risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Areas under the curve (AUCs) were meta-analyzed using Hartung-Knapp-Sidik-Jonkman random-effects models with 95% CIs. Heterogeneity, 95% prediction intervals (PIs), sensitivity analyses, and subgroup analyses were conducted.

RESULTS: After screening 10,253 records, 28 (0.3%) studies were included; 18 (64.3%) focused on general older adults. Prediction horizons ranged from 3 months to 7 years, and fall incidence ranged from 1.6% to 46.6%. Twenty-three (82.1%) studies applied ML, and 5 (17.9%) studies used DL. Input modalities included text (n=18, 64.3%), sensor (n=5, 17.9%), image (n=1, 3.6%), and multimodal data (n=4, 14.3%). Common predictors included age, sex, fall history, depression, and basic daily activities. Only one model underwent external validation. Calibration reporting was sparse. All models were rated at high risk of bias. Ten models were meta-analyzed, yielding a pooled AUC of 0.79 (95% CI 0.69-0.87) with extreme heterogeneity (τ2=0.64; τ=0.80; I2=99.8%; Q=4128.99). The confidence-distribution bootstrap PI was 0.20 to 0.99, indicating substantial uncertainty in expected performance across new populations. Subgroup analyses indicated moderation by sample size and population type, with higher discrimination in specific populations than in general samples; however, the specific population subgroup included only 2 studies. Although all participants were community dwelling, some cohorts were recruited through clinically enriched pathways rather than general community sampling.

CONCLUSIONS: ML-DL models show potential for identifying community-dwelling older adults at elevated future fall risk; however, wide PIs, limited external validation, and high risk of bias suggest real-world performance may be optimistic. The pooled AUC should be interpreted as a summary of reported discrimination under study-specific conditions, predominantly from internally validated, high-risk-of-bias models, rather than as a robust estimate of transportable real-world performance. This review extends prior reviews by focusing on community-dwelling settings and by integrating PROBAST, Hartung-Knapp-Sidik-Jonkman meta-analysis, PIs, and modality-specific synthesis to evaluate both discrimination and uncertainty. Findings support the use of ML-DL models for proactive fall prevention while emphasizing the need for validation and context-specific implementation.

PMID:42133917 | DOI:10.2196/84844

Neurology. 2026 Jun 9;106(11):e214908. doi: 10.1212/WNL.0000000000214908. Epub 2026 May 14.

ABSTRACT

OBJECTIVES: The HERMES-24 score recently demonstrated high accuracy for outcome prediction after large vessel occlusion (LVO) treatment in late time window patients from randomized clinical trials. In this study, we externally validate the score in a real-world patient cohort.

METHODS: Data from German Stroke Registry patients with LVO treated with endovascular therapy beyond 6 hours from symptom onset or last seen well were used. We performed a complete case analysis, excluding functionally dependent patients (premorbid modified Rankin Scale [mRS] >2/>3 for prediction of mRS ≤2/≤3, respectively). We assessed the HERMES-24 score for 90-day mRS prediction using bootstrap resampling and the c-statistic.

RESULTS: The analyzed cohort comprised 2,117 patients (mean age 74 ± 13.3 years; 55.4% female; median admission NIH Stroke Scale (NIHSS) 14 (Q1-Q3: 9-18)). The HERMES-24 score achieved an area under the curve (AUC) of 0.876 (95% CI 0.859-0.889) for mRS ≤2 and 0.856 (95% CI 0.837-0.875) for mRS ≤3. Subgroup analysis for mRS ≤2 prediction showed lower performance in patients with NIHSS <18 (AUC 0.850, 95% CI 0.832-0.870).

DISCUSSION: In our real-world cohort of late time window patients with LVO, the HERMES-24 score showed good discriminative performance, supporting its cautious clinical applicability, considering its lower performance than in trial populations, especially in patients with lower baseline NIHSS scores.

PMID:42133912 | DOI:10.1212/WNL.0000000000214908

J Med Internet Res. 2026 May 14;28:e78321. doi: 10.2196/78321.

ABSTRACT

BACKGROUND: Previous research has demonstrated that the use of continuous glucose monitoring (CGM) can improve glycemic control in people with type 2 diabetes when used regularly alongside a digital diabetes self-management education and support (DSMES) program. However, to date, there is limited evidence showing the benefits of a digitally delivered DSMES program combined with real-time CGM for adults with type 2 diabetes.

OBJECTIVE: The objective of this study is to evaluate the impact of a DSMES program coupled with CGM on hemoglobin A1c (HbA1c) and CGM-derived glycemic measures compared to usual care for adults with type 2 diabetes over 6 months.

METHODS: Participants with type 2 diabetes and HbA1c of 8% or higher (64 mmol/mol) who were not using mealtime bolus insulin (aged 26-83 y; mean HbA1c 9.6%, SD 1.4% [mean 81.2 mmol/mol, SD 15.8 mmol/mol]) were randomly assigned to a digital DSMES+CGM integrated solution (n=51) or usual care (n=49) for 6 months. The primary outcome was HbA1c. The secondary outcomes were CGM-derived glycemic measures, including glucose management indicator, percent time in range 70 to 180 mg/dL, percent time above range (>180 mg/dL), percent time below range (<70 mg/dL), and mean glucose. Linear mixed effects models were used for intention-to-treat analyses.

RESULTS: HbA1c was lower among the intervention group versus the usual care group at 3 months (difference=-0.7%, 95% CI -1.4% to -0.1% or difference=-8.1 mmol/mol, 95% CI -15.5 to -0.7 mmol/mol; P=.03) and at 6 months (difference=-0.6%, 95% CI -1.4% to 0.2% or difference=-6.9 mmol/mol, 95% CI -15.7 to 1.9 mmol/mol; P=.12) but only reached statistical significance at 3 months. CGM-derived glycemic measures, including glucose management indicator (difference=-0.9%, 95% CI -1.7% to -0.1%; P=.03), time in range (difference=14.6%, 95% CI 1.0% to 28.2%; P=.04), time above range (difference=-14.9%, 95% CI -29.0% to -0.9%; P=.04), and mean glucose (difference=-36.4 mg/dL, 95% CI -70.0 to -2.9 mg/dL; P=.03), also significantly improved for the intervention group versus the usual care group at 6 months.

CONCLUSIONS: The combination of digital DSMES+CGM is effective for supporting adults with type 2 diabetes in managing their condition and has the potential to reduce the risk of long-term health complications.

PMID:42133904 | DOI:10.2196/78321