Nevin Manimala

J Dent. 2026 Apr 2:106670. doi: 10.1016/j.jdent.2026.106670. Online ahead of print.

ABSTRACT

OBJECTIVES: This study examined the impact of the COVID-19 pandemic on presentation, referrals, diagnoses, stage distribution, primary treatment, and survival for Head and Neck Cancer (HNC) patients in Northern Ireland (NI) by analysing population-based patient level data collected during 2016-2023.

METHODS: Individual-level data for all patients diagnosed with HNC available on the regional Cancer Patient Pathway System (CaPPs) during the period 2016-2023 was accessed to examine the number of cancers diagnosed, referrals, diagnosis, stage at diagnosis, and first treatment. Northern Ireland Cancer Registry (NICR) data up to 2021 was used to estimate the proportion of patients managed by the regional Multidisciplinary Team (MDT) and provide additional key characteristics and survival information. Data on activity in primary dental care (2016-2023) was accessed from the Northern Ireland Statistics and Research Agency (NISRA). Four time-periods were compared: pre-pandemic (PP: January 2016-March 2020), initial pandemic (IP: April 2020-March 2021), initial recovery (IR: April 2021-March 2022) and pandemic recovery (PR: April 2022-May 2023).

RESULTS: Adult dental examinations in primary care dental services decreased by 78%, from a yearly average of 965,000 during the PP period to 218,000 during the IP period. The number of HNC patients assessed at the MDT did not change significantly over the period 2016-2023 (P>0.05) from an annual average of 322 in the PP period; 302 in the IP period; 315 in the IR period and 342 in RP. Although there was an increased proportion of late-stage HNCs (III and IV) in the IP period, this was only significant for the oral cancer subsite (51.7% PP versus 67.1% IP), with recovery in the following periods. There was a decrease in the number of HNC patients receiving surgery as first treatment, and conversely an increase in radiotherapy, across the four time periods. The number of patients undergoing surgery as first treatment type decreased from PP (136) to IP periods (119) and failed to recover to pre-pandemic levels (117 in PR). Short-term (2-year) observed and net survival was not significantly different for HNC patients diagnosed pre-pandemic compared to periods thereafter (IP, IR, RP). The largest decrease in 2-year net survival was found for oral cancer, from 64.7% (PP) to 57.3% (IR), which approached significance (P=0.06).

CONCLUSION: The COVID-19 pandemic had wide-ranging impacts on HNC in Northern Ireland with substantially fewer examinations provided in primary dental care; reduced HNC incidence in the IP period; higher proportions of late-stage disease (statistically significant in oral cavity only); fewer surgical treatments and lower survival. These patterns approached statistical significance for oral cancers, the site most likely to be detected through dental screening.

CLINICAL SIGNIFICANCE: The COVID-19 pandemic severely impacted patient access to primary care dental services throughout NI, where clinical screening for HNC is undertaken by General Dental Practitioners (GDPs) as part of a dental check-up. This study demonstrates the importance of primary dental care services in the identification and early diagnosis of HNCs.

PMID:41935818 | DOI:10.1016/j.jdent.2026.106670

Environ Pollut. 2026 Apr 2:128058. doi: 10.1016/j.envpol.2026.128058. Online ahead of print.

ABSTRACT

Microplastics (MPs; 1-5000 μm) have been detected in various locations, and numerous surveys have been conducted in rivers to identify their sources and characterize the extent of MP pollution. However, standardized observation and analytical methods for small MPs have not yet been established, and the relationship between MP abundance and size-distribution characteristics remains poorly understood. This study aimed to characterize the size spectra of MP number and mass concentrations over a broad size range in river water and evaluate the applicability of a power-law model to these size spectra. To achieve this, we applied three different sampling methods to surface water in the Tsurumi River, Japan, yielding seven MP samples. The results demonstrated the statistical significance of the power-law approximation for the size spectra of the number and mass concentrations of MPs across all samples. The estimated power-law slopes were -3.27±0.19 and -1.05±0.20 for number and mass concentrations, respectively, which are close to the assumed values of -3 and -1, respectively. Additionally, MP mass concentrations were calculated from the measured values within a limited size range using the power-law model of the MP size spectrum. The results indicated that MP mass concentrations can be accurately estimated by extrapolating across unmeasured size ranges using a power-law relationship. This approach addresses a key limitation that has hindered inter-study comparisons owing to differences in the MP size ranges considered and provides an important step toward harmonizing MP datasets and improving the quantitative understanding of MP pollution in riverine environments.

PMID:41935770 | DOI:10.1016/j.envpol.2026.128058

Am J Cardiol. 2026 Apr 2:S0002-9149(26)00203-1. doi: 10.1016/j.amjcard.2026.03.060. Online ahead of print.

ABSTRACT

Traditional cardiovascular trials combine adverse events into composites, ignoring the clinical importance and weight of endpoints. The Win Ratio (“WR”) is a contemporary statistical technique overcoming these limitations. We aimed to evaluate outcomes of high-risk percutaneous coronary intervention supported with Impella® versus intra-aortic balloon pump (IABP), by pooling data from the PROTECT-II and PROTECT-III studies, using the win ratio. All patients from PROTECT-II RCT (“P-II”) and patients from PROTECT-III (“P-III”) who met P-II inclusion/exclusion criteria were pooled. The WR was based on independently adjudicated major adverse cardiac and cerebrovascular events (MACCE) at 90 days with following hierarchy: (1) Mortality; (2) Stroke; (3) Spontaneous Myocardial Infarction (sMI); 4) Re-Hospitalization; and (5) Peri-Procedural MI (pMI). All MACCE were analyzed as time-to-event outcomes, except pMI (binary endpoint). Sub-analyses included: 1) complex cases: patients with atherectomy or unprotected left main or chronic total occlusion, 2) all patients excluding firsts from P-II (“learning cases”); and 3) Impella P-II and P-III cohorts separately. Win statistics (WR, net benefit (NB), and win odds (WO)) were calculated. The primary analysis (719 Impella and 211 IABP-supported PCI) yielded a WR of 1.691 in favor of Impella (1.314-2.176, p<0.001), with NB of 0.166 (0.084-0.247, p<0.001) and WO of 1.398 (1.187-1.645, p<0.001). The WR, NB and WO for complex cases remained statistically significant in favor of Impella. Excluding first patients resulted in increased win statistics compared to primary analysis. In conclusion, pooled WR analyses from P-II and P-III studies demonstrated improved HRPCI outcomes up to 90 days with Impella compared to IABP.

PMID:41935767 | DOI:10.1016/j.amjcard.2026.03.060

J Arthroplasty. 2026 Apr 2:S0883-5403(26)00302-5. doi: 10.1016/j.arth.2026.03.078. Online ahead of print.

ABSTRACT

INTRODUCTION: Total knee arthroplasty (TKA) remains a highly successful and frequently performed procedure with variability in surgeon preferences regarding implant fixation and patellar resurfacing. This study aimed to characterize current practice patterns among members of The Knee Society and to identify key factors influencing implant fixation and patella resurfacing.

METHODS: A 23-question survey was distributed to 216 members of The Knee Society. The survey assessed demographic information, primary TKA volume, fixation technique preferences, patellar resurfacing practices, and the clinical rationale for these decisions. Responses were collected over a 4-week period in May 2025. Descriptive statistics were used to summarize the data.

RESULTS: The response rate was 48.1% (104 surgeons), with 52 (50.0%) being in practice greater than 25 years and 39 (37.9%) performing 201 to 300 primary TKAs annually. Cemented fixation was dominant, with an average use rate of 72.9%; 67.3% (70 surgeons) used both cemented and cementless implants, with an average cementless use of 35.8% of cases. Age (70.0%) and bone quality (82.9%) were the most cited indications for cementless use. Conversely, 35.6% (37 surgeons) reported using cemented fixation in all patients. Patellar resurfacing practices varied widely, with 34.7% (33 surgeons) reporting always resurfacing and individual rates ranging from 0 to 100%. 40.2% (41 surgeons) of respondents said their indications have changed in the past 5 years; resurfacing was most influenced by degree of arthritis (53.7%), patellar tracking (23.1%), and size/thickness (21.0 to 31.6%). Among surgeons performing cementless TKA, patellar resurfacing remained heterogeneous, and 40% (24 surgeons) still preferred cemented patellar components.

CONCLUSION: Cemented fixation in primary TKA remains the standard among expert TKA surgeons, though cementless techniques are increasingly used in select patients. Patellar resurfacing practices remain highly variable, reflecting individualized decision-making. These findings highlight evolving trends and underscore the need for continued research and consensus in primary TKA.

PMID:41935761 | DOI:10.1016/j.arth.2026.03.078

J Arthroplasty. 2026 Apr 2:S0883-5403(26)00272-X. doi: 10.1016/j.arth.2026.03.069. Online ahead of print.

ABSTRACT

BACKGROUND: The adoption of artificial intelligence (AI) scribes has grown rapidly in recent years, aiming to improve clinical workflow, increase efficiency, and reduce administrative burden by transcribing doctor-patient interactions. These systems capture in-office conversations and generate summaries using either standard or surgeon-specific templates. However, to date, no randomized controlled trials have rigorously assessed the proposed benefits of AI scribes. This randomized controlled trial focused on assessing AI scribe efficiency, error rate, accuracy, and patients’ perceptions in comparison to traditional clinical dictation-transcription methods.

METHODS: A randomized controlled trial was conducted involving 304 patients in a single-surgeon adult reconstruction practice. Patients were allocated into two groups: a conventional documentation group (using dictation transcribed by the office administrator or preconstructed templates: 140 patients) and an AI scribe group (139 patients). Timing data were recorded from when the surgeon entered a consultation room to when they began with the next patient. Additional data included administrative processing times, such as transcription and faxing of medical letters. All documentation was reviewed for medical errors by the surgeon in both groups. Grammar, spelling, and wrong wording were assessed by unblinded researchers. Letter quality was independently assessed using ChatGPT, focusing on grammar, clarity, and completeness.

RESULTS: Use of AI scribes resulted in a statistically significant reduction in both physician and administrative processing times (P < 0.0001). There was no significant difference in spelling or grammatical errors between groups. However, letters produced using AI scribes were rated as significantly more complete, professional, and clear. There were 19 medical errors in the AI scribe group compared to only nine errors in the conventional group. Patients were not negatively affected by using an AI scribe, and the vast majority found it helpful.

CONCLUSION: The use of AI scribes can effectively enhance clinical efficiency and reduce administrative workload without compromising documentation quality or patient safety. Their implementation offers meaningful benefits to both physicians and office staff, allowing more focus on patient care and other critical tasks.

PMID:41935758 | DOI:10.1016/j.arth.2026.03.069

J Affect Disord. 2026 Apr 2:121734. doi: 10.1016/j.jad.2026.121734. Online ahead of print.

ABSTRACT

BACKGROUND: Catatonia is a recurrent neuropsychiatric syndrome affecting approximately 9% of psychiatric inpatients, yet the impact of acute treatment strategies on long-term recurrence risk remains poorly understood. This study examined how treatments administered during acute catatonic episodes influence recurrence risk.

METHODS: We conducted a retrospective cohort study of 205 adults hospitalized with catatonia at a tertiary care center between 2001 and 2021. Catatonia diagnoses were confirmed by chart review using Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. The primary outcome was time to a new catatonic episode, with patients censored at last follow-up if no recurrence was observed. Treatment exposure was ascertained from the Latest Catatonia Episode (LaCE) for non-recurrent patients and from the Nearest Antecedent Catatonia Episode (NACE) for those with recurrence. Cox proportional hazards models estimated adjusted hazard ratios for benzodiazepines, antipsychotics, electroconvulsive therapy, and mood stabilizers, controlling for age and.

RESULTS: Overall, 31% of patients experienced recurrence over a median follow-up of 6.4 years. Benzodiazepines, used in 88% of patients, were consistently protective against recurrence (adjusted hazard ratio 0.50, 95% confidence interval 0.27-0.94, p = 0.03). Antipsychotics demonstrated a biphasic effect: lower hazard of recurrence within 60 days (adjusted hazard ratio 0.36, 95% confidence interval 0.13-1.00, p = 0.05) but associated with increased hazard thereafter (adjusted hazard ratio 2.14, 95% confidence interval 1.08-4.254, p = 0.08).

CONCLUSIONS: Benzodiazepines use was associated with sustained protection against catatonia recurrence. The time-dependent antipsychotic effect warrants careful consideration in maintenance treatment planning. While our retrospective design limits causal inference, these findings emphasize the need for prospective studies to optimize maintenance strategies and prevent recurrence.

PMID:41935752 | DOI:10.1016/j.jad.2026.121734

Clin Res Hepatol Gastroenterol. 2026 Apr 2:102822. doi: 10.1016/j.clinre.2026.102822. Online ahead of print.

ABSTRACT

BACKGROUND: In individuals with normal body weight, altered fat distribution contributes to metabolic dysfunction and hepatic steatosis. We hypothesized that the weight-adjusted waist index (WWI), an indicator of abdominal fat accumulation, is associated with lean MASLD.

METHODS: We analyzed lean adults from 2017-March 2020 pre-pandemic (N = 824). MASLD was defined using controlled attenuation parameter (CAP) from vibration-controlled transient elastography together with metabolic criteria. Four machine learning models (XGB, GBM, LASSO, SVM) were trained to prioritize candidate predictors from anthropometric and metabolic indices. The top consensus predictor was then evaluated in an independent cohort (NHANES August 2021-August 2023, N = 782) using survey-weighted logistic regression, subgroup analyses, and smooth curve fitting to assess potential non-linearity.

RESULTS: Across models, WWI ranked as the most important feature for discriminating lean MASLD and exceeded established indices such as the lipid accumulation product (LAP) and cardiometabolic index (CMI) in global importance metrics. The XGB model achieved the highest discrimination (AUC = 0.756). In the validation cohort, MASLD prevalence increased across WWI quartiles (7.5% to 44.0%). As a continuous variable, WWI was associated with MASLD after full adjustment (OR = 3.08, 95% CI: 1.53-6.21). However, quartile-based associations were attenuated and not statistically significant in the fully adjusted model. A modest trend across quartiles remained. Subgroup analyses demonstrated generally consistent associations across demographic and clinical strata. The dose-response analysis suggested a non-linear relationship, with MASLD risk increasing more steeply beyond a WWI of approximately 11 cm/√kg.

CONCLUSIONS: Among lean adults, WWI is independently associated with MASLD and may capture central-adiposity-related risk not reflected by BMI alone. WWI could serve as a simple complementary anthropometric marker for risk stratification in normal-weight populations, pending prospective validation.

PMID:41935737 | DOI:10.1016/j.clinre.2026.102822

Free Radic Biol Med. 2026 Apr 2:S0891-5849(26)00270-4. doi: 10.1016/j.freeradbiomed.2026.03.073. Online ahead of print.

ABSTRACT

BACKGROUND: Personalized antioxidant supplementation is promoted to optimize redox balance and inflammation profile.

OBJECTIVE: To quantify the short-term effects of vitamin C supplementation on redox and inflammatory outcome measures and explore the potential for supplement response heterogeneity in participants with vitamin C inadequacy through aggregated sets of multi-cycle n-of-1 trials.

METHODS: Eight healthy young males (age 25.56 ± 3.15 years, body mass 68.24 ± 9.70 kg) completed four supplementation (vitamin C 1g) and four placebo trials administered on repeated occasions in randomized sequences following a 1-month run-in period. Vitamin C, F₂-isoprostanes, interleukin-6, and tumor necrosis factor-α were assessed as primary outcomes. Separate within-participant linear mixed-effects modelling and meta-analytic models estimated replicate-averaged treatment effects and person-by-treatment response variation to vitamin C supplementation.

RESULTS: Supplementation resulted in a statistically significant increase in plasma vitamin C of 20.6 μmol/L (95% confidence interval [CI]: 16.8 to 24.5). This mean treatment effect was lower than our selected clinically important threshold of 23 μmol/L. Vitamin C supplementation reduced F₂-isoprostanes by 25.9 pg/mL (CI: 22.2 to 29.6 pg/mL), interleukin-6 by 1.2 pg/mL (CI: 0.7 to 1.7 pg/mL), and tumor necrosis factor-α by 0.5 pg/mL (CI: 0.2 to 0.9 pg/mL). The participant-by-treatment variance component from linear mixed-effects modelling was not statistically significant for all outcomes (P>0.05), agreeing with the small τ-statistics for all outcomes. Shrinkage-adjusted estimates also showed strong shrinkage toward the mean, indicating that the observed response variation mainly reflected random within-person cycle-to-cycle variability rather than true inter-individual variability.

CONCLUSIONS: Replicate-averaged treatment effects of vitamin C supplementation on our study outcomes were statistically significant, but heterogenous treatment effects were not detected between participants with baseline inadequacy. Cycle-to-cycle within-participant variation was larger than the observed inter-individual variability for each primary outcome response, suggesting that, if clinically relevant, “average treatment” may suffice for people prone to vitamin C inadequacy.

CLINICAL TRIAL REGISTRY: Open Science Framework (osf.io/e567r).

ETHICS: ERC-009/2024; #83059/2024.

PMID:41935704 | DOI:10.1016/j.freeradbiomed.2026.03.073

Am J Obstet Gynecol MFM. 2026 Apr 2:101959. doi: 10.1016/j.ajogmf.2026.101959. Online ahead of print.

ABSTRACT

BACKGROUND: The postpartum period is a critical window to address maternal health inequities. Black, Hispanic, Indigenous, and rural populations experience disproportionately high rates of postpartum morbidity and postpartum hospital use (PHU), defined as readmissions or emergency department visits after delivery. Delivery hospitalizations provide an opportunity for early identification of individuals at high risk of PHU, who may benefit from targeted interventions to prevent adverse outcomes. We previously developed a 30-day PHU prediction model using New York City (NYC) birth data (2016-2018), which achieved an area under the receiver operating curve (AUC) of 0.69. However, its performance in obstetric populations outside of a dense urban setting has not been examined.

STUDY DESIGN: We aimed to evaluate the accuracy of our PHU prediction model in South Carolina (SC) and Florida (FL), states with diverse populations, including substantial rural representation, and in a different US geographic region than the NYC development sample. We additionally examined model performance in subgroups defined by race/ethnicity, Medicaid insurance, and rural residence.

METHODS: We performed a retrospective cohort study of linked birth certificate and hospital discharge data from 2016-2019 births in SC (n=183,836) and FL (n=696,963). We ascertained 21 predictors consistent with the NYC model, excluding two variables (prenatal depression, Apgar) unavailable in the new states. PHU was defined as ≥1 inpatient or ED encounter within 30 days postpartum. Model performance was assessed using calibration (intercept, slope) and discrimination (AUC). We first applied the original NYC model coefficients to generate PHU predicted probabilities among SC and FL births. We then tested a series of stepwise model updating strategies: recalibrating intercepts, re-estimating predictor coefficients, and incorporating additional contextual indicators of hospital access – residential rurality and driving distance to the nearest delivery hospital – hypothesized to be relevant in settings with larger rural populations.

RESULTS: Cumulative 30-day PHU incidence was 7.4% in SC and 7.2% in FL; rates were higher among Black individuals, Medicaid-insured individuals, and rural residents. Applying the original NYC model coefficients achieved an AUC of 0.68 [95% CI 0.67-0.68] and 0.69 [95% CI 0.68-0.69] among SC and FL births, respectively, but generated overestimated and extreme risk predictions compared with observed risk. Updating model intercepts corrected calibration, and additionally re-estimating coefficients resulted in an AUC of 0.69 [95% CI 0.68-0.69) in SC and 0.70 [95% CI 0.70-0.71] in FL. Inclusion of hospital distance and rurality did not meaningfully change calibration or discrimination. Model discrimination was slightly lower when subset to Black, Medicaid-insured, and rural residents, but AUC increased within each group after re-estimating predictor coefficients.

CONCLUSION: A PHU prediction model developed in an urban NYC cohort demonstrated similarly moderate discrimination in SC and FL as in the original NYC sample but overestimated absolute risk in these new settings. Modest model updating, including recalibration of intercepts and re-estimation of coefficients, yielded well-calibrated models without requiring new predictors. Hospital access measures did not substantially improve prediction. These findings demonstrate that an existing prediction model for postpartum acute care use can be adapted for use in geographically and socio-demographically diverse populations. Geographic validation and model updating are important steps in deploying predictive tools to reduce persistent gaps in maternal health outcomes.

PMID:41935688 | DOI:10.1016/j.ajogmf.2026.101959

J Allergy Clin Immunol. 2026 Apr 2:S0091-6749(26)00222-8. doi: 10.1016/j.jaci.2026.03.017. Online ahead of print.

ABSTRACT

BACKGROUND: Asthma has heterogeneous risk factors, subtypes, and treatments. It is often unclear how to stratify this heterogeneity in scientific studies and clinical care. Genetics could explain root causes of this clinical heterogeneity, called endotypes, but prior studies have used models that are not designed for complex diseases like asthma.

OBJECTIVE: We aimed to find genetic effects that partly explain different asthma endotypes.

METHODS: We used recent powerful and robust statistical models of context-specific genetic effects in complex traits. We identified genetic subtypes by clustering clinical asthma features in a case/control cohort, GALA II. We replicated the genetic endotypes in UK Biobank with gene-context interaction tests.

RESULTS: Asthma-associated SNPs, polygenic scores, and genome-wide heritability revealed subtype-specific genetic endotypes correlated with type 2 inflammation (T2), allergy, and neuroticism. We validated the T2 associations with molecular data including nasal RNA-seq. In UK Biobank, we replicated these endotypes and found they interact with several polygenic scores and drug-relevant genes.

CONCLUSION: Our results show how context-specific genetic effects can unravel biomedically meaningful endotypes of complex disease and suggest novel precision treatment strategies.

PMID:41935671 | DOI:10.1016/j.jaci.2026.03.017