Category: Nevin Manimala

Int Endod J. 2026 Mar 13. doi: 10.1111/iej.70142. Online ahead of print.

ABSTRACT

BACKGROUND: Artificial intelligence (AI) is transforming medical imaging, yet its economic impact in dentistry remains largely unexplored.

AIM: This study evaluated the cost-effectiveness of AI-assisted detection of apical periodontitis on panoramic radiographs, including downstream clinical decision-making.

MATERIAL AND METHODS: Using data from a randomised study on AI-assisted detection of apical lesions, a decision-analytic model was established to analyse costs and effectiveness from a German mixed-payer perspective.

RESULTS: AI support reduced average costs per case and increased treatment effectiveness, outperforming unaided examiner performance. These gains were primarily driven by improved specificity, reducing false-positive detection. However, effects varied by examiner experience; junior clinicians achieved the greatest cost savings and effectiveness gains, whereas senior examiners showed reduced sensitivity and slightly lower effectiveness at similar costs.

CONCLUSION: AI-assisted diagnostics offer significant potential to improve cost-effectiveness by reducing overtreatment, with benefits being most pronounced among less experienced practitioners. Adapting AI systems to individual examiners or experience levels might further enhance clinical and economic impact.

PMID:41826269 | DOI:10.1111/iej.70142

Am J Hum Biol. 2026 Mar;38(3):e70242. doi: 10.1002/ajhb.70242.

ABSTRACT

OBJECTIVES: Changes in the timing of puberty may reflect shifts in population health, including the rising prevalence of overweight and obesity. Therefore, this study aimed to analyze the longitudinal association between body mass index (BMI) in childhood and pubertal development 5 years later among Brazilian students.

METHODS: This longitudinal study included 494 students aged 7-10 years. Data were collected in 2007 and 2012. BMI z-scores were calculated. Pubertal development was self-assessed using Tanner stages, and girls reported age at menarche. Structural equation modeling was used to assess the effects of the 2007 BMI on sexual maturation (SM) in 2012, adjusting for socioeconomic status (SES), birth weight, breastfeeding, physical activity, and dietary patterns (DP).

RESULTS: No statistically significant association between BMI and SM was observed in either sex. Among boys, higher adherence to DP IV (milk, coffee with milk, cheese, breads/biscuits) (β = -0.21) and higher SES (β = -0.21) were associated with normal/late SM. Among girls, a higher 2007 BMI z-score (β = -0.27) had a direct negative effect on age at menarche, while DP II (ultra-processed foods) showed an indirect negative effect on age at menarche, mediated by the 2007 BMI z-score (β = -0.05).

CONCLUSIONS: This study found that in girls, higher childhood BMI was associated with an earlier age at menarche. In boys, DP IV and SES were associated with normal/late SM. These findings highlight the significance of monitoring puberty timing at the population level and the need for sex-sensitive, prospective research to elucidate the determinants of earlier puberty, especially in low- and middle-income countries.

PMID:41826258 | DOI:10.1002/ajhb.70242

J Med Imaging Radiat Oncol. 2026 Mar 13. doi: 10.1111/1754-9485.70084. Online ahead of print.

ABSTRACT

BACKGROUND: Beta Thalassaemia Major is a hereditary disorder characterised by defective protein synthesis in the beta-globin chain, leading to chronic anaemia. As a consequence of repeated blood transfusions used to manage anaemia, excessive iron accumulation occurs, primarily in the liver and other vital organs, leading to organ damage.

PURPOSE: To determine the correlation between liver iron concentration and iron accumulation in the liver due to blood transfusions in paediatric patients diagnosed with Beta Thalassaemia Major, using shear wave elastography and liver magnetic resonance imaging apparent diffusion coefficient measurements.

MATERIALS AND METHODS: A prospective study was conducted from January 2025 to April 2025 on 77 paediatric patients diagnosed with Beta Thalassaemia Major, utilising liver shear wave elastography, liver apparent diffusion coefficient, T2* values and serum ferritin levels.

RESULTS: Descriptive statistics for the continuous variables of the patients: elasticity median (10.39 ± 4.39 kPa), velocity median (1.81 ± 0.36 m/s), liver ADC (0.52 ± 0.42), liver T2* (4.93 ± 5.15), LIC (9.45 ± 5.7). The median elasticity values differed significantly across the iron overload severity groups (p = 0.006). A post hoc analysis was performed to identify the groups responsible for this difference. The analysis revealed that the differences originated from comparisons between the mild (9.58 ± 3.62) and severe (14.44 ± 5.91) groups, the moderate (9.47 ± 3.24) and severe (14.44 ± 5.91) groups and the severe (14.44 ± 5.91) and normal (8.16 ± 2.44) groups (p^ac < 0.001; p^bc < 0.001; p^cd = 0.003).

CONCLUSION: We demonstrated a correlation between liver shear wave elastography and liver apparent diffusion coefficient values with MRI T2* and LIC in the group of paediatric patients diagnosed with Beta Thalassaemia Major who had a high liver iron burden.

PMID:41826250 | DOI:10.1111/1754-9485.70084

Med Decis Making. 2026 Mar 13:272989X261423177. doi: 10.1177/0272989X261423177. Online ahead of print.

ABSTRACT

BackgroundClinical trial designs are typically narrowly focused on error control in hypothesis testing, but this approach is inadequate in many contexts, particularly when a decision maker intends to, or must, consider multiple relevant clinical and health economic outcomes under uncertainty. Value-of-information (VoI) metrics can be used to estimate the monetary value of data collection to the decision maker. Adaptive trial designs use prespecified decision rules as data are collected and analyzed to modify the ongoing trial design. To date, VoI considerations have rarely been integrated into this approach, partly due to the computational burden.MethodsWe propose a value-driven adaptive design that refocuses trial design on VoI as a metric to direct trial adaptations. Specifically, a VoI analysis is performed at each interim analysis to determine whether or not the trial should proceed to the next analysis (i.e., determine whether further data collection is sufficiently valuable). We provide methods to compute the expected net benefit of perfect information, expected net benefit of sampling (ENBS) for the next analysis, and the ENBS for subsequent sequential analyses. Our approach is flexible to any statistical model, decision model, and research cost function and does not require distributional assumptions about the net benefit.ResultsWe describe our method in detail and demonstrate its implementation via a case study comparing infant immunoprophylaxis and maternal vaccination to prevent respiratory syncytial virus-related medical attendances.ConclusionsOur value-driven adaptive design aligns pragmatic clinical trial design with the requirements of decision makers. Designs with VoI-based adaptations have the potential to improve the cost-effectiveness of clinical trials.HighlightsOur value-driven adaptive design is a new method that uses the expected net benefit of sampling to define stopping rules at interim analyses (i.e., to determine if further data collection is sufficiently valuable).Our method orients trial designs to efficiently produce evidence to inform the decision maker.

PMID:41826246 | DOI:10.1177/0272989X261423177

Vet Rec. 2026 Mar 13. doi: 10.1002/vetr.70499. Online ahead of print.

ABSTRACT

BACKGROUND: Data evaluating paracetamol combined with NSAIDs in dogs are scarce. Results of clinical studies in dogs investigating intravenous paracetamol vary.

METHODS: Dogs were randomised to either receive 10 mg/kg paracetamol intravenously after induction of anaesthesia and every 8 hours during hospitalisation (test) or not (control). In both groups, meloxicam or robenacoxib was administered at the licensed dose, interval and route. Intraoperative nociception or postoperative pain, defined by a Glasgow composite measure pain scale-short form score greater than 4 of 20, was treated with 0.1 mg/kg methadone intravenously as needed.

RESULTS: Data from 14 dogs that received paracetamol and 13 dogs that did not were analysed. There were no statistically significant differences in clinical or demographic data between the two groups. Median (range) rescue methadone requirements were 0.0 (0.0‒0.2) mg/kg and 0.1 (0.0‒0.3) mg/kg for the test and control groups, respectively (p = 0.17), with no difference intraoperatively (p = 0.72) or postoperatively (p = 0.24). Four test and seven control dogs required rescue analgesia perioperatively (p = 0.17).

LIMITATIONS: Low analgesia requirements in both groups may have resulted in a type two statistical error.

CONCLUSION: When used as part of a multimodal analgesic protocol, paracetamol did not provide significant opioid-sparing effects in the perioperative period.

PMID:41826244 | DOI:10.1002/vetr.70499

Vet Rec. 2026 Mar 13. doi: 10.1002/vetr.70495. Online ahead of print.

ABSTRACT

BACKGROUND: Non-ambulatory tetraparesis or tetraplegia in cats may constitute a diagnostic challenge for general practitioners. Therefore, this study aimed to evaluate if clinical variables from signalment, history, clinical examination and basic ancillary tests are associated with underlying diagnoses in cats with non-ambulatory tetraparesis or tetraplegia.

METHODS: This was a retrospective single-centre study of cases presented between 2010 and 2023. Information on disease onset, progression, neurological and physical examination findings and ancillary tests was analysed across all diagnoses. Diagnostic categories comprising five or more cases were carried forward to univariate and/or multivariable analyses.

RESULTS: Eighty-one cats were included, with 82.7% of cases represented by six conditions: polyneuropathy (PN; n = 26), ischaemic myelopathy (IM; n = 15), spinal cord neoplasia (n = 8), feline infectious peritonitis (n = 7), intracranial neoplasia (n = 6) and spinal cord contusion (n = 5). On multivariable analysis, an age of below 3 years, progressive presentation, normal mentation, reduced spinal reflexes in the thoracic limbs and normal blood tests were statistically associated with PN. Age between 6 and 9 years or older than 9 years and peracute onset of clinical signs were associated with IM.

LIMITATIONS: This was a retrospective study with limited multivariable analysis in certain diagnostic categories. Furthermore, the study included only referral cases, which may not represent the animal population seen by general practitioners.

CONCLUSIONS: PN and IM were the most common causes for non-ambulatory tetraparesis or tetraplegia in this population of cats. Attention to the neurological examination and easy to identify clinical features can be used to determine the most likely differential diagnoses and assist general practitioners in the formulation of a diagnostic plan.

PMID:41826233 | DOI:10.1002/vetr.70495

Semin Nucl Med. 2026 Mar 12:S0001-2998(26)00044-9. doi: 10.1053/j.semnuclmed.2026.02.002. Online ahead of print.

ABSTRACT

Nuclear medicine infection imaging has traditionally relied on semantic visual interpretation supported by simple semi-quantitative indices. While effective, this paradigm is limited by observer dependence, restricted sensitivity to subtle or diffuse disease, and difficulty in standardising interpretation across centres. Advances in quantitative imaging, radiomics and artificial intelligence (AI) are reshaping this landscape. These complementary domains, collectively conceptualised as computomics, extend infection imaging from qualitative pattern recognition toward objective, reproducible and data-driven characterisation of disease. Quantitative imaging converts tracer distribution into measurable biological metrics, ranging from simple region-of-interest count ratios to standardised uptake values and kinetic parameters. Radiomics builds on this foundation by extracting high-dimensional features describing intensity, shape, texture and spatial heterogeneity, revealing image information not appreciable to the human eye. AI, through machine learning and deep learning approaches, integrates quantitative and radiomic data with clinical variables to automate segmentation, enhance reconstruction, support classification, and enable predictive modelling. Together, these tools offer potential to improve differentiation of infection from sterile inflammation, quantify disease burden, monitor therapy response, and standardise interpretation in complex scenarios. Quantitative accuracy and radiomic stability remain highly dependent on acquisition, reconstruction and processing parameters. AI-driven image enhancement and denoising may improve visual appearance while altering voxel statistics, with downstream effects on quantitative metrics and texture features. Variability in feature definitions, segmentation methods and analysis pipelines further limits reproducibility. Consequently, harmonisation, standardisation, transparent validation and physics-informed AI models are essential.

PMID:41826111 | DOI:10.1053/j.semnuclmed.2026.02.002

J Nutr. 2026 Mar 12:101398. doi: 10.1016/j.tjnut.2026.101398. Online ahead of print.

ABSTRACT

BACKGROUND: Data from randomized controlled trials of vitamin D₃ supplementation in modifying the course of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are sparse.

OBJECTIVES: We evaluated the effect of vitamin D₃ supplementation on healthcare utilization and other clinical outcomes among adults with coronavirus disease 2019 (COVID-19) and their close contacts.

METHODS: We conducted a parallel 2-group randomized controlled double-blinded trial targeting free-living adults in the United States and Mongolia. Index participants with newly diagnosed COVID-19 were cluster-randomized with up to one of their cohabiting contacts either to an oral vitamin D₃ loading dose of 9600 IU/d for 2 d followed by 3200 IU/d for 4 wk or to placebo. Participants completed weekly questionnaires on healthcare utilization, disease severity, and long COVID (index participants) or new SARS-CoV-2 infection (household contacts). The primary outcome was ≥1 healthcare visits (including hospitalization) or death within 4 wk among the index participants.

RESULTS: Index participants (n = 1747) were a median of 38.0 y old (IQR: 31.1-47.0), 65.6% female/other sex, 4.2% Black non-Hispanic, 4.8% Hispanic/Latinx, 43.2% Asian, 44.3% non-Hispanic White, and 44.9% vitamin D deficient or insufficient (25-hydroxyvitamin D₃ <20 ng/mL). Baseline characteristics for the household contacts (n = 277) were similar. The 4-wk cumulative incidence of healthcare utilization in index participants did not significantly differ between the vitamin D₃ (n = 863) and placebo (n = 884) groups [cumulative incidences, 0.28 compared with 0.29; odds ratio (OR), 0.97; 95% confidence interval (CI): 0.75, 1.24]. Similar nonsignificant results were observed for the prespecified secondary treatment and prevention outcomes, though per-protocol analyses showed a nonsignificant trend toward benefit of vitamin D₃ on the prevalence of long COVID at 8 wk (OR, 0.78; 95% CI: 0.59, 1.03). No safety concerns were identified.

CONCLUSIONS: Among adults with newly diagnosed SARS-CoV-2 infections, vitamin D₃ supplementation did not significantly change the 4-wk cumulative incidence of healthcare utilization or COVID-19-related outcomes compared with placebo. Promising results for long COVID warrant further study. This study was registered at clinicaltrials.gov as NCT04536298. First registered on 1 September, 2020.

PMID:41826107 | DOI:10.1016/j.tjnut.2026.101398

J Prosthet Dent. 2026 Mar 12:S0022-3913(26)00090-9. doi: 10.1016/j.prosdent.2026.02.009. Online ahead of print.

ABSTRACT

STATEMENT OF PROBLEM: Systematic reviews (SRs) are time-consuming and resource-intensive processes. Whether large language models (LLMs) can improve the process is unclear.

PURPOSE: The purpose of this study was to evaluate the accuracy and reliability of 4 LLMs (GPT-4, Gemini, Claude, and Elicit) in performing SR tasks (full-text screening, data extraction, and risk of bias assessment) at 3 different sequential periods of time (0, 15, and 30 days).

MATERIAL AND METHODS: A comprehensive systematic search was conducted across 5 databases in December 2024, with 59 articles evaluated for screening (2 used for pilot) and 31 for data extraction (2 used for pilot). A 3-pronged prompting strategy was used, including persona-based initialization, few-shot learning, and structured population, intervention, control, outcome (PICO) criteria. Performance was assessed through 3 repeated evaluations at 2-week intervals by measuring accuracy and reliability using standard metrics (accuracy, precision, F1-score, sensitivity, and specificity) against expert assessments, data extraction quality on a 0 to 5 scale, and risk of bias agreement via the Cohen kappa, with statistical analysis using Kruskal-Wallis and Dunn post-hoc tests (α=.05).

RESULTS: In full-text screening, Claude achieved the highest sensitivity at 97%, while Claude and Elicit both showed strong overall performance with 86% accuracy and 87% F1-scores. All models maintained sensitivity above 90%. For data extraction, GPT-4 consistently performed best with median scores of 5.0, while Claude and Gemini showed similar capabilities. Significant differences only appeared in labeling and modeling tasks during Week 1 (P=.04). Risk of bias assessment agreement with experts varied from 55% to 90% across different criteria.

CONCLUSIONS: LLMs show potential for SR efficiency (especially for data extraction) but require human oversight because of variable performance across models and tasks.

PMID:41826091 | DOI:10.1016/j.prosdent.2026.02.009

Orthop Surg. 2026 Mar 13. doi: 10.1111/os.70277. Online ahead of print.

ABSTRACT

BACKGROUND: In the multiple ligament injury of the knee joint, apart from the anterior cruciate ligament and the posterior cruciate ligament, the Posterolateral Corner and the Posteromedial Corner are two structures that are easily overlooked. If not properly identified and repaired in one stage, the knee joint may be unstable, even failure of cruciate ligament reconstruction. The purpose of this article was to evaluate the effect of knee joint recovery after PLC (Posterolateral Corner) with or without PMC (Posteromedial Corner) injury.

METHODS: From 2016 to 2020, we screened a total of 2564 patients, of which 292 patients met the inclusion and exclusion criteria. In the end, a total of 44 people completed the study. Follow-up was performed at 1, 3, 6, 9, and 12 months after surgery. We used pain visual analog scale (VAS) for pain, IKDC score, Lysholm score, Tegner score. Opti-knee (a portable motion analysis system) was used to evaluate the stability of the knee joint at 1 year. In our prospective cohort study, we used the unpaired Student’s t-test for statistical analysis.

RESULTS: The knee joint function of PLC group and PLC combined PMC group was better than that before operation at 3 or 6 months after operation. Except for IKDC at 9-month follow-up and Tegner score at 9-month and 12-month follow-up, there was no significant difference between the other groups.

CONCLUSIONS: PLC and PLC combined with PMC injury showed similar prognostic effects, although the PLC group was numerically superior to the other group. We recommend primary repair and reconstruction in patients with confirmed PLC and PMC injuries to achieve the best postoperative recovery.

PMID:41826073 | DOI:10.1111/os.70277