Tag: nevin manimala

JMIR Mhealth Uhealth. 2025 Oct 1;13:e68464. doi: 10.2196/68464.

ABSTRACT

BACKGROUND: Management of noncommunicable diseases (NCDs) is an increasing challenge for health care systems. Although remote patient monitoring presents a promising solution by utilizing technology to monitor patients outside clinical settings, there is a lack of knowledge about the effect on resource utilization.

OBJECTIVE: This systematic review aimed to review the effects of remote patient monitoring on health care resource utilization by patients with NCDs.

METHODS: Eligible randomized controlled trials (RCTs) involved digital transmission of health data from patients to health care personnel. Outcomes included hospitalizations, length of stay, outpatient visits, and emergency visits. A systematic literature search was performed in Medline, Embase, and Cochrane Central Register of Controlled Trials in June 2024. Titles, abstracts, and full texts were screened individually by 2 authors. Risk of bias was assessed, and data were extracted, analyzed, and pooled in meta-analysis when possible. Confidence in the estimates was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

RESULTS: We included 40 RCTs published between 2017 and 2024. The largest group of NCDs was cardiovascular disease (16 studies). Remote patient monitoring may slightly decrease the proportion of hospitalizations compared with usual care (risk ratio [RR] 0.86, 95% CI 0.77 to 0.95; low certainty). Compared with usual care, remote patient monitoring had fewer or an equal number of hospitalizations (mean difference -0.13, 95% CI -0.29 to 0.03; low certainty). Hospital length of stay may be slightly reduced with remote patient monitoring compared with usual care (mean difference -0.84, 95% CI -1.61 to -0.06 days; low certainty). The proportion of outpatient visits showed probably little to no difference between remote patient monitoring and usual care (RR 0.94, 95% CI 0.87 to 1.02; moderate certainty). Compared with usual care, remote patient monitoring had slightly more outpatient visits, but the CI was wide (mean difference 0.41, 95% CI -0.22 to 1.03; low certainty). The results indicate a small or no difference between remote patient monitoring and usual care regarding proportion of emergency visits (RR 0.91, 95% CI 0.79 to 1.05; low certainty). We are uncertain whether remote patient monitoring increases or decreases the number of emergency visits, as the evidence was of very low certainty.

CONCLUSIONS: This systematic review showed that remote patient monitoring possibly led to lower proportions of patients being hospitalized, fewer hospitalizations, and shorter hospital length of stay compared with usual care. Patients undergoing remote monitoring had possibly more outpatient visits compared with usual care. The proportions of patients with outpatient visits or emergency visits were probably similar. Finally, we had very low certainty in the number of emergency visits. The results should be considered with caution as the certainty of evidence was moderate to very low. We did not find results regarding institutional stay.

PMID:41032865 | DOI:10.2196/68464

Medwave. 2025 Oct 1;25(9):e3106. doi: 10.5867/medwave.2025.09.3106.

ABSTRACT

INTRODUCTION: Surgical waiting lists for conditions not covered by the Explicit Health Guarantees represent unmet needs and structural gaps within the Chilean public health system. The field of orthopedics and traumatology accounts for a high volume of pending procedures, with total knee arthroplasty being the most frequently delayed. The coexistence of deferrable pathologies not formally recorded, combined with the low efficiency in the use of operating rooms, aggravates this problem. This study aims to characterize the surgical waiting list for conditions not covered by the Explicit Health Guarantees in Chile between 2022 and 2024, with a focus on orthopedics and traumatology. Additionally, we identify the most delayed procedures, the most affected health services, and the current capacity for resolution.

METHODS: A descriptive observational study based on official data requested from the Ministry of Health through transparency and public records, including the Department of Health Statistics and Information and the National Health Fund. Surgical procedures awaiting treatment were analyzed by specialty, region, establishment, sex, and age for the period from 2022 to 2024.

RESULTS: Orthopedics and traumatology were the specialties with the highest number of pending procedures (22 to 24% of the total). Knee arthroplasty consistently ranked first, with over 20 000 cases annually. The O’Higgins Health Service had the highest burden. In 2022, the rate of arthroplasties performed on patients covered by the National Health Fund was four times lower than on patients covered by Social Security Health Institutions. No region achieved a surgical volume sufficient to reduce the waiting list significantly.

CONCLUSIONS: The problem of waiting lists in orthopedics is mainly due to organizational shortcomings. Creating the role of trauma emergency ward, optimizing the use of wards, and creating outpatient surgical units are short- and medium-term measures to reverse this trend.

PMID:41032845 | DOI:10.5867/medwave.2025.09.3106

Opt Lett. 2025 Oct 1;50(19):6145-6148. doi: 10.1364/OL.571324.

ABSTRACT

Harmonically mode-locked soliton fiber laser can host an ensemble of identical solitons in parallel, providing a unique many-body system for exploring the intrinsic stochasticity of soliton dynamics in nonlinear optical systems. We report in this work the experimental observation of parallel soliton dynamics under homogeneous perturbation in a harmonically mode-locked fiber laser. Given an abrupt and transient decrease in the pump power, the parallel solitons exhibit evolution trajectories of probabilistic nature, featuring prominent re-distribution of soliton energies followed by random collapse and recovery after the perturbation. We investigate statistical dependences of the soliton collapse upon the perturbation parameters, while revealing threshold behaviors of the recovery dynamics. This work provides unique insight into the stochasticity of the nonlinear soliton evolution in mode-locked fiber lasers and may help to improve laser stability.

PMID:41032814 | DOI:10.1364/OL.571324

Opt Lett. 2025 Oct 1;50(19):6133-6136. doi: 10.1364/OL.574551.

ABSTRACT

The progress of AlGaN-based deep ultraviolet light-emitting diodes is significantly limited by their unideal light extraction efficiency. In this work, a cost-efficient nanosphere lithography technique is utilized to fabricate wafer-scale SiO₂-based patterned dielectric nanostructures on the backside of sapphire substrates. Mapping results and statistical analyses demonstrate a uniform optical power enhancement across the entire chip, and the average power can be increased by 16.7% with almost identical peak wavelength and slightly enhanced operating voltage. The light output power of the LEDs with the patterned film exhibits a substantial enhancement of 34.0% compared to conventional LEDs at an injected current of 330 mA, accompanied by a 1.34-fold increase in light extraction efficiency. Finite-difference time-domain simulations indicate that the nanostructures on the patterned film effectively weakened total internal reflection at the sapphire/air interface. The above results validate the scalability of this method for industrial mass production of high-power DUV LEDs.

PMID:41032811 | DOI:10.1364/OL.574551

Opt Lett. 2025 Oct 1;50(19):6117-6120. doi: 10.1364/OL.570619.

ABSTRACT

Polarization optical fiber sensors are based on modifications of fiber birefringence by an external measurand (e.g., strain, pressure, acoustic waves). Yet, this means that different input states of polarization will result in very distinct behaviors, which may or may not be optimal in terms of sensitivity and signal-to-noise ratio. To tackle this challenge, this manuscript presents an optimization technique for the input polarization state using the Fisher information formalism, which allows for achieving maximal precision for a statistically unbiased metric. By first measuring the variation of the Mueller matrix of the optical fiber in response to controlled acoustic perturbations induced by piezo speakers, we compute the corresponding Fisher information operator. Using maximal information states of the Fisher information, it was possible to observe a significant improvement in the performance of the sensor, increasing the signal-to-noise ratio from 4.3 to 37.6 dB, attaining an almost flat response from 1.5 kHz up to 15 kHz. As a proof-of-concept for dynamic audio signal detection, a broadband acoustic signal was also reconstructed with significant gain, demonstrating the usefulness of the introduced formalism for high-precision sensing with polarimetric fiber sensors.

PMID:41032807 | DOI:10.1364/OL.570619

Int Braz J Urol. 2026 Jan-Feb;52(1):e20250453. doi: 10.1590/S1677-5538.IBJU.2025.0453.

ABSTRACT

PURPOSE: To evaluate the prevalence, predictors, and progression of acute kidney injury (AKI) in patients undergoing mPCNL for nephrolithiasis.

MATERIALS AND METHODS: We retrospectively analyzed data from 569 patients who underwent mPCNL at a single tertiary academic center (01/2016-10/2024). AKI was defined per KDIGO criteria as sCr increase >0.3 mg/dL or ≥1.5× baseline. Stone-free status was no residual stones on CT at 3-month follow-up. Complications were classified using the modified Clavien system. Kidney function was reassessed 30-90 days post-op. Descriptive statistics, logistic regression, and Cox regression were applied.

RESULTS: Median (IQR) age and stone volume were 57 (48-66) years and 2.1 (0.9-4.2) cm³. Median preoperative sCr and operative time were 0.9 (0.7-1.1) mg/dL and 90 (73-120) minutes. Post-mPCNL, 40 patients (7.0%) developed AKI. Complications occurred in 138 (24.2%) patients; 449 (78.9%) were stone-free. AKI patients had higher CCI (1.3 vs. 0.5, p=0.04), pre-op sCr (1.1 vs. 0.8 mg/dL, p<0.01), stone volume (5.7 vs. 2 cm³, p=0.02), and longer operative time (130 vs. 90 min, p=0.01). Complications were more frequent in AKI patients (42.5% vs. 22.8%, p=0.01). At multivariate analysis, operative time (OR 1.1, p=0.03), pre-op sCr (OR 3.8, p=0.001), and early complications (OR 2.5, p=0.02) were independently associated with AKI. AKI persisted in 9 (22.5%) patients, mainly those with complications (88.9% vs. 38.7%, p=0.01). On Cox analysis, lower BMI (HR 0.8, p=0.02) and absence of complications (HR 0.3, p=0.01) predicted faster AKI recovery.

CONCLUSION: Acute kidney injury remains a clinically significant complication following mPCNL.

PMID:41032756 | DOI:10.1590/S1677-5538.IBJU.2025.0453

JCO Clin Cancer Inform. 2025 Oct;9:e2500102. doi: 10.1200/CCI-25-00102. Epub 2025 Oct 1.

ABSTRACT

PURPOSE: The increasing use of patient portal messages has enhanced patient-provider communication. However, the high volume of these messages has also contributed to physician burnout.

METHODS: Patient-generated portal messages sent to a single cancer center from 2011 to 2023 were extracted. BERTopic, a natural language processing topic modeling technique based on large language models, was optimized. For further categorization, the topic words were labeled using GPT-4, followed by review by two oncologists. Uniform Manifold Approximation and Projection was used for dimensionality reduction and visualizing topics. Message volume changes over time were assessed using a Student’s t test.

RESULTS: A total of 2,280,851 messages were analyzed. The monthly average number of messages increased from 2,071 in 2012 to 43,430 in 2022 (P < .001). There was a significant rise in message volume after the COVID-19 pandemic, with a posterior probability of a causal effect of 96.4% (P = .04). Scheduling-related messages were the most frequent across departments, whereas symptoms and health concerns were second or third most common topics. In medical oncology and surgical oncology, topics on prescriptions and medications were more common compared with radiation oncology and gynecologic oncology. Despite concurrent institutional changes in self-scheduling systems, scheduling-related messages did not decrease over time.

CONCLUSION: The substantial increase in patient portal messages, particularly scheduling-related inquiries, underscores the need for streamlined communication to reduce the burden on health care providers. These findings highlight the need for strategies to manage message volume and mitigate physician burnout, laying groundwork for artificial intelligence-driven future triage systems to improve message management and patient care.

PMID:41032743 | DOI:10.1200/CCI-25-00102

JMIR Form Res. 2025 Oct 1;9:e70158. doi: 10.2196/70158.

ABSTRACT

BACKGROUND: The dose of mobile health (mHealth) interventions can influence participant engagement, acceptability, and overall impact. However, few mHealth interventions have explored this dose-response relationship.

OBJECTIVE: This study aims to explore how dose influences the acceptability, engagement, cost, and impact on infant feeding status of a parent-targeted mHealth text messaging program which aims to enhance child health, including breastfeeding exclusivity and duration.

METHODS: This pragmatic randomized controlled trial was conducted from October 2021 to May 2024. The Healthy Beginnings for Hunter New England Kids (HB4HNEKids) program provides- text messages aimed to support parents and carers and their children by providing evidence-based preventive health information across the first 2000 days. Participants were enrolled in HB4HNEKids from 5 Child and Family Health Services in the Hunter New England region of New South Wales, Australia, and randomized into either a high-dose or low-dose text message group for the first 2 years of the pilot program. Dose refers to the quantity and frequency of text messages sent to participants. Participants in the high-dose text message group received an average of 111-121 text messages, and the low-dose text message group received 80-82 text messages across the 2 years. Outcomes of interest included acceptability, engagement, cost, and infant feeding status in relation to dose. Engagement with the messages was determined using click rates and program opt-out rates. Participant acceptability was assessed via a brief survey. Impact on infant feeding status (ie, breastfeeding, formula feeding, or mixed feeding) was determined by participants reporting their feeding status at several time points across the program. Cost was determined by assessing the per participant and total cost of sending text messages for each dose group across the 2-year period.

RESULTS: There were no statistically significant differences in click rates between high or low-dose text message groups. In the first 6 months, significantly more participants opted out of the high-dose text message group (191/2724; 7%) compared to the low-dose (108/2812; 3.8%; P<.001). In terms of program acceptability, 183 out of 214 (85.5%) participants of the high-dose and 228 out of 252 (90.5%) participants of the low-dose text message group were satisfied with the frequency of text messages. In addition, 188 out of 215 (87%) participants of high-dose and 220 out of 255 (86%) participants of low-dose text message group indicated they would recommend the program to other caregivers. The average per participant and total cost to the health service for sending messages was lower in the low-dose group (A$9.32 per participant and A$15,271.48 total; A$1 is approximately equal to US $0.68) compared to the high-dose text message group (A$12.96 per participant and A$21,241.44 total).

CONCLUSIONS: The HB4HNEKids program demonstrated positive outcomes including high acceptability across both groups and no impact on infant feeding status, irrespective of dose. Given the higher opt-out rates and message costs in the high-dose text message group, a lower dose is likely more scalable for future use.

PMID:41032735 | DOI:10.2196/70158

J Med Internet Res. 2025 Oct 1;27:e71297. doi: 10.2196/71297.

ABSTRACT

BACKGROUND: Sharing information derived from individual patient data is restricted by regulatory frameworks due to privacy concerns. Generative artificial intelligence can generate shareable virtual patient populations as proxies for sensitive reference datasets. Explicit demonstration of privacy is demanded.

OBJECTIVE: This study evaluated whether a privacy-by-design technique called “avatars” can generate synthetic datasets replicating all reported information from randomized clinical trials (RCTs).

METHODS: We generated 2160 synthetic datasets from two phase 3 RCTs for patients with multiple sclerosis (NCT00213135 and NCT00906399; n=865 and 1516 patients) with different configurations to select one synthetic dataset with optimal privacy and utility for each. Several privacy metrics were computed, including protection against distance-based membership inference attacks. We assessed fidelity by comparing variable distributions and assessed utility by checking that all end points reported in the publications had the same effect directions, were within the reported 95% CIs, and had the same statistical significance.

RESULTS: Protection against membership inference attacks was the hardest privacy metric to optimize, but the technique yielded robust privacy and replication of the primary end points (in 72.5% and 80.8% of the 1080 generated datasets). Utility was uneven across the variables and end points, such that information about some end points could not be captured. With optimized generation configurations, we selected one dataset from each RCT replicating all efficacy end points of the placebo and approved treatment arms while maintaining satisfactory privacy (hidden rate: 85.0% and 93.2%).

CONCLUSIONS: Generating synthetic RCT datasets replicating primary and secondary efficacy end points is possible while achieving a satisfactory and explicit level of privacy. To show the potential of this method to unlock health data sharing, we released both placebo arms as open datasets.

PMID:41032725 | DOI:10.2196/71297

JMIR Med Educ. 2025 Oct 1;11:e78320. doi: 10.2196/78320.

ABSTRACT

BACKGROUND: Large language models such as ChatGPT (OpenAI) have shown promise in medical education assessments, but the comparative effects of prompt engineering across optimized variants and relative performance against medical students remain unclear.

OBJECTIVE: This study aims to systematically evaluate the impact of prompt engineering on five ChatGPT variants (GPT-3.5, GPT-4.0, GPT-4o, GPT-4o1-mini, and GPT-4o1) and benchmark their performance against fourth-year medical students in midterm and final examinations.

METHODS: A 100-item examination dataset covering multiple choice questions, short answer questions, clinical case analysis, and image-based questions was administered to each model under no-prompt and prompt-engineering conditions over 5 independent runs. Student cohort scores (N=143) were collected for comparison. Responses were scored using standardized rubrics, converted to percentages, and analyzed in SPSS Statistics (v29.0) with paired t tests and Cohen d (P<.05).

RESULTS: Baseline midterm scores ranged from 59.2% (GPT-3.5) to 94.1% (GPT-4o1), and final scores ranged from 55% to 92.4%. Fourth-year students averaged 89.4% (midterm) and 80.2% (final). Prompt engineering significantly improved GPT-3.5 (10.6%, P<.001) and GPT-4.0 (3.2%, P=.002) but yielded negligible gains for optimized variants (P=.07-.94). Optimized models matched or exceeded student performance on both exams.

CONCLUSIONS: Prompt engineering enhances early-generation model performance, whereas advanced variants inherently achieve near-ceiling accuracy, surpassing medical students. As large language models mature, emphasis should shift from prompt design to model selection, multimodal integration, and critical use of artificial intelligence as a learning companion.

PMID:41032724 | DOI:10.2196/78320