Nevin Manimala

Biomedica. 2026 Mar 2;46(1):71-82. doi: 10.7705/biomedica.7702.

ABSTRACT

INTRODUCTION: Antibiotic consumption and resistance have increased worldwide. Antibiotic resistance results in longer hospital stays and higher healthcare costs.

OBJECTIVE: To describe the consumption of antibiotics and associated expenses in Colombia.

MATERIALS AND METHODS: A meticulous descriptive cross-sectional study of antibiotic consumption and expenditure in Colombia from 2020 to 2023 was conducted. Between 2020 and 2023, a description of the consumption and expenditure of antibiotics in Colombia was made. Data were obtained from IQVIA™ (IMS Health and Quintiles). The prominent families of antimicrobials used in Colombia were selected. Twelve pharmacological families were classified, including 27 antimicrobials and three β-lactamase inhibitors. The defined daily dose was used to measure antibiotic consumption, identify variations, and evaluate medical prescription practices. The defined daily dose per 1,000 inhabitants per day was estimated to obtain information from the population receiving daily antibiotic treatment. The amount of antibiotics used was estimated in grams and tons per year.

RESULTS: The top 10 most consumed antimicrobials by defined daily dose per 1,000 inhabitants per day in Colombia were amoxicillin, azithromycin, metronidazole, cephalexin, ciprofloxacin, trimethoprim-sulfamethoxazole, ampicillin, sulbactam, clarithromycin, cefazolin, and dicloxacillin. The total consumption of antibiotics was 2,139 tons, which represented an expense of USD$ 708,112,587, for an increase of 17 and 8%, respectively, during the period.

CONCLUSIONS: The progressive increase in consumption and spending on antimicrobials in Colombia requires a set of interventions that include promoting changes in medical prescribing behaviour and a public education campaign that leads to the adoption of a sustainable public health policy.

PMID:41875456 | DOI:10.7705/biomedica.7702

Diving Hyperb Med. 2026 Mar 31;56(1):83-87. doi: 10.28920/dhm56.1.83-87.

ABSTRACT

Closed circuit rebreather (CCR) diving sets use soda lime, a sodium hydroxide-based ‘scrubber’ substance to remove CO₂ from exhaled breathing gas thus prolonging dive time and efficiency. Inadvertent water ingress into the set may result in reaction with the scrubber and a highly alkaline solution known as a ‘caustic cocktail’ may be formed. Ingestion or aspiration of this solution can cause severe chemical burns. Irrigation with freshwater is the mainstay of initial treatment of ‘caustic cocktail’ injuries in CCR divers. Published advice advises divers never to use acidic diluents to irrigate and neutralise a caustic cocktail solution due to concerns over the potentially exothermic nature of the neutralisation reaction. However, there is limited available evidence to support this advice, and it was felt that further research into the best treatment options available for caustic cocktails is required. This study used an in vitro model of an ingested caustic cocktail to investigate pH and temperature changes after adding different diluents (including acidic diluents orange juice or coca cola) to a solution of sodium hydroxide. Acidic diluents reduce pH significantly more than neutral diluents with a respective mean drop in pH of 5.99 compared to 0.78 (P = 0.015). There is no statistically significant difference in temperature change noted between the two types of diluent (P = 0.32) with no exothermia generated. We propose that orange juice or coca cola are more effective irrigation solutions than fresh or seawater, and that advice to divers who use CCRs could change.

PMID:41875445 | DOI:10.28920/dhm56.1.83-87

Diving Hyperb Med. 2026 Mar 31;56(1):48-51. doi: 10.28920/dhm56.1.48-51.

ABSTRACT

INTRODUCTION: This study’s aim was to determine the number of scuba tank fills done in Victoria, Australia from 1 July 2024 to 30 June 2025 to provide an estimate of the number of scuba dives conducted during that period and, from that, estimates of the fatality and decompression illness rates.

METHODS: Suppliers of compressed gas for scuba diving in Victoria were identified through internet searches, industry liaison and the Australasian Diving Safety Foundation records. Those identified were emailed an invitation to participate in the tank fill survey and provided with dedicated spreadsheets. Email reminders were sent to collect monthly data on air, nitrox and ‘other’ fills. Data were compiled and, at the end of the survey period, non-regular participants were approached to provide actual numbers or estimates of the year’s fills.

RESULTS: Overall, 38/40 (95%) identified current suppliers participated in the survey, with 27 submitting regular monthly data and the remainder providing actual or estimated annual fills. There were 46,720 reported fills, including 39,386 air, 6,758 nitrox, and 576 others, with proportions of 84%, 15% and 1%, respectively. During that period, 11 scuba divers were treated for decompression illness (DCI) (eight of whom had dived locally) and there were two fatalities.

CONCLUSIONS: It is estimated that around 50,000 scuba tank fills were provided, equating to approximately 50,000 dives conducted in Victorian waters during from 1 July 2024 to 30 June 2025. During that period, there were eight open circuit divers who had dived in Victoria treated for DCI and two scuba diving fatalities, yielding estimates of 16 DCI cases and four deaths per 100,000 dives.

PMID:41875441 | DOI:10.28920/dhm56.1.48-51

Diving Hyperb Med. 2026 Mar 31;56(1):13-20. doi: 10.28920/dhm56.1.13-20.

ABSTRACT

INTRODUCTION: Acute respiratory symptoms after diving are common among competitive breath-hold divers. These symptoms, including shortness of breath, cough, haemoptysis, and chest discomfort, are often linked to immersion pulmonary oedema (IPO) or pulmonary barotrauma. This study aimed to evaluate the incidence, clinical presentation, and risk factors of IPO using portable ultrasound devices in a depth competition for breath-hold divers in Taiwan.

METHODS: This observational study was conducted during a competition around Liuqiu Island, Taiwan. Twenty-five breath-hold divers participated. Lung ultrasonography was performed pre- and post-diving, along with measurements of basic vital signs. Symptoms and diving history were recorded. The primary outcome measure was B-line score before and after diving.

RESULTS: Following the dive, 7/25 (28%) of divers reported acute respiratory symptoms, 10/25 (40%) showed ultrasound evidence of increased extravascular lung fluid, and 2/25 (8%) met the clinical criteria for IPO, presenting with both symptoms and hypoxaemia (SpO₂ ≤ 95%) alongside positive B-lines. B-line scores significantly increased from a median of 4 (range 1-4) to 7 (range 3-13) (P = 0.048). Male sex, higher body mass index, and elevated pre-dive systolic blood pressure were significantly associated with positive ultrasound findings. Among all factors, only diving depth remained statistically significant associated with increased post-dive B-line scores (regression coefficient = 0.046) (P = 0.007).

CONCLUSIONS: The incidence of post-dive acute respiratory symptoms was 28%, and 8% of participants exhibited clinical features of IPO. Positive lung ultrasound findings were observed in 40% of divers, mostly asymptomatic. Maximum diving depth was significantly associated with increased post-dive B-line scores.

PMID:41875438 | DOI:10.28920/dhm56.1.13-20

JMIR Form Res. 2026 Mar 24;10:e88445. doi: 10.2196/88445.

ABSTRACT

BACKGROUND: There is a growing interest in developing novel psychological interventions for eating disorders, with an emphasis on targeting maintaining factors. One hypothesized mechanism underlying illness maintenance is the experience of an “inner eating disorder voice,” which reinforces maladaptive thoughts, emotions, and behaviors. Preliminary studies suggest that the eating disorder voice is common among patients and is linked to greater illness severity.

OBJECTIVE: This single-arm, mixed methods pilot feasibility study aimed to evaluate a novel virtual reality (VR)-based therapy targeting the eating disorder voice. The intervention was adapted from AVATAR therapy for psychosis and was examined as an adjunct to treatment as usual in individuals with eating disorders. In this adaptation, participants engaged with a therapist-controlled avatar representing their inner eating disorder voice in VR. The primary objectives were to assess the feasibility, acceptability, and safety of the intervention and to provide preliminary estimates of its clinical efficacy.

METHODS: Adults with anorexia nervosa (9/10, 90%) or bulimia nervosa (1/10, 10%) took part in a 7-session VR-based therapy course at the Mental Health Centre Copenhagen, Copenhagen University Hospital, Denmark, alongside their treatment as usual. Quantitative measures of feasibility (recruitment, retention rates, and satisfaction scores), safety, and eating disorder-related outcomes were collected at baseline and after treatment between June 2023 and January 2024. Qualitative interviews conducted after the intervention (October 2023 to November 2023) explored participants’ experiences. Descriptive statistics, paired t tests, and thematic analysis were conducted, and the analyses were finalized in October 2025.

RESULTS: Recruitment targets were met: 14 individuals were referred, and 11 provided consent well within the prespecified time frame. Treatment completion rate was 80% (8/10; 95% CI 44%-97%), and no serious adverse events occurred. Participants reported high satisfaction (7/10, 70%; mean 9, SD 1.15 on a 10-point Likert scale; median 9, IQR 8.5-10.0; range 7-10), and qualitative data (8/10, 80%) suggested that they valued the immersive virtual representation of their eating disorder voice. Exploratory analyses indicated improvements in eating disorder symptoms (Hedges g=-0.99, 95% CI -1.74 to -0.24; P=.01), power dynamics associated with the eating disorder voice (Hedges g=-1.63, 95% CI -2.59 to -0.67; P=.002), and emotion regulation via cognitive reappraisal (Hedges g=0.87, 95% CI 0.08-1.66; P=.04).

CONCLUSIONS: The VR-based avatar intervention for eating disorders was feasible, acceptable, and safe, with preliminary signals of clinical improvement. These findings support further development and evaluation of the intervention in a randomized clinical trial.

PMID:41875424 | DOI:10.2196/88445

JMIR AI. 2026 Mar 24;5:e80549. doi: 10.2196/80549.

ABSTRACT

BACKGROUND: The workload that stems from writing clinical histories is one of the main sources of stress and overload for primary care professionals, accounting for up to 43% of the working day. The introduction of technology, specifically artificial intelligence (AI), in the field of health could significantly reduce the time spent writing clinical reports without compromising the quality of care.

OBJECTIVE: The objective of this study is to evaluate the impact of implementing an AI solution for the automatic transcription of consultations in several primary care centers in Catalonia.

METHODS: A proof of concept of a multicenter study was carried out with alternating assignment of consultations to the intervention group (use of an AI assistant that automatically generates consultation notes) or control group (usual clinical practice). The impact was evaluated through the recorded documentation time and the initial quality of the transcription measured with the Levenshtein distance expressed as corrected words per minute, complemented by a qualitative categorization of clinician-reported errors and the perceived satisfaction of patients and professionals through questionnaires evaluated through a Likert scale.

RESULTS: For the intervention group, the average processing time was 6.63%, while the review time by the professional amounted to 15.2%. Because documentation-time data were not available for the control group, no direct between-group comparison of time savings was possible; time-related findings are therefore exploratory and limited to intervention-group process and review metrics. Levenshtein-based estimates showed that in most cases, the review was <24 words per minute and 26% of drafts required no edits, indicating a high-quality initial transcription. A qualitative analysis of clinician feedback showed that context or meaning errors were the most frequent, while unsupported additions or hallucinations were uncommon. The satisfaction surveys were answered by 289 patients and 213 professionals. Patient satisfaction was high (≥4/5), with no statistically significant differences between the control and intervention groups. The professionals rated the audio quality at 9.06 out of 10 (SD 1.18; medicine) and 7.62 out of 10 (SD 1.58; nursing) and the transcription at 8.14 out of 10 (SD 1.74) and 6.93 out of 10 (SD 1.52), respectively.

CONCLUSIONS: The implementation of an AI tool was feasible in routine primary care, was well accepted by clinicians, and did not negatively affect patient satisfaction, with a generally low transcription review burden. However, this proof-of-concept study does not allow conclusions about comparative time savings, and adequately powered randomized studies are needed to confirm benefits for care quality and efficiency.

PMID:41875421 | DOI:10.2196/80549

JMIR Res Protoc. 2026 Mar 24;15:e86515. doi: 10.2196/86515.

ABSTRACT

BACKGROUND: Young adults face rising wellness challenges, including prediabetes risk, requiring sustained engagement with preventive health interventions. Digital wellness applications offer promise for promoting healthy lifestyle behaviors, yet high dropout rates and inadequate personalization limit their effectiveness. This paper outlines the technical implementation and formative usability evaluation of MiCARE, a theory-driven progressive web application (PWA) designed to support sustained wellness engagement among young adults through user-centered design.

OBJECTIVE: This study aims to systematically implement theory-driven design specifications into a functional web application, the MiCARE platform, and to conduct a formative usability evaluation with a convenience sample of 20 university-affiliated young adults aged 18 to 34 years in Victoria, Australia, in both rural and urban areas using the task-technology fit and unified theory of acceptance and use of technology frameworks as organizing lenses to assess usability, usefulness, and satisfaction.

METHODS: This is an embedded mixed methods study conducted across 2 phases: phase 3 and phase 4. Phase 3 involves the technical implementation of 6 theory-driven features (ie, empathetic chatbot, learning hub, dynamic goal setting, gamification, personalized reminders, and progress dashboard) using HTML5, CSS3, JavaScript, Google Dialogflow ES, and Firebase services, following the Agile methodology over 6 months with biweekly self-managed sprints and clinical verification. Phase 4 is a 3-month formative usability feasibility evaluation with 20 young adults recruited from La Trobe University (Bundoora and Bendigo campuses). Participants will complete screening and initial, midpoint, and final surveys assessing usability, usefulness, and satisfaction, while real-time use analytics captures engagement patterns. Data analysis will use the task-technology fit and unified theory of acceptance and use of technology frameworks as interpretive guides, with quantitative data analyzed using descriptive statistics (R Studio) and qualitative feedback analyzed through thematic analysis (NVivo). Use analytics will provide descriptive contextual information only. The study has received ethics approval from the La Trobe University Human Research Ethics Committee (HEC24507).

RESULTS: The study will take place between 2025 and 2026. Phase 3 (technical implementation) commenced in October 2025 and is currently ongoing, with core features under active development and verification. Phase 4 (formative usability and feasibility evaluation) is scheduled to commence following completion of phase 3. Evaluation results will be disseminated in academic forums and peer-reviewed publications in early 2027. The findings will enable us to evaluate the feasibility, acceptability, and usability of a theory-driven PWA in this university-affiliated sample, informing refinements and future larger-scale studies.

CONCLUSIONS: This study will contribute to the technical implementation and formative usability evaluation of a multitheoretical, user-centered PWA for wellness engagement in preventive health, bridging the gap between conceptual frameworks and deployed interventions.

PMID:41875407 | DOI:10.2196/86515

PLoS Genet. 2026 Mar 24;22(3):e1012067. doi: 10.1371/journal.pgen.1012067. eCollection 2026 Mar.

ABSTRACT

Interbreeding between anatomically modern humans and archaic hominins has contributed to the genomes of present-day human populations. However, our understanding of the specific gene regulatory consequences of Neanderthal, and particularly, Denisovan introgression is limited. Here, we used a massively parallel reporter assay to investigate the regulatory effects of 25,869 high-confidence introgressed SNPs segregating in present-day individuals of Papuan genetic ancestry in immune cell types. Overall, 8.22% of Denisovan and 8.58% of Neanderthal sequences showed active regulatory activity, and 9.22% of these displayed differential activity between archaic and modern alleles. We found no association between introgressed allele frequency on activity regardless of introgression source, but introgressed Denisovan alleles at higher frequencies were less likely to be differentially active than expected, suggesting introgression is under some degree of selective constraint. Both activity and differentially activity were associated with distance to the nearest transcription start site, while differential activity was additionally associated with differential transcription factor binding. Genes predicted to be regulated by differentially active sequences included IFIH1 and TNFAIP3, key immune genes and known examples of archaic introgression. Overall, this work provides experimental validation of regulatory activity for thousands of archaic variants in populations with the highest levels of Denisovan ancestry worldwide, revealing how human evolutionary history actively shapes present-day genetic diversity and immune function.

PMID:41875405 | DOI:10.1371/journal.pgen.1012067

JMIR AI. 2026 Mar 24;5:e70017. doi: 10.2196/70017.

ABSTRACT

BACKGROUND: Despite the growing potential of large language models (LLMs) in mental health services, evidence on its capabilities in diagnostic processes remains limited.

OBJECTIVE: This study described the development and evaluation of CapyEngine, an LLM-powered diagnostic tool designed to assist in the diagnosis of mental disorders.

METHODS: We developed and evaluated CapyEngine through 3 phases. In phase 1, we created a disorder and symptom database using Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR). We then designed and developed CapyEngine’s architecture using LLMs, embedding models, and vector searches. In phase 2, we conducted usability testing with mental health professionals (n=7). In phase 3, we compared CapyEngine’s diagnostic accuracy against ChatGPT-4o and clinicians using 35 standardized case scenario exam questions from psychiatry and clinical psychology board exams. Questions were input into CapyEngine, and the top 10 recommended diagnoses were obtained. ChatGPT-4o was prompted to provide the top 10 potential diagnoses for each question. Clinicians (n=3) received similar instructions to generate at least 10 potential diagnoses for each question. Responses were then analyzed to compare diagnostic accuracy of CapyEngine, ChatGPT-4o, and clinicians. Accuracy was measured by the percentage of questions where the correct answer was among the top 10 (least stringent), top 5, or top 1 (most stringent) results of the diagnosis list.

RESULTS: Preliminary user interview reflected high acceptability and feasibility of CapyEngine. Across diagnostic accuracy thresholds, ChatGPT-4o consistently outperformed both CapyEngine and clinicians in broader rankings (top 10 and top 5 benchmarks; all P<.03). Clinicians showed significantly higher accuracy than CapyEngine using the top 5 benchmark (odds ratio 0.26, 95% CI 0.09-0.78; P=.02). For the top 1 benchmark, no significant differences were observed, where clinicians showed a borderline advantage over ChatGPT-4o (odds ratio 0.34, 95% CI 0.13-0.91; P=.05). Regarding the range and slope of diagnostic accuracy decline across benchmarks (least to most stringent), CapyEngine showed the smallest decline (0.14) and flattest slope (-0.07), reflecting more consistent and constrained diagnostic ranking behavior as evaluation thresholds became more stringent. Clinicians exhibited a moderate decline (0.26), whereas ChatGPT-4o demonstrated a sharp decrease (0.69) in accuracy when only the top-ranked diagnosis was considered, consistent with broader diagnostic coverage at less stringent thresholds.

CONCLUSIONS: Overall, ChatGPT-4o achieved the highest accuracy at less stringent benchmarks (top 10 and top 5), while clinician performance did not differ significantly from ChatGPT-4o in identifying the single most likely diagnosis. Although CapyEngine was less accurate overall, it exhibited more consistent and constrained diagnostic ranking across evaluation benchmarks, likely reflecting its DSM-5-TR-based, domain-specific design rather than broader diagnostic coverage. Nonetheless, CapyEngine shows promise as a tool to augment the mental health diagnostic process, and further research is needed to evaluate the risks and benefits of integrating artificial intelligence systems, such as CapyEngine, into clinical workflows.

PMID:41875403 | DOI:10.2196/70017

PLoS One. 2026 Mar 24;21(3):e0344023. doi: 10.1371/journal.pone.0344023. eCollection 2026.

ABSTRACT

Aiming at the TTC (Time to Collision) and derivative indicators’ problems of unclear definition and missed/wrong judgments of traffic conflicts on curved road in the traditional Cartesian coordinate system, a new method that can better identify the conflicts on curved road is proposed. The method first establishes the Frenet coordinate system according to the road centerline (i.e., the reference line), and obtains the vehicle trajectory coordinates in the Frenet coordinate system. The Frenet coordinate system can simplify the calculation difficulty of vehicle trajectory and conflict under the curve road. Then determine the vehicle state in the Frenet coordinate system, and then use TTC to calculate rear-end and lane-change conflicts according to the state of the vehicle (non-lane-change/lane-change). Finally, a total of 4 hours of video data were collected based on the K283 of the lane-switch work zone of the Jiqing Highway. Subsequently, the continuous high-precision conflict data in the region was obtained through the video and conflict identification program, and the traditional method was compared with the new method. The results show that different methods have a significant impact on the identification of the number of serious conflicts. The new method can reduce the missed judgments of serious rear-end conflicts on curved road, especially at the junctions of curved and straight segments (segment 3/4/7/8/9), and can also reduce wrong judgments of serious lane-change conflicts. In addition, among the 125 added serious rear-end conflicts identified by the new method, the maximum deceleration of 10 conflicting vehicles during the conflict exceeds the dangerous state -4/-1.5m/s2, which explain that the new method can help us better identify the risks of curved road. The new method combines the Frenet coordinate system, vehicle state determination and TTC, which can reduce the missed/wrong judgments of conflicts on curved road, and expand the traffic conflict identification from previous straight road to full-line road alignment.

PMID:41875402 | DOI:10.1371/journal.pone.0344023