Category: Nevin Manimala

J Prosthodont. 2026 Apr 14. doi: 10.1111/jopr.70141. Online ahead of print.

ABSTRACT

PURPOSE: To compare the long-term survival of nonsurgical endodontic re-treatment versus single-tooth implants and to identify independent demographic, systemic, and lifestyle predictors of failure using a statistical model that accounts for patient-level clustering.

MATERIALS AND METHODS: A retrospective cohort study was conducted using electronic health records from a university setting between 2010 and 2016. Two cohorts were defined by Current Dental Terminology (CDT) codes: endodontic re-treatment (n = 1001) and single-tooth implants (n = 1822). The primary outcome was treatment failure (extraction or removal). To address the nonindependence of multiple procedures within the same patient, a shared frailty Cox proportional hazards model was employed to calculate hazard ratios (HRs) adjusted for clustering.

RESULTS: The analysis included 2823 procedures. The shared frailty model revealed that single-tooth implants had a significantly lower risk of failure compared to endodontic re-treatment (HR = 0.21; 95% confidence interval [CI]: 0.14-0.33; p < 0.001). Stratified frailty models revealed that tobacco use (HR = 2.76; p < 0.001) and diabetes (HR = 2.37; p = 0.007) were strong predictors of failure, specifically for endodontic re-treatments, alongside thyroid problems and osteoporosis. In the implant cohort, high blood pressure emerged as a significant predictor (HR = 3.96; p = 0.048). Unlike in standard survival models, patient age was not a significant predictor of failure (p = 0.335) after adjusting for patient frailty.

CONCLUSIONS: When rigorously accounting for intra-patient correlation, single-tooth implants demonstrated a superior survival advantage over endodontic re-treatment in this population. However, the long-term success of both modalities is significantly associated with the patient’s systemic health, with specific risk factors varying by modality.

PMID:41979007 | DOI:10.1111/jopr.70141

Alzheimers Dement. 2026 Apr;22(4):e71365. doi: 10.1002/alz.71365.

ABSTRACT

INTRODUCTION: Digital speech biomarkers (DSBs) support the detection and monitoring of Alzheimer’s disease (AD) in Latinos. However, they have not been benchmarked against standard cognitive and neuroimaging measures, missing a critical validation milestone.

METHODS: Thirty-three AD patients and 33 healthy controls completed verbal fluency tasks, episodic memory and executive tests, and magnetic resonance imaging (MRI) (volume) and functional MRI (fMRI) (connectivity) scans. Between-group machine learning classification was compared among fluency-derived DSBs, episodic and executive test scores, MRI, and fMRI measures.

RESULTS: The fluency classifier’s performance (area under the curve [AUC] = 0.84) was comparable (p > 0.14) to the episodic (AUC = 0.90), executive (AUC = 0.79), and structural (AUC = 0.90) classifiers and superior to the functional classifier (AUC = 0.65, p = 0.002). Top discriminating features were word length and frequency, both associated with right (pre)frontal volume upon adjusting for sociodemographic factors.

DISCUSSION: DSBs appear non-inferior to standard cognitive and imaging measures, supporting scalable AD assessments in Latinos.

HIGHLIGHTS: We examined digital speech biomarkers (DSBs) for detecting AD in Latinos. DSBs were benchmarked against cognitive and neuroimaging features. DSB-based classifiers matched or outperformed cognitive and brain classifiers. Top DSBs included word length, phonological neighborhood, and frequency. Word length and frequency correlated with right (pre)frontal brain volume.

PMID:41979006 | DOI:10.1002/alz.71365

J Prosthodont. 2026 Apr 14. doi: 10.1111/jopr.70142. Online ahead of print.

ABSTRACT

PURPOSE: This 5-year cross-sectional study aimed to determine whether immediate and delayed impression workflows result in differences in crestal bone levels (CBLs), peri-implant indices, mucosal margin position, and pink esthetic score (PES).

MATERIALS AND METHODS: Patients who had received a single posterior implant crown in the premolar and molar regions for ≥5 years were identified. Outcome measurements for peri-implant indices, including modified plaque index (mPI), modified sulcus bleeding index (mSBI), presence or absence of bleeding on probing (BoP), and probing pocket depths (PPDs), were measured at six sites per implant. The peri-implant mucosal margin position was measured relative to an adjacent or contralateral tooth. CBLs were assessed radiographically using standardized vertical bitewing radiographs with the paralleling technique. PES was calculated with a total possible score of 14. The Shapiro-Wilk test was employed to assess the normality of the data distribution. For variables following a normal distribution, a two-sample t-test was used to compare the mean values between the two groups. Conversely, for non-normally distributed data, the Mann-Whitney U test was utilized to determine whether significant differences existed between the group distributions. The significance level was set at 0.05.

RESULTS: Mean mesial CBL for the immediately- and delayed-impressed groups were -0.30 ± 1.01 mm and 0.07 ± 1.18 mm, respectively. Mean distal CBL for the same groups were -0.14 ± 0.56 mm and -0.30 ± 0.79 mm, respectively. Mean mesio-buccal, mid-buccal, and disto-buccal PPDs were 3.18 ± 1.08 mm, 1.36 ± 0.76 mm, and 2.73 ± 1.10 mm for the immediate impression group and 3.14 ± 1.35 mm, 1.93 ± 1.14 mm, and 3.07 ± 1.07 mm for the delayed impression group. Mean mesio-lingual, mid-lingual, and disto-lingual PPDs were 2.55 ± 0.69 mm, 1.45 ± 0.69 mm, and 3.09 ± 0.94 mm for the immediate impression group and 3.29 ± 0.83 mm, 2 ± 1.24 mm, and 3.50 ± 1.45 mm for the delayed impression group. Mean PES was 12.64 ± 1.03 and 12 ± 2 for the immediately- and delayed-impressed groups. There were no statistically significant differences between immediate and delayed impression groups for PES, peri-implant indices, mucosal marginal position, or CBLs.

CONCLUSION: At 5 years, there was no significant difference in PES, CBL, peri-implant indices, or mucosal margin position between implants restored with immediate impressions and those restored with delayed impressions made after osseointegration and soft tissue healing.

PMID:41978996 | DOI:10.1111/jopr.70142

Geospat Health. 2026 Feb 2;21(1). doi: 10.4081/gh.2026.1453. Epub 2026 Apr 14.

ABSTRACT

This study investigates spatial disparities in cancer and lung-cancer mortality across Europe through an integrative geospatial epidemiological framework. Using age-standardised Eurostat mortality data for 2022 at the NUTS-2 level, we combine Getis-Ord Gi* and Anselin Local Moran’s I to detect statistically significant hot/cold spots, while multivariate regressions incorporate environmental and topographic predictors. Results reveal pronounced east-west and urban-rural gradients: persistent high-mortality clusters span Central and Eastern Europe, where historical industrialisation, elevated smoking prevalence, and structural healthcare gaps converge. By contrast, Southern European regions – Portugal, western Spain, and southern Greece – are associated with lower observed mortality levels, plausibly reflecting favourable behavioural profiles, environmental conditions, and healthcare accessibility. Spatial outliers identify territories where localised factors, such as air-pollution peaks or differential diagnostic capacity, modify broader regional patterns. Overall, the findings highlight geography as a structuring context for exposure, vulnerability, and access to care, rather than as a direct causal driver of cancer risk, and demonstrate the value of spatial epidemiology for territorial health governance, environmental monitoring, and urban planning. Policy relevance is twofold. First, the evidence supports region-specific interventions aligned with the Sustainable Development Goals (SDG) – especially SDG 3 (health), SDG 10 (reduced inequalities), and SDG 11 (sustainable cities). Second, the spatial outputs provide a robust empirical basis for informing the health-equity ambitions of Europe’s Beating Cancer Plan and the environmental-justice agenda of the European Green Deal. By bridging granular geospatial evidence with EU-wide priorities, the study underscores the need for place-based, equity-oriented frameworks in cancer prevention and control across heterogeneous European landscapes.

PMID:41978989 | DOI:10.4081/gh.2026.1453

Proc Inst Mech Eng H. 2026 Apr 14:9544119261441368. doi: 10.1177/09544119261441368. Online ahead of print.

ABSTRACT

Electrospun nanofiber scaffolds are important in biomedicine, especially skin tissue engineering, in which scaffold porosity and fiber orientation significantly affect cell penetration, nutrition diffusion, and biomechanical integration. Despite progress on image-based, non-destructive methods for SEM analysis, integrating quantitative metrics from multiple morphological descriptors into a unified and automated workflow remains challenging. In this paper, we present a software tool developed using MATLAB App Designer, which facilitates SEM image analysis for non-destructive characterization of electrospun nanofiber scaffolds. This application provides capability to determine porosity, pore size, fiber diameter and fractal dimension as well as estimation of BET surface area and Barrett-Joyner-Halenda (BJH) volume based on geometric models. Eight independently electrospun nanofiber scaffolds, fabricated at identical electrospinning parameters, were analyzed using a combination of automated thresholding, morphological processing, and skeletonization. For each sample, five SEM images were analyzed (total = 40 images). Estimated BET and BJH data were extrapolated from image-based parameters, considering cylindrical-like scaffold geometry to assess internal consistency. High correlations were observed between porosity and surface area, and pore size with BJH volume highlight that the model is appropriate for relative scaffold screening. Statistical comparison detected various methods (Otsu and morphological thresholding) were significantly different from each other (p < 0.05), indicating importance of method choices on results. A user-friendly GUI allows users to access techniques and view metric outputs easily. Although strong R values were observed, they reflect internal coherence, not external validation. The tool offers a replicable platform for early-stage scaffold assessment in tissue engineering and nanomaterial research.

PMID:41978985 | DOI:10.1177/09544119261441368

Monaldi Arch Chest Dis. 2026 Apr 13. doi: 10.4081/monaldi.2026.3705. Online ahead of print.

ABSTRACT

Hydropneumothorax is an uncommon but serious complication of pulmonary tuberculosis (PTB), often resulting from the rupture of a tuberculous cavity into the pleural space with bronchopleural fistula formation. Early diagnosis and optimal management are crucial to improving outcomes. A descriptive study was conducted over 18 months in 50 microbiologically confirmed PTB patients presenting with pneumothorax or hydropneumothorax at a tertiary care hospital in Punjab, India. Demographic, clinical, radiological, and microbiological data were recorded. Lung expansion was quantified using Light’s Index at serial intervals up to 8 weeks. Statistical analysis was performed using Chi-square/Fisher exact tests; p<0.05 was considered significant. The mean age was 34.48±11.69 years, and 82% were male. All patients presented with breathlessness, 96% with chest pain, 68% with fever, and 62% with cough. New TB cases comprised 82%, recurrent 8%, and loss-to-follow-up 10%. The mean lung expansion time was 2.92±2.16 weeks. Significant associations were found between drainage status and lung expansion (p=0.01) and between type of TB and lung expansion (p=0.04). Complete radiological expansion was achieved in 76% of patients within 8 weeks. Surgical referral to the Cardiothoracic and Vascular Surgery Department was required in 24%. Hydropneumothorax in PTB predominantly affects young adult males and often requires prolonged drainage. Early intercostal tube drainage significantly improves lung expansion outcomes, particularly in new TB cases.

PMID:41978980 | DOI:10.4081/monaldi.2026.3705

J Prosthodont. 2026 Apr 14. doi: 10.1111/jopr.70136. Online ahead of print.

ABSTRACT

PURPOSE: The aim was to evaluate the ability of four large language models (LLMs) (OpenAI’s ChatGPT-3.5, Microsoft 365 Copilot, DeepSeek-R1, and Google Gemini 2.5 Pro) to develop treatment options when presented with clinical cases published in the maxillofacial prosthodontics literature.

MATERIALS AND METHODS: Six maxillofacial case reports were fed to the LLMs following a prompt that requested prosthodontic treatment options from the perspective of a prosthodontist. Expert evaluators scored the relevance, clarity, depth, focus, and coherence of the responses. Statistical analyses, including descriptive statistics, two-way analysis of variance (ANOVA), post hoc Tukey tests, Pearson correlation analyses, and intraclass correlation coefficients (ICCs), were performed (α < 0.05).

RESULTS: There were significant differences among the total mean relevance (p = 0.003), clarity (p = 0.006), depth (p < 0.001), focus (p < 0.001), and coherence (p < 0.001) scores of chatbots. Copilot consistently scored the lowest, and Gemini or DeepSeek scored the highest for all five factors. Depth (p = 0.006), focus (p = 0.024), and coherence (p = 0.013) scores of senior prosthodontists were slightly higher than those of junior prosthodontists. Pearson correlation analysis revealed positive correlations between the total mean scores for all five factors (p < 0.001).

CONCLUSIONS: The study demonstrates the ability of LLMs to develop maxillofacial prosthetic treatment plans tailored to specific clinical scenarios. There were significant differences between the abilities of the LLMs evaluated in this study. Copilot scored the lowest for all factors evaluated, and Gemini and/or DeepSeek scored the highest.

PMID:41978968 | DOI:10.1111/jopr.70136

J Korean Med Sci. 2026 Apr 13;41(14):e113. doi: 10.3346/jkms.2026.41.e113.

ABSTRACT

BACKGROUND: Updated data on stroke care trends are crucial for advancing stroke treatment. This study aimed to assess trends in inpatient care for first-ever stroke patients in South Korea over a 12-year period, focusing on demographic shifts and acute treatments including rehabilitation.

METHODS: This multicenter cohort study analyzed first-ever stroke patients admitted to three representative hospitals in South Korea during 2008 (n = 911), 2014 (n = 1,489), and 2020 (n = 1,434). The 2008 data were collected retrospectively, while 2014 and 2020 data were obtained from a prospective cohort study. Data included demographics, risk factors, stroke characteristics, hospital course, and rehabilitation treatments.

RESULTS: From 2008 to 2020, the mean age of stroke patients increased from 62.0 to 66.2 years. The proportion of ischemic stroke cases increased markedly from 47.3% to 74.5% while risk factors such as diabetes mellitus and hyperlipidemia showed increasing prevalence. Mechanical thrombectomy increased from 0% to 3.3%. Mean hospital stay decreased from 25.2 to 14.9 days, while in-hospital mortality declined from 5.9% to 3.7%. Rehabilitation consultations increased from 27.8% to 80.6%, occurring earlier during hospitalization. Rehabilitation therapy during hospitalization increased from 23.7% to 55.8%, and transfers to rehabilitation medicine rose from 12.8% to 19.1%. Home discharge increased from 34.8% to 60.0%.

CONCLUSION: Management of first-ever stroke patients in Korea improved substantially over 12 years, reflecting positive impacts of national quality initiatives and advancing stroke care.

PMID:41978925 | DOI:10.3346/jkms.2026.41.e113

J Korean Med Sci. 2026 Apr 13;41(14):e34. doi: 10.3346/jkms.2026.41.e34.

ABSTRACT

BACKGROUND: Hybrid closed-loop (HCL) systems adjust basal insulin levels using real-time glucose levels obtained from continuous glucose monitors (CGM). This study evaluated the MiniMed 770G system in Korean youths with childhood-onset type 1 diabetes (T1D).

METHODS: Of the 457 patients followed-up for childhood-onset T1D for > 1 year at Seoul National University Children’s Hospital and Seoul National University Bundang Hospital between February 2022 and May 2023, 20 patients (10 boys, 10 girls) who used a MiniMed 770G system for ≥ 3 months with a CGM active time of > 70% were enrolled. Glycemic outcomes, including glycated hemoglobin A1c (HbA1c), and CGM-derived metrics (time in range [TIR], time below range, time above range > 180 mg/dL and > 250 mg/dL [TAR 180 and TAR 250], and coefficient of variation [CV]) were analyzed. Generalized estimating equation (GEE) analysis compared glycemic outcomes between auto-mode users (> 85% and ≤ 85%) during the 1-year follow-up.

RESULTS: The median age at HCL initiation was 14.0 years (interquartile range [IQR], 11.2, 17.9), with a median diabetes duration of 6.5 years (IQR, 5.7, 8.9). The numbers of auto-mode (> 85%) users at 3, 6, 9, and 12 months were 10, 9, 9, and 7, respectively. Compared to auto-mode (≤ 85%) users, auto-mode (> 85%) users demonstrated 0.75 lower HbA1c (P = 0.037), 7.0 higher TIR (P = 0.015), 6.7 lower TAR 180 (P = 0.031), and 3.2 lower CV (P = 0.001) during the year using GEE analysis. In an analysis of auto-mode (> 85%) users, the median TIR, TAR, and CV significantly improved from 59% at baseline to 74.5% at 3 months (P = 0.008), and from 65% at baseline to 73% at 6 months (P = 0.012). Neither severe hypoglycemia nor diabetic ketoacidosis was observed throughout the year. The most common reasons for auto-mode exit were hyperglycemia and a lack of calibration.

CONCLUSION: Use of HCL system with auto-mode (> 85%) enhanced glycemic control in youth with childhood-onset T1D during the study period.

PMID:41978923 | DOI:10.3346/jkms.2026.41.e34

J Korean Med Sci. 2026 Apr 13;41(14):e10. doi: 10.3346/jkms.2026.41.e10.

ABSTRACT

BACKGROUND: This study aims to report the nationwide risk stratification of prostate cancer (PCa) over the past decade-an analysis that has not been previously conducted, as such data are not available through the medical insurance-based big data registry of South Korea.

METHODS: Nationwide data on the clinicopathologic variables of PCa at the time of diagnosis through biopsy, prostate-specific antigen (PSA) levels, clinical stage, Gleason grade, and residential area of the patient were obtained from 51 general hospitals (with ≥ 200 beds) across South Korea in 2010, 2012, 2014, 2016, 2018, and 2020. The risk criteria were based on universal guidelines defined in the 2010s, with high risk defined as PSA levels > 20 ng/mL, clinical stage ≥ cT3a, and Gleason group (GG) ≥ 4; low risk was defined as PSA levels < 10 ng/mL, clinical stage ≤ cT2a, and GG < 1.

RESULTS: Data from 27,075 cases, representing 37.9% of the 71,403 patients registered in the National Cancer Statistics during the study period, were obtained from 51 hospitals. High-risk PCa (50.6%) was the most prevalent disease during the study period, while the proportion of low-risk diseases, including potential low-risk cases, decreased from 11.4% in 2010 to 7.6% in 2020. High-risk PCa was most prevalent in 9 of the 17 administrative regions, with 55.4% of high-risk cancer cases originating in rural areas compared to 47.7% from urban areas (P < 0.001).

CONCLUSION: Approximately 50% of the patients with PCa detected in South Korea in the 2010s had high-risk disease, which was a consistent nationwide. The higher prevalence of low-risk disease among residents of the capital metropolitan area, compared to the higher frequency of high-risk disease among rural residents, suggests disparities in access to early PCa detection and diagnosis.

PMID:41978922 | DOI:10.3346/jkms.2026.41.e10