Nevin Manimala

BMC Med Educ. 2026 Jun 5. doi: 10.1186/s12909-026-09596-8. Online ahead of print.

ABSTRACT

BACKGROUND: The number of combined Doctor of Medicine and Master of Business Administration (MD/MBA) programs in the United States has increased fivefold over the past two decades, reflecting a shift toward integrating medical and business education. While most MD/MBA programs follow a 5-year structure with a dedicated year for business coursework, some offer 4-year programs that integrate both degrees concurrently. This study evaluated the structure and characteristics of MD/MBA programs in the United States in 2025, comparing 4-year and 5-year program structures and examining how 4-year programs integrate medical and business training.

METHODS: In January 2025, 93 U.S. MD/MBA programs were identified using AAMC and Association of MD/MBA Programs databases. Programs were categorized by duration (4-year vs. 5-year) and analyzed for admissions requirements, credit loads, degree integration, and institutional characteristics. Findings were compared to a 2022 analysis by Laditi et al. Additional analyses compared 4-year and 5-year programs in 2025, including how 4-year programs integrate business coursework into medical training. Statistical analyses used chi-square or Fisher’s exact tests (α = 0.05).

RESULTS: In total, 93 MD/MBA programs were identified in 2025, compared to 92 in 2022. From 2022 to 2025, significant changes included programs requiring full-time MBA credit loads (9% to 37%, p < 0.001) and a reduction in GMAT requirements (34% to 15%, p = 0.01). Of the 93 programs, 12 (13%) offered a 4-year track. Compared to 5-year programs, 4-year programs offered significantly more MBA specializations (83% vs. 15%, p < 0.001) and required fewer than 50 MBA credits (100% vs. 66%, p = 0.03). Among 4-year programs, 42% delivered MBA coursework online, 25% in-person, and 33% in a hybrid format.

CONCLUSIONS: The overall number of MD/MBA programs remained stable between 2022 and 2025, but program structures and admission requirements continued to evolve. This study highlights the differences between 4-year and 5-year MD/MBA programs and describes how 4-year programs integrate business training within medical education. These findings may inform prospective students, program administrators, and medical education policymakers seeking to design, improve, or select MD/MBA programs that best prepare future physician-leaders.

PMID:42249401 | DOI:10.1186/s12909-026-09596-8

Orphanet J Rare Dis. 2026 Jun 5. doi: 10.1186/s13023-026-04410-6. Online ahead of print.

ABSTRACT

BACKGROUND: Xeroderma Pigmentosum (XP), is a rare genetic condition characterised by extreme sensitivity to ultra violet (UV) radiation, conferring a 2,000- to 10,000-fold increased risk of developing melanoma and non-melanoma skin cancers. Families affected by XP face intense emotional strain, ongoing medical surveillance and intervention, and stringent lifelong adaptations to minimise UV exposure. Despite these challenges, little is known about the psychosocial burden experienced by children with XP and their immediate family members. This study explored the lived experiences and support needs, both medical and psychosocial, of families caring for a child with XP.

METHOD: We conducted qualitative semi-structured interviews, in person or via Zoom, with parents and children affected by XP, examining diagnostic experiences, psychosocial impacts, care preferences, and informational needs. The interview guide was developed by a multidisciplinary expert panel. Eligible participants included parents of children with XP, and patients or siblings aged 5-18 years without intellectual disability. Participants were recruited via the Australian Paediatric XP Support Group, representing the full known XP cohort in Australia. Of the seven identified families, five contributed at least one parent participant. Among eight identified children, four were ineligible, and one was not enrolled. Interviews were audio-recorded, transcribed verbatim, and analysed using inductive, line-by-line coding in NVivo Pro. Descriptive statistics summarised participant demographics.

RESULTS: Eight parents (63% female, mean age 45 years) and three children (67% female, mean age 10 years) participated. Four themes emerged: (1) a prolonged and distressing diagnostic journey, often marked by misdiagnosis and uncertainty; (2) strong preferences for integrated, multidisciplinary care to reduce fragmentation; (3) significant psychosocial impacts, including isolation, anxiety-driven vigilance, and challenges adapting to absolute UV-protective routines; and (4) substantial unmet information needs at diagnosis, leaving families feeling overwhelmed and underprepared.

CONCLUSION: Families affected by XP experience significant and enduring psychosocial burden. Findings highlight the urgent need for coordinated, interdisciplinary support that extends beyond medical care. This study contributes to the growing call within the rare disease community for integrated care models that centre patient and family wellbeing.

PMID:42249400 | DOI:10.1186/s13023-026-04410-6

Mol Cancer. 2026 Jun 5;25(1):151. doi: 10.1186/s12943-026-02671-0.

NO ABSTRACT

PMID:42249396 | DOI:10.1186/s12943-026-02671-0

JMIRx Med. 2026 Jun 5;7:e81547. doi: 10.2196/81547.

ABSTRACT

BACKGROUND: Chaotic dynamics has been the subject of both theoretical and empirical research in epidemiology, with the most recent research strongly focusing on SARS-CoV-2. However, few empirical studies have been undertaken with respect to influenza, even though evidence of chaos has also been found in influenza surveillance data. Furthermore, empirical studies on chaos are focused on reconstructing hidden attractors in epidemiological time series to filter out noise; however, dynamical noise affecting chaotic dynamics can have relevant epidemiological features that are, in this way, left unresearched and that can be used for epidemiological surveillance and risk analysis by capturing the main underlying nonlinear processes associated with epidemiological dynamics.

OBJECTIVE: This study aimed to reinforce empirical research on chaotic dynamics in influenza surveillance and the study of the dynamical noise affecting that chaotic dynamics, addressing the consequences for epidemiological risk analysis and surveillance.

METHODS: Working with the weekly share of positive influenza tests for the Northern Hemisphere from January 2009 to March 2025 compiled by Our World in Data using FluNet data from the World Health Organization, we applied a recent method based on topological data analysis for reconstructing underlying attractors from time series and decomposing the dynamics down to independent and identically distributed noise. We adapted the method to the epidemiological context so that it can be used for predictive decomposition with direct application to epidemiological risk analysis and surveillance.

RESULTS: We found evidence of a low-dimensional chaotic attractor in the researched surveillance data, with a fractal dimension between 1 and 2, and a positive statistically significant largest Lyapunov exponent. The chaotic dynamics had power law scaling associated with long-wave influenza outbreaks, and it is affected by a stochastic component that is nonstationary in variance, leading to turbulent bursts in the outbreak dynamics. Testing different machine learning algorithms using the attractor as input for prediction and a 10-week rolling window, we found the following largest R2 scores for the prediction of the target series: 92.11% (1 week ahead), 85.95% (2 weeks ahead), 81.75% (3 weeks ahead), 77.59% (4 weeks ahead), and 73.35% (5 weeks ahead).

CONCLUSIONS: The main results reinforce previous theoretical and empirical studies on chaos in epidemiology. Our findings showed that there is a 2-dimensional chaotic attractor that can support up to a 1-month prediction of the target surveillance series with high prediction scores and that the attractor plus noise can be modeled in a way that supports uncertainty quantification and epidemiological risk analysis.

PMID:42247685 | DOI:10.2196/81547

JMIR Pediatr Parent. 2026 Jun 5;9:e88772. doi: 10.2196/88772.

ABSTRACT

BACKGROUND: Hemolytic disease of the fetus and newborn (HDFN) is a life-threatening condition resulting from maternal-fetal erythrocyte antigen incompatibility. Although anti-Rhesus D (RhD) prophylaxis has reduced RhD-associated cases, HDFN persists due to non-RhD antibodies and gaps in prevention. Population-based data on maternal and neonatal outcomes and recurrence patterns are limited.

OBJECTIVE: This study aimed to characterize maternal and neonatal outcomes, health care use patterns, and recurrence rates of HDFN across pregnancies.

METHODS: We conducted a retrospective cohort study of 464,711 pregnancies within the Kaiser Permanente Southern California system from January 1, 2008, to June 30, 2022. HDFN diagnoses were confirmed using validated natural language processing-assisted manual chart review and followed through 2023. Maternal characteristics, neonatal outcomes, and health care use were compared by HDFN status, and recurrence patterns were evaluated among individuals with ≥2 pregnancies. Chi-square tests and Wilcoxon rank-sum tests were used to compare characteristics between HDFN and non-HDFN pregnancies. Statistical significance was defined as P<.05.

RESULTS: Among all pregnancies, 139 of 464,711 (0.03%) were diagnosed with HDFN. Women with HDFN were more likely than those without HDFN to be older (aged ≥35 years; n=42, 30.2% vs n=97,146, 20.9%) and multiparous (n=121, 87.1% vs n=264,766, 57%). Infants affected by HDFN had higher rates of preterm birth (n=40, 28.4% vs n=42,240, 9.5%), low birth weight (<2500 g; n=22, 15.6% vs n=31,740, 7.1%), and neonatal jaundice (n=92, 65.2% vs n=162,465, 36.4%) than non-HDFN infants. Delivery hospitalizations (median 5.0, IQR 2.0-7.5 days vs median 2.0, IQR 1.0-2.0 days) and neonatal intensive care unit stays (median 4.0, IQR 0.0-7.0 days vs median 0.0, IQR 0.0-0.0 days) were longer, and maternal nondelivery hospitalizations were more frequent (n=27, 19.4% vs n=23,228, 5%) among pregnancies complicated by HDFN. Among women with a prior HDFN-affected pregnancy, 83.3% (n=25) experienced recurrence in a subsequent pregnancy. Of these recurrent cases, 32% (n=8) were severe, and 75% (n=6) involved fetal anemia requiring at least 1 intrauterine transfusion.

CONCLUSIONS: HDFN was rare but was associated with substantial maternal and neonatal morbidity, including higher rates of preterm birth, increased neonatal intensive care unit admissions, and greater health care use. Recurrence was frequent and clinically significant, underscoring the importance of early surveillance and proactive management strategies.

PMID:42247681 | DOI:10.2196/88772

Biodemography Soc Biol. 2026 Jun 5:1-12. doi: 10.1080/19485565.2026.2684735. Online ahead of print.

ABSTRACT

Women have a higher risk of Long COVID, defined as symptoms persisting for three or more months after SARS-CoV-2 infection. This study examines whether the elevated risk of Long COVID among women varies across income subgroups in a nationally representative sample of the U.S. population. Using data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS), we estimated adjusted odds ratios for Long COVID associated with female sex, stratified by four age categories and 11 income groups. We conducted random-effects meta-analyses of income subgroup estimates within each age category and assessed heterogeneity using Cochran’s Q, I² statistics, prediction intervals, and Galbraith plots. Among younger age groups (18-34, 35-49, and 50-64 years), Cochran’s Q ranged from 7.70 to 10.98 (p > 0.10), and I² was 0.00%, indicating no significant heterogeneity across income groups. In the ≥65 age group, Cochran’s Q was 18.35 (p = 0.0494), and I² was 21.96%, suggesting modest heterogeneity. The 95% prediction interval for the ≥65 group (1.121-1.978) was wider than those for younger groups: 1.437-1.975 (18-34 years), 1.551-2.019 (35-49 years), and 1.355-1.766 (50-64 years).

PMID:42247671 | DOI:10.1080/19485565.2026.2684735

Sci Prog. 2026 Apr-Jun;109(2):368504261457365. doi: 10.1177/00368504261457365. Epub 2026 Jun 5.

ABSTRACT

ObjectiveDelirium is an established predictor of adverse outcomes in general ICU populations, but its specific prognostic impact in critically ill patients with acute pancreatitis (AP) remains unclear. This study aimed to evaluate the independent association between ICU-acquired delirium and clinical outcomes in this high-risk population.MethodsThis retrospective cohort study utilized data from the MIMIC-IV database (2008-2022). Critically ill adults with AP were included and stratified by the presence of ICU-acquired delirium, assessed using the CAM-ICU. The primary outcome was 90-day all-cause mortality. Secondary outcomes included 90-day unplanned readmission, emergency department revisits, and a composite adverse outcome. Propensity score matching (PSM) was performed to balance baseline characteristics, generating 178 matched pairs. Multivariable Cox regression with four sequential models and sensitivity analyses were conducted to assess robustness.ResultsAmong 594 included patients, 44.6% (265/594) developed delirium. After PSM, baseline characteristics were well-balanced. Delirium was independently associated with increased 90-day all-cause mortality (aHR=1.91, 95% CI: 1.04-3.50; P=0.038) and a higher risk of the composite adverse outcome (aHR=1.84, 95% CI: 1.24-2.73; P=0.002). The association with unplanned readmission remained significant after full adjustment (aHR=1.87, 95% CI: 1.20-2.92; P=0.006), while the association with ED revisits did not reach statistical significance. Sensitivity analyses confirmed the robustness of the primary findings.ConclusionsIn critically ill patients with AP, ICU-acquired delirium was an independent predictor of increased 90-day mortality, unplanned readmission and composite adverse outcomes. These findings highlight delirium as a significant prognostic factor, underscoring the importance of routine screening and targeted management in this vulnerable population.

PMID:42247663 | DOI:10.1177/00368504261457365

JMIR Form Res. 2026 Jun 5;10:e68004. doi: 10.2196/68004.

ABSTRACT

BACKGROUND: Surgeons work in a progressive field where communicating research is vital to advancing health care and enabling meaningful interactions among clinicians. It also contributes to societal impact, increases access to information, and reduces misinformation. Additionally, there can be barriers to accessing papers. Social media enhances research impact through sharing scholarly work and improving its translation into clinical practice, but little is known about how to design specific posts to maximize research impact through language.

OBJECTIVE: The purpose of this study was to determine the linguistic cues that optimize research impact among surgeons through Twitter (subsequently rebranded X). Additionally, this research combines the linguistic features of the posts and article access to determine their unique contributions.

METHODS: An exploratory linguistic analysis of 84 posts extracted from Twitter was conducted, which shared scholarly activity by 17 of the most-followed surgeons. The linguistic cues were measured on a continuous scale, computed from the percentage of each linguistic cue used in the text, and reported as mean (SD). Regression analysis and analysis of covariance were conducted to determine which cues influenced research impact and to estimate the potential association with study accessibility (open vs restricted access).

RESULTS: Analyzed tweets were highly analytic (mean 94.77, SD 9.00), moderate in clout (mean 42.69, SD 19.84), low in tone (mean 20.06, SD 33.91), suggesting negative tone use, and low in authenticity (mean 19.52, SD 24.50). Results suggest that a high use of formal language negatively impacts readership and citations. Analytical language was indirectly associated with readership (β=-0.296, 95% CI -423.57 to -59.95; P=.01) and citations (β=-0.524, 95% CI -0.442 to -0.187; P<.001). Linguistic clout had a positive association with readership (β=0.260, 95% CI 8.58-186.91; P=.03), and tone in tweets had a negative association with readership (β=-0.317, 95% CI -138.52 to -5.39; P=.04). Negative language tone was found to increase the impact of research. With respect to linguistic cues and study accessibility, the results also suggest that the number of citations was impacted by readership (F1,66=4.11, 95% CI 2.459E-06 to 0.003; P=.047) and analytic linguistic cues (F1,66=18.77, 95% CI -0.402 to -0.149; P<.001) used in the post, but the association of open (mean 3.04, SE 1.062) versus restricted access (mean 1.83, SE 0.716) was not statistically significant (F1,66=0.877, 95% CI 0.405-3.266; P=.352).

CONCLUSIONS: This research is the first to explore article accessibility and linguistic cues used in creating posts that share research on social media to determine their influence on research impact, making this study both innovative and unique relative to existing studies in the surgery field. Through language, the medical field can expand its impact and encourage dialogue between scientists and the public, thereby increasing scientific and societal contributions while reducing the negative effects of limited article access.

PMID:42247625 | DOI:10.2196/68004

Adv Clin Exp Med. 2026 Jun 5. doi: 10.17219/acem/220688. Online ahead of print.

ABSTRACT

BACKGROUND: Intracardiac leads commonly produce metal artifacts on computed tomography (CT) images. These artifacts may be reduced using dedicated metal artifact reduction algorithms, such as metal artifact reduction (MAR).

OBJECTIVES: The aim of this study was to develop a method for measuring lead-related artifacts in CT and to assess the suitability of various reconstruction presets for lead visualization.

MATERIAL AND METHODS: Fifty-four patients (mean age: 73.9 ±11.32 years) with implanted cardiac implantable electronic devices (CIEDs) who underwent cardiac CT, chest CT, or pulmonary angio-CT were included in the study. Images were reconstructed using at least 2 kernels (soft tissue and lung) with slice thicknesses of 0.6 mm or 1.0 mm. A tissue density volume >1,000 HU, corresponding to the presumed volume of hyperdense artifacts, was isolated within a manually drawn spherical region of interest (ROI), and the values were recorded. The obtained values for each iterative metal artifact reduction (iMAR) reconstruction preset were compared with native images (without iMAR) to calculate the percentage reduction in hyperdense artifacts.

RESULTS: All tested algorithm variants reduced artifact volume; however, only 2 presets achieved statistically significant reductions: “dental fillings” (p = 0.001) and “neuro coils” (p = 0.000). Pacemaker-dedicated presets reduced metal artifacts in all cases, although the reductions were not statistically significant (p = 0.667), which may limit their reliability in routine clinical practice.

CONCLUSIONS: We proposed a method for evaluating intracardiac leads that enables precise three-dimensional (3D) assessment of hyperdense artifacts. The metal artifact reduction technique demonstrated promising results, particularly for the “dental fillings” and “neuro coils” presets.

PMID:42247616 | DOI:10.17219/acem/220688

ESC Heart Fail. 2026 Jun 5:xvag148. doi: 10.1093/eschf/xvag148. Online ahead of print.

ABSTRACT

BACKGROUND: The renal effects of sacubitril/valsartan (Sac/Val) in heart failure (HF) remain incompletely defined, partly because kidney outcomes in pivotal HF trials have been variably prespecified and heterogeneously defined. We performed an updated systematic review and meta-analysis to assess whether the apparent renal signal of Sac/Val varies according to endpoint definition.

METHODS: This updated systematic review was conducted in accordance with PRISMA 2020. Building on the pre-existing evidence base from prior meta-analyses, we performed an updated search of PubMed and Web of Science. Randomized controlled trials (RCTs) and observational comparative studies in adults with HF comparing Sac/Val with angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, or standard care were included if renal outcome data were extractable. Renal outcomes were analyzed using a hierarchical cross-endpoint approach, including sustained ≥50% estimated glomerular filtration rate (eGFR) decline, end-stage kidney disease (ESKD), composite kidney outcomes, and annualized eGFR decline. Random-effects meta-analysis was performed, with Hartung-Knapp and RCT-only sensitivity analyses.

RESULTS: Overall, 13 study-level reports comprising 34,969 patients were included. Sac/Val was associated with a lower risk of sustained 50% eGFR decline (RR 0.68, 95% CI 0.57-0.82) and composite kidney outcome (RR 0.70, 95% CI 0.58-0.84), with the composite endpoint showing the most robust and consistent signal, including in RCT-only analyses. By contrast, the association for ESKD alone was directionally favorable but not statistically significant (RR 0.80, 95% CI 0.64-1.00). Sac/Val was also associated with a slower annualized eGFR decline (MD 0.52 mL/min/1.73 m2/year, 95% CI 0.35-0.69).

CONCLUSIONS: The renal signal associated with Sac/Val in HF appeared at least partly dependent on endpoint definition. Composite kidney outcomes may best capture its potential nephroprotective effect, with sustained 50% eGFR decline showing a consistent pattern, whereas isolated ESKD remains inconclusive. These findings support a potential nephroprotective role of ARNIs but future research are needed.

PMID:42247581 | DOI:10.1093/eschf/xvag148