JMIRx med最新文献

{"title":"Use of a Specialist Telephone Consultation Line for Long COVID in Primary Care in British Columbia: Retrospective Descriptive Quality Improvement Study.","authors":"Saniya Kaushal, Jastinder Bhandal, Peter Birks, Jesse Greiner, Adeera Levin, Michelle Malbeuf, Zachary Schwartz","doi":"10.2196/57021","DOIUrl":"10.2196/57021","url":null,"abstract":"<p><strong>Background: </strong>Long COVID (post-COVID-19 condition) continues to challenge primary care. To support family physicians in British Columbia, the general internal medicine (GIM) COVID-19 Rapid Access to Consultative Expertise (RACE) line was launched in August 2020 to provide real-time specialist advice.</p><p><strong>Objective: </strong>This quality improvement study aimed to evaluate the implementation and utilization of the GIM-COVID-19 Long-Term Sequelae RACE line in British Columbia. Specifically, it sought to characterize the demographics of patients involved in RACE consultations, identify the most common themes and clinical queries presented by primary care providers, and assess how usage patterns evolved over time during the COVID-19 pandemic.</p><p><strong>Methods: </strong>We conducted a retrospective descriptive analysis of 149 RACE line call summaries between August 2020 and June 2021. Six calls were excluded due to insufficient information, such as incomplete documentation or absence of a clear COVID-19-related question. Because the original extraction notes are no longer available, further details about these calls cannot be provided, leaving 143 eligible calls. Data extracted included patient age, sex, geographical location, symptom type, and timing of symptom onset post-COVID-19 infection. Calls were categorized by symptom duration (acute: <2 wk, subacute: 2-12 wk, chronic: >12 wk), thematic content (respiratory, fatigue, neurological, etc), and query type (symptom management, return-to-work, vaccination, etc). Data were coded independently by two reviewers using a standardized spreadsheet and predefined codebook. Discrepancies were resolved through discussion. Descriptive statistics summarized the findings.</p><p><strong>Results: </strong>Many calls involved female patients (91/143, 64%), with the most common age group being 40-49 years (32/113, 28%). Most calls came from Greater Vancouver (35/83, 42%) and the Fraser Valley (29/83, 35%). Subacute symptoms (52/149, 35%) and vaccination-related concerns (29/149, 19%) were the most common inquiry types. Symptom-related inquiries accounted for 92 of 143 calls (64%), with 253 symptoms documented overall. Respiratory symptoms were most common (100/253, 40%), especially shortness of breath (35 calls), cough (26), and fatigue (23). Call volumes peaked from January to June 2021, coinciding with the provincial vaccine rollout.</p><p><strong>Conclusions: </strong>The GIM-COVID-19 Long-Term Sequelae RACE line served as a critical early support system for primary care providers as the long COVID landscape evolved. This quality improvement study emphasizes the value of rapid access and specialist-informed consultation tools during emerging public health challenges. The trends ascertained may inform future health system responses, particularly when designing more scalable, interdisciplinary models to support primary care in managing complex chronic conditions.</p>","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"7 ","pages":"e57021"},"PeriodicalIF":0.0,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12892256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146159555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Administration Technique of Intranasal Corticosteroid Sprays Among Nepali Pharmacists: Cross-Sectional Study.","authors":"Amar Prashad Chaudhary, Suraj Kumar Thakur, Shiv Kumar Sah","doi":"10.2196/83042","DOIUrl":"10.2196/83042","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Allergic rhinitis is a common condition affecting up to 40% of people worldwide, with a notably high prevalence in South Asia. The primary treatment for moderate to severe allergic rhinitis is intranasal corticosteroid sprays (INCS), the use of which is typically demonstrated to patients by registered pharmacists. However, many patients do not use these sprays correctly.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study evaluated the proficiency of pharmacists in demonstrating the correct technique for using INCS and the factors contributing to proper technique.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In a cross-sectional survey of 365 registered pharmacists in the Kathmandu Valley, Nepal, a trained observer used a standardized 12-step checklist to assess each pharmacist's technique for using INCS. The 12-step checklist was created after studying international guidelines, studies conducted in Nepal, international research articles, and instructional pamphlets. Simple random sampling was done to collect the data from community pharmacies in Kathmandu district. Demographics, education, experience, previous training, and instructional materials use were recorded. A total of 12 marks were awarded for all 12 steps, with one mark given for each step. Proficiency was classified as \"adequate\" if more than 6 marks were obtained.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Out of 365 pharmacists, 239 (65.5%) were male and 126 (34.5%) were female. Overall, 216 pharmacists (59.2%) were aged 26 years or younger and 235 pharmacists (69.9%) held a diploma in pharmacy. We found that 193 (52.9%) pharmacists demonstrated inadequate technique, while only 172 (47.1%) showed adequate skill overall. However, only 22 pharmacists (6%) demonstrated all 5 critical steps. The likelihood of providing appropriate counseling on the use of INCS was significantly correlated with multiple independent factors. Those with a diploma in pharmacy had a 97% lower likelihood of providing appropriate counseling compared with those with a bachelor's degree in pharmacy and above (P&lt;.001). Pharmacists who perform counseling sessions 1-4 times per week had 11-fold greater odds of doing so correctly compared with those who do not (P=.002). Pharmacists who do not use educational leaflets were 96% less likely to provide adequate counseling (P= .005) . Similarly, pharmacists under the age of 26 are 89% less likely than older pharmacists to provide adequate counseling (P=.001). It is interesting to note that men were found to have almost 2.3 times higher odds of providing appropriate counseling than women (P=.02).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;More than half of the registered pharmacists in Nepal demonstrated inadequate technique when using INCS. The inadequate patient counseling on INCS use can significantly increase the risk of adverse drug reactions and reduce the efficacy of the therapy. Thus, there is a strong need for educational interventions and policy change for improved pr","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"7 ","pages":"e83042"},"PeriodicalIF":0.0,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12855720/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146088449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automating Individualized Notification of Drug Recalls to Patients: Complex Challenges and Qualitative Evaluation.","authors":"Meghana Gadgil, Rose Pavlakos, Simona Carini, Brian Turner, Ileana Elder, William Hess, Lisa Houle, Lavonia Huff, Elaine Johanson, Carole Ramos-Izquierdo, Daphne Liang, Pamela Ogonowski, Joshua Phipps, Tyler Peryea, Ida Sim","doi":"10.2196/68345","DOIUrl":"10.2196/68345","url":null,"abstract":"<p><strong>Background: </strong>Consumer-level drug recalls usually require action by individual patients. The Food and Drug Administration (FDA) has public-facing outlets to inform the public about drug safety information, including all recalls, but individual consumers may not be aware of them. And there is no system in place to notify individual prescribers which of their patients are affected by a specific recall.</p><p><strong>Objective: </strong>We aimed to leverage the FDA's Healthy Citizen prototype web-based software platform, which provides users with information about recalls, to automatically notify patients of relevant recalls.</p><p><strong>Methods: </strong>We developed and evaluated an electronic notification system in the primary care and cardiology practices at a large, urban, academic medical center. The health care portal scanned the FDA Healthy Citizen application programming interface nightly to detect new recalls, identified patients who had those medications in their electronic health record (EHR) medication list, and sent them a message through the EHR patient portal with a link to a customized FDA information display. Using structured interviews, we assessed qualitative feedback on the system and portal messaging from a convenience sample of 9 patients.</p><p><strong>Results: </strong>The system was technically functional, but it was not possible to trace a medication prescription from the EHR to specific lot numbers dispensed to that patient by a community pharmacy. The qualitative feedback obtained from patients showed convergence of topics.</p><p><strong>Conclusions: </strong>Lack of an accurate electronic audit trail from prescription to dispensed medication precludes clinical deployment of automated drug recall notification.</p>","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"7 ","pages":"e68345"},"PeriodicalIF":0.0,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12798837/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145967643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the Financial Factors Influencing Maternal, Newborn, and Child Health in Africa: Tobit Regression and Data Envelopment Analysis.","authors":"Youssef Er-Rays, Meriem M'dioud, Hamid Ait-Lemqeddem, Badreddine El Moutaqi","doi":"10.2196/59703","DOIUrl":"10.2196/59703","url":null,"abstract":"<p><strong>Background: </strong>Despite international efforts, maternal, newborn, and child health (MNCH) outcomes in Africa continue to lag due to inefficient health systems and underperforming financial frameworks. Financial factors-such as total health expenditure, health coverage indices, and spending per capita-are key but understudied drivers of MNCH service efficiency.</p><p><strong>Objective: </strong>This study investigates the extent to which financial inputs influence the technical efficiency of MNCH service delivery across 46 African countries. The aim is to generate evidence for health financing policies that can enhance both efficiency and health equity.</p><p><strong>Methods: </strong>We adopted a 2-stage analytical framework. First, data envelopment analysis using a variable returns-to-scale, input-oriented model was applied to measure technical efficiency. Second, Tobit regression identified the financial determinants of inefficiency. Explanatory variables included current health expenditures, a health coverage index, and current health expenditures per capita.</p><p><strong>Results: </strong>Only 12 of 46 countries (26%) achieved full technical efficiency (efficiency score=1), while the rest (n=34, 74%) were inefficient, with a mean score of 0.849. Efficiency was notably lower in low-income countries (mean 0.810) compared to upper-middle-income countries (mean 0.940). Tobit regression showed that increased current health expenditure significantly reduced inefficiency (β=-.0811; P=.001). Conversely, a higher health coverage index unexpectedly increased inefficiency (β=.0155; P=.001), suggesting that expanded coverage without improved governance or resource capacity may strain systems. Health expenditure per capita was not statistically significant. Model 2 demonstrated stronger explanatory power (pseudo R²=0.8943).</p><p><strong>Conclusions: </strong>Financial factors, particularly total health expenditure, play a decisive role in shaping MNCH efficiency across African nations. However, expanding health coverage without parallel improvements in system governance may exacerbate inefficiencies. To enhance MNCH outcomes, policy efforts must focus on increasing and strategically allocating financial resources while strengthening institutional accountability and performance.</p>","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"6 ","pages":"e59703"},"PeriodicalIF":0.0,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12675993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145672904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Limitations of Large Language Models in Clinical Practice Guideline-Concordant Treatment Decision-Making on Real-World Data: Retrospective Study.","authors":"Tobias Roeschl, Marie Hoffmann, Djawid Hashemi, Felix Rarreck, Nils Hinrichs, Tobias Daniel Trippel, Matthias I Gröschel, Axel Unbehaun, Christoph Klein, Jörg Kempfert, Henryk Dreger, Benjamin O'Brien, Gerhard Hindricks, Felix Balzer, Volkmar Falk, Alexander Meyer","doi":"10.2196/74899","DOIUrl":"10.2196/74899","url":null,"abstract":"<p><strong>Background: </strong>Studies have shown that large language models (LLMs) are promising in therapeutic decision-making, with findings comparable to those of medical experts, but these studies used highly curated patient data.</p><p><strong>Objective: </strong>This study aimed to determine if LLMs can make guideline-concordant treatment decisions based on patient data as typically present in clinical practice (lengthy, unstructured medical text).</p><p><strong>Methods: </strong>We conducted a retrospective study of 80 patients with severe aortic stenosis who were scheduled for either surgical (SAVR; n=24) or transcatheter aortic valve replacement (TAVR; n=56) by our institutional heart team in 2022. Various LLMs (BioGPT, GPT-3.5, GPT-4, GPT-4 Turbo, GPT-4o, LLaMA-2, Mistral, PaLM 2, and DeepSeek-R1) were queried using either anonymized original medical reports or manually generated case summaries to determine the most guideline-concordant treatment. We measured agreement with the heart team using Cohen κ coefficients, reliability using intraclass correlation coefficients (ICCs), and fairness using the frequency bias index (FBI; FBI >1 indicated bias toward TAVR).</p><p><strong>Results: </strong>When presented with original medical reports, LLMs showed poor performance (Cohen κ coefficient: -0.47 to 0.22; ICC: 0.0-1.0; FBI: 0.95-1.51). The LLMs' performance improved substantially when case summaries were used as input and additional guideline knowledge was added to the prompt (Cohen κ coefficient: -0.02 to 0.63; ICC: 0.01-1.0; FBI: 0.46-1.23). Qualitative analysis revealed instances of hallucinations in all LLMs tested.</p><p><strong>Conclusions: </strong>Even advanced LLMs require extensively curated input for informed treatment decisions. Unreliable responses, bias, and hallucinations pose significant health risks and highlight the need for caution in applying LLMs to real-world clinical decision-making.</p>","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"6 ","pages":"e74899"},"PeriodicalIF":0.0,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12587749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145446747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of the COVID-19 Pandemic on Routine Childhood Vaccination Coverage in Ecuador From 2019 to 2021: Comparative Analysis.","authors":"Jose Sanchez, Alejandro Arjuna Rodriguez, Kimberlly Pamela Montenegro Cuello","doi":"10.2196/75293","DOIUrl":"10.2196/75293","url":null,"abstract":"<p><strong>Background: </strong>The COVID-19 pandemic disrupted essential health care services globally, including routine childhood immunization programs. Ecuador faced significant challenges in maintaining vaccination coverage during this period.</p><p><strong>Objective: </strong>The aim of this study is to analyze the impact of the COVID-19 pandemic on routine childhood vaccination coverage in Ecuador by comparing prepandemic (2019) and pandemic (2020-2021) data.</p><p><strong>Methods: </strong>This retrospective observational study analyzed vaccination coverage data from the Ministry of Public Health of Ecuador and demographic data from the National Institute of Statistics and Censuses. We examined routine childhood vaccination coverage for children under 24 months across all 24 provinces. Statistical analyses were performed using SPSS (version 28.0), including descriptive statistics and comparative analysis. Coverage rates were calculated as percentages of children in target age groups receiving recommended doses.</p><p><strong>Results: </strong>A significant decline in routine childhood vaccination coverage was observed during the pandemic. BCG vaccine coverage decreased from 86.4% in 2019 (n=286,569) to 80.7% in 2020 (n=266,961) and 75.3% in 2021 (n=248,812). Pentavalent vaccine third dose coverage dropped from 85.0% to 68.0% across the same period. The most dramatic decline was seen in measles-mumps-rubella vaccine second dose coverage, falling from 75.7% in 2019 to 58.4% in 2021. Coastal and highland provinces experienced the most severe reductions, with approximately 137,000 fewer doses administered in 2020 compared to stable prepandemic levels.</p><p><strong>Conclusions: </strong>The COVID-19 pandemic significantly impacted routine childhood vaccination coverage in Ecuador, with sustained declines through 2021. Regional disparities were evident, with vulnerable populations facing greater challenges accessing immunization services. Urgent interventions, including catch-up campaigns and strengthened health systems, are needed to restore coverage levels and prevent outbreaks of vaccine-preventable diseases.</p>","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"6 ","pages":"e75293"},"PeriodicalIF":0.0,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12534038/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145314203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Conversational Artificial Intelligence-Based Web Application for Medical Consultations: Prototype Study.","authors":"Jorge Guerra Pires","doi":"10.2196/56090","DOIUrl":"10.2196/56090","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) has evolved through various trends, with different subfields gaining prominence over time. Currently, conversational AI-particularly generative AI-is at the forefront. Conversational AI models are primarily focused on text-based tasks and are commonly deployed as chatbots. Recent advancements by OpenAI have enabled the integration of external, independently developed models, allowing chatbots to perform specialized, task-oriented functions beyond general language processing.</p><p><strong>Objective: </strong>This study aims to develop a smart chatbot that integrates large language models from OpenAI with specialized domain-specific models, such as those used in medical image diagnostics. The system leverages transfer learning via Google's Teachable Machine to construct image-based classifiers and incorporates a diabetes detection model developed in TensorFlow.js. A key innovation is the chatbot's ability to extract relevant parameters from user input, trigger the appropriate diagnostic model, interpret the output, and deliver responses in natural language. The overarching goal is to demonstrate the potential of combining large language models with external models to build multimodal, task-oriented conversational agents.</p><p><strong>Methods: </strong>Two image-based models were developed and integrated into the chatbot system. The first analyzes chest X-rays to detect viral and bacterial pneumonia. The second uses optical coherence tomography images to identify ocular conditions such as drusen, choroidal neovascularization, and diabetic macular edema. Both models were incorporated into the chatbot to enable image-based medical query handling. In addition, a text-based model was constructed to process physiological measurements for diabetes prediction using TensorFlow.js. The architecture is modular; new diagnostic models can be added without redesigning the chatbot, enabling straightforward functional expansion.</p><p><strong>Results: </strong>The findings demonstrate effective integration between the chatbot and the diagnostic models, with only minor deviations from expected behavior. Additionally, a stub function was implemented within the chatbot to schedule medical appointments based on the severity of a patient's condition, and it was specifically tested with the optical coherence tomography and X-ray models.</p><p><strong>Conclusions: </strong>This study demonstrates the feasibility of developing advanced AI systems-including image-based diagnostic models and chatbot integration-by leveraging AI as a service. It also underscores the potential of AI to enhance user experiences in bioinformatics, paving the way for more intuitive and accessible interfaces in the field. Looking ahead, the modular nature of the chatbot allows for the integration of additional diagnostic models as the system evolves.</p>","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"6 ","pages":"e56090"},"PeriodicalIF":0.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12527318/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145304925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating Variance of Log Standardized Incidence Ratios Assessing Health Care Providers' Performance: Comparative Analysis Using Bayesian, Bootstrap, and Delta Method Approaches.","authors":"Solomon Woldeyohannes, Yomei Jones, Paul Lawton","doi":"10.2196/77415","DOIUrl":"10.2196/77415","url":null,"abstract":"<p><strong>Background: </strong>In health care providers' performance assessment, standardized incidence ratios are essential tools used to assess whether observed event rates deviate from expected values. Accurate estimation of variance in these ratios is crucial as it affects decision-making regarding providers' performance. There is little data on how the choice of these variance estimation methods affects decision-making.</p><p><strong>Objective: </strong>In this study, we compared 3 methods (the delta method, bootstrapping method, and Bayesian approach) to estimate the variance of the logarithm of the standardized incidence ratio.</p><p><strong>Methods: </strong>Using patient-level data from the Australia and New Zealand Dialysis and Transplant Registry for 2012-2023, we used a random effects model to predict treatment at home 1 year after starting treatment. We compared the 3 approaches (with more than 5000 iterations for bootstrapping and Markov chain Monte Carlo sampling) using bias, variance, and mean squared error (MSE) as performance measures. Using the 3 methods, funnel plots were used to compare the hospitals' performance in treating Indigenous and non-Indigenous patients close to home, as a service-level measure of equity.</p><p><strong>Results: </strong>The bias values across all methods were similar, with the Bayesian method narrowly having the lowest bias (0.01922), followed by the delta method (0.01927) and bootstrap method (0.02567). In addition, the Bayesian method exhibited the lowest variance (0.00005), indicating more stable and less dispersed estimates. The delta method had a higher variance (0.00016), while the bootstrap method had the highest variance (0.00027), meaning it introduced more uncertainty. Finally, the Bayesian method had the lowest MSE (0.00042), indicating better overall accuracy, while the bootstrap method had the highest MSE (0.00094), showing it was the least reliable method.</p><p><strong>Conclusions: </strong>We demonstrated that these methods can be used to measure equity for patient-centered outcomes, both within and between service providers simultaneously. The choice of variance estimation method is critical and heavily affects the interpretation of the performance of health service providers. We favor the Bayesian Markov chain Monte Carlo method as it was found to be a better approach.</p>","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"6 ","pages":"e77415"},"PeriodicalIF":0.0,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12605305/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145260148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-World Performance of COVID-19 Antigen Tests: Predictive Modeling and Laboratory-Based Validation.","authors":"Miguel Bosch, Dawlyn Garcia, Lindsey Rudtner, Nol Salcedo, Raul Colmenares, Sina Hoche, Jose Arocha, Daniella Hall, Adriana Moreno, Irene Bosch","doi":"10.2196/68376","DOIUrl":"10.2196/68376","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Rapid and safe deployment of lateral-flow antigen tests, coupled with uncompromised quality assurance, is critical for outbreak control and pandemic preparedness, yet real-world performance assessment still lacks laboratory and quantitative approaches that remain uncommon in current regulatory science. The approach proposed here can help standardize and accelerate early phase appraisal of antigen tests in preparation for clinical validation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The aim of this study is to present a quantitative, laboratory-anchored framework that links image-based test line intensities and the population distribution of naked-eye limits of detection (LoD) to a probabilistic prediction of positive percent agreement (PPA) as a function of viral-load-related variables (eg, quantitative real-time polymerase chain reaction [qRT-PCR] cycle thresholds [Cts]). Using dilution-series calibrations and a Bayesian model, the predicted PPA-vs-Ct curve closely tracks the observed PPA in a real-world self-testing cohort.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The proposed methodology combines: (1) a quantitative evaluation of the test signal response to concentrations of target protein and inactive virus or active virus, (2) a statistical characterization of the LoD using the observer's visual acuity of the test band, and (3) a calibration of a gold-standard method (eg, qRT-PCR cycles) against virus concentration. We elaborate these quantitative methods and unfold a Bayesian-based predictive model to describe the real-world performance of the antigen test, quantified by the probability of positive agreement as a function of viral-load variables like qRT-PCR Cts.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;We applied the methodology by characterizing each brand of COVID-19 antigen test and estimating its real-world probability of agreement with qRT-PCR. We aligned protein and inactivated-virus standard curves at matched signal intensities and fit a linear calibration linking protein to viral concentrations. Using logistic regression, we modeled the PPA as a continuous function of qRT-PCR Ct, then integrated this curve over a predefined reference Ct distribution to obtain the expected sensitivity. This standardization enables consistent performance comparisons across sites.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Modeling performance under real-world conditions requires coupling laboratory evaluation with the population's ability to perceive the test's visual signal. We represent observer capability as a probability density function of the LoD over the signal-intensity domain. Rather than reporting bin-based sensitivity, we summarize performance with the PPA as a continuous function of qRT-PCR Ct. Our framework produces PPA-Ct curves by composing (1) normalized signal-to-concentration models from the laboratory, (2) the observer LoD distribution, and (3) a Ct-to-viral-load calibration. The resulting inferences are inherently context-bound-di","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"6 ","pages":"e68376"},"PeriodicalIF":0.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12500314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145240491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Interventions for the Prevention and Management of Maternal Anemia in the Advent of the COVID-19 Pandemic: Systematic Review and Meta-Analysis.","authors":"John Kyalo Muthuka, Dianna Kageni Mbari-Fondo, Francis Muchiri Wambura, Kelly Oluoch, Japheth Mativo Nzioki, Everlyn Musangi Nyamai, Rosemary Nabaweesi","doi":"10.2196/57626","DOIUrl":"10.2196/57626","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The COVID-19 pandemic presented many unknowns for pregnant women, with anemia potentially worsening pregnancy outcomes due to multiple factors.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This review aimed to determine the pooled effect of maternal anemia interventions and associated factors during the pandemic.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Eligible studies were observational and included reproductive-age women receiving anemia-related interventions during the COVID-19 pandemic. Exclusion criteria comprised non-English publications, reviews, editorials, case reports, studies with insufficient data, sample sizes below 50, and those lacking DOIs. A systematic search of PubMed, Scopus, Embase, Web of Science, and Google Scholar identified articles published between December 2019 and August 2022. Risk of bias was evaluated using the Cochrane Risk of Bias 2 tool for randomized trials and the National Institutes of Health's assessment tool for observational studies. Pooled rate ratios (RRs) with 95% CIs were calculated in Review Manager 5.4.1. Synthesis included subgroup analysis, meta-regression, and publication bias checks to assess intervention effectiveness.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;This meta-analysis included 11 studies with 6129 pregnant women. Of these, 3591 (59%) were in the intervention group and 2538 (41%) were in the comparator group. Effects were recorded for 1921 (53.4%) women in the intervention group and 1350 (53.1%) in the comparator group. The cumulative impact ranged from 23% to 81%, averaging 56%. The initial analysis showed no significant effect on anemia prevention (RR 0.79, 95% CI 0.61-1.02; P=.07), with high heterogeneity (I²=97%). Sensitivity analysis excluding 4 outlier studies improved the effect size to a significant level at 39% (RR 0.61, 95% CI 0.43-0.87; P=.006). Subgroup analysis revealed substantial heterogeneity (I²=87.2%). Intravenous sucrose had a poor impact (RR 1.31, 95% CI 1.17-1.47; P&lt;.001), while medicinal or herbal interventions showed benefit (RR 0.81, 95% CI 0.73-0.90; P=.006). Educational interventions yielded a 28% effect (RR 0.72), medicinal administration 19% (RR 0.81), iron supplementation 17% (RR 0.83), and intravenous ferric carboxylmaltose 15% (RR 0.85; P&lt;.02). Additional sensitivity analysis confirmed a pooled positive effect of 17% (RR 0.83, 95% CI 0.79-0.88; P&lt;.001), with minimal heterogeneity (I²=0%). Regionally, effectiveness was highest in Africa (RR 0.84, 95% CI 0.79-0.89; P&lt;.001). Multicenter studies and those with 2020 data were predictive of better outcomes (RR 0.84 and RR 0.50, respectively). Despite initial heterogeneity and publication bias, interventions showed utility in mitigating maternal anemia in targeted subgroups and regions.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Maternal anemia interventions during the COVID-19 pandemic showed modest, context-specific effectiveness, with declining impact from 2020 to 2022. Although high heterogeneity and study inconsi","PeriodicalId":73558,"journal":{"name":"JMIRx med","volume":"6 ","pages":"e57626"},"PeriodicalIF":0.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12645416/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145240432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}