Category: Nevin Manimala

Int J Oral Maxillofac Implants. 2025 Apr 25;0(0):1-31. doi: 10.11607/jomi.11308. Online ahead of print.

ABSTRACT

PURPOSE: this study evaluates implant success rates and facial mucosal profile changes in maxillary single immediate implant placement and provisionalization with socket-shield (IIPP+SS) and without socket-shield (IIPP-SS) technique.

MATERIALS & METHODS: thirty dental implants in 25 patients were assigned to either the IIPP-SS group (15 implants) or the IIPP+SS (15 implants) group. Clinical and radiographic outcomes were collected at pre-surgery (T0), 2- week (T1), 6-month (T6), and 12-month (T12) post-surgical follow-ups. The implant success rate, marginal bone level changes, facial mucosal level changes, and papilla level changes were evaluated at different time points. Facial mucosal profile changes were assessed individually for hard and soft tissue zones and as a whole using volumetric analysis.

RESULTS: two implants were excluded (1 patient dropped out and 1 implant failed) from the data analysis in this study, resulting in an overall implant success rate of 96.6% (28/29) after 1 year. Less facial mucosal profile changes were noted in the IIPP+SS group than in the IIPP-SS group, although the difference was only marginally statistically significant (p= 0.06). No statistically significant difference was found in the facial mucosal level changes (p=0.18) and papilla level changes (p = 0.67 for mesial papilla level and p = 0.41 for distal papilla level) changes between the IIPP-SS and IIPP+SS groups.

CONCLUSIONS: Within the limitations of this 1-year prospective study, IIPP+SS appears to maintain only the implant facial mucosal profile slightly better than IIPP alone. Both treatment modalities provide clinically satisfactory outcomes biologically, functionally, and esthetically.

PMID:40279379 | DOI:10.11607/jomi.11308

JAMA Netw Open. 2025 Apr 1;8(4):e256930. doi: 10.1001/jamanetworkopen.2025.6930.

ABSTRACT

IMPORTANCE: Evaluation for myocardial infarction (MI) in emergency departments (EDs) is a common, resource-intensive process. High-sensitivity cardiac troponin I (hs-cTnI) assays have become a key tool in rapidly ruling out MI, with the potential to reduce health care resource utilization.

OBJECTIVE: To determine whether a 0-hour and 1-hour (hereafter referred to as 0/1-hour) hs-cTnI accelerated protocol reduces health care resource utilization compared with a traditional 0/3-hour standard care protocol for MI exclusion in the ED.

DESIGN, SETTING, AND PARTICIPANTS: This is a prespecified secondary analysis of the RACE-IT trial, a stepped-wedge randomized clinical implementation trial conducted across 9 EDs in Michigan. The trial enrolled 32 608 consecutive ED patients evaluated for suspected MI between July 8, 2020, and April 3, 2021. Statistical analysis was conducted from July 10 to September 5, 2024.

INTERVENTIONS: The 0/1-hour hs-cTnI accelerated protocol for MI exclusion was compared with the traditional 0/3-hour standard care protocol.

MAIN OUTCOMES AND MEASURES: Main outcomes were ED discharge to home, ED length of stay, rates of cardiac stress testing, cardiology consultation, left heart catheterization, and cardiac revascularization within 30 days.

RESULTS: A total of 32 608 patients (median age, 59 years [IQR, 45-71 years]; 18 705 women [57.4%]) were included in the analysis. The rate of ED discharge to home was 58.0% for the accelerated protocol group (11 082 of 19 103) and 59.8% for the standard care group (8070 of 13 505) (adjusted odds ratio [AOR], 1.05; 95% CI, 0.95-1.15). The accelerated protocol group showed significant reductions in the odds of cardiac stress testing (3.3% [623 of 19 103] vs 3.9% [526 of 13 505]; AOR, 0.62; 95% CI, 0.49-0.78), cardiology consultations (8.6% [1640 of 19 103] vs 12.2% [1651 of 13 505]; AOR, 0.57; 95% CI, 0.49-0.67), and left heart catheterization rates (1.0% [198 of 19 103] vs 1.2% [167 of 13 505]; AOR, 0.65; 95% CI, 0.43-0.99) compared with the standard protocol group. The median ED length of stay decreased by 20 minutes (IQR, 18-24 minutes) in the accelerated protocol group, with no significant change in revascularization rates.

CONCLUSIONS AND RELEVANCE: This secondary analysis of a randomized clinical trial of a 0/1-hour hs-cTnI protocol to rule out MI in the ED found that there was a reduction in cardiac evaluations and ED length of stay without increasing revascularization rates compared with the standard 0/3-hour hs-cTnI protocol. This approach could optimize health care resources in EDs.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04488913.

PMID:40279128 | DOI:10.1001/jamanetworkopen.2025.6930

JAMA Netw Open. 2025 Apr 1;8(4):e257227. doi: 10.1001/jamanetworkopen.2025.7227.

ABSTRACT

IMPORTANCE: Racial and ethnic disparities in uterine cancer survival are well-documented; however, limited data exist regarding the interplay of geography, diversity, and race and ethnicity in survival disparities.

OBJECTIVE: To examine associations of race and ethnicity with uterine cancer-specific survival according to geographic region and regional diversity.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included patients with uterine cancer diagnosed from 2000 to 2019, from 17 Surveillance, Epidemiology, End Results registries, grouped by US location and ranked according to the US Census Bureau’s Diversity Index (DI; range, 0%-100%; higher values indicate greater diversity), a metric of racial and ethnic composition. Analyses were conducted from June 8, 2024 to October 30, 2024.

EXPOSURES: Race and ethnicity of patients with uterine cancer, categorized as Asian, Black, Hispanic, and White.

MAIN OUTCOMES AND MEASURES: Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs for multivariable-adjusted associations of race and ethnicity with uterine cancer-specific survival (primary outcome) in the overall sample and stratified by location. Location-stratified models were used to examine whether associations of race and ethnicity with survival varied by tumor characteristics.

RESULTS: Among 162 500 patients with uterine cancer (median [IQR] age at diagnosis, 61 [54-69] years), there were 12 226 Asian patients (7.5%), 14 007 Black patients (8.6%), 20 799 Hispanic patients (12.8%), and 115 468 White patients (71.1%). Cancer-specific survival was better among Asian patients (HR, 0.91; 95% CI, 0.86-0.97), worse among Black patients (HR, 1.34; 95% CI, 1.28-1.40), and not different among Hispanic patients (HR, 1.01; 95% CI, 0.97-1.06) compared with White patients. Location-stratified analyses found worse uterine cancer-specific survival among Black patients compared with White patients in both higher DI locations (California: HR, 1.34; 95% CI, 1.25-1.44; DI, 69.7%; New Jersey: HR, 1.34; 95% CI, 1.21-1.50; DI, 65.8%; Georgia: HR, 1.39; 95% CI, 1.26-1.53; DI = 64.1%) and lower DI locations (Louisiana: HR, 1.34; 95% CI, 1.16-1.54; DI = 58.6%; Connecticut: HR, 1.42; 95% CI, 1.17-1.72; DI, 55.7%; Iowa: HR, 1.71; 95% CI, 1.01-2.89; DI, 30.8%). Hispanic patients, compared with White patients, had worse survival in Hawaii (HR, 2.09; 95% CI, 1.28-3.42) and Georgia (HR, 1.44; 95% CI, 1.13-1.82), whereas Asian patients had better survival than White patients in California (HR, 0.91; 95% CI, 0.84-0.97). In locations demonstrating survival disparities between Black and White patients, these patterns were evident in most tumor characteristic-defined strata.

CONCLUSIONS AND RELEVANCE: In this cohort study of patients with uterine cancer, racial and ethnic disparities in survival within specific geographic areas were identified. Targeted research may reduce national disparities.

PMID:40279127 | DOI:10.1001/jamanetworkopen.2025.7227

JAMA Netw Open. 2025 Apr 1;8(4):e257288. doi: 10.1001/jamanetworkopen.2025.7288.

ABSTRACT

IMPORTANCE: Digital health technologies (DHTs) aiming to monitor, treat, and manage diseases can be prescribed for patients with multimorbidity; yet most DHTs are designed for individual conditions or problems, while approximately half of patients with chronic conditions have multiple chronic conditions.

OBJECTIVES: To identify DHTs approved by the US Food and Drug Administration (FDA) or listed in the Organisation for the Review of Care and Health Apps (ORCHA) library and prescribable for a hypothetical patient with 5 conditions and to model the number of DHTs this patient should be prescribed to receive benefits health professionals considered important.

EVIDENCE REVIEW: The FDA databases (Premarket Notification 510(k), Premarket Approval, and De Novo) and the ORCHA App Library from National Health Service Somerset were systematically searched for DHTs registered or updated between January 1, 2019, and December 31, 2022, that could be prescribed to a hypothetical woman with 5 chronic conditions (type 2 diabetes, hypertension, chronic obstructive pulmonary disease, osteoporosis, and osteoarthritis). After abstracting each DHT’s elementary functions (ie, simple and delineated features to monitor, treat, and/or manage conditions), an assessment was undertaken to determine the fewest DHTs this hypothetical patient should be prescribed to receive benefit from digital functions health professionals considered important.

FINDINGS: A total of 148 DHTs were identified (68 [46%] from FDA databases), of which 96 (65%) involved devices and 52 (35%) were standalone health apps. Only 5 DHTs (3.4%) were intended for 2 or more conditions. DHTs offered 140 elementary functions, ranging from recording, tracking, or visualizing health parameters to providing information to digital therapeutics with just-in-time interventions. The hypothetical patient would need to be prescribed up to 13 apps and 7 devices (a blood pressure monitor, a smartwatch, a pulse oximeter, a connected weight scale, a sensor-attached inhaler to monitor adherence, a lung function monitor, and a blood glucose sensor) to receive benefits from 28 functions at least 3 of 5 health professionals considered important.

CONCLUSIONS AND RELEVANCE: This systematic review found that almost all prescribable DHTs were developed for a single condition or problem. Thus, patients with multiple chronic conditions would have to routinize many DHTs concurrently in daily life to benefit from digital functions health professionals considered important.

PMID:40279126 | DOI:10.1001/jamanetworkopen.2025.7288

JAMA Netw Open. 2025 Apr 1;8(4):e257295. doi: 10.1001/jamanetworkopen.2025.7295.

ABSTRACT

IMPORTANCE: Alcohol use disorder (AUD) may negatively affect preexposure prophylaxis (PrEP) adherence and continuation, reducing PrEP effectiveness.

OBJECTIVE: To estimate the prevalence of and and factors associated with AUD diagnoses among commercially insured individuals who take PrEP.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used US health care claims data to identify individuals aged 16 to 64 years who received at least 1 new PrEP prescription between January 1, 2014, to December 31, 2021. Data were analyzed from June 2024 to February 2025.

EXPOSURE: Sociodemographic characteristics included patient age, sex, geographic location, employment status, and type of health insurance. Clinical characteristics included sexually transmitted infection (STI) diagnosis and testing, use of psychotherapy services, and diagnosis of other mental health conditions.

MAIN OUTCOMES AND MEASURES: The main outcome was an AUD diagnosis within 6 months before or after the date of PrEP initiation. Among individuals with an AUD diagnosis, receipt of medications for AUD (MAUDs), including Food and Drug Administration (FDA)-approved MAUDs (acamprosate, disulfiram, and oral and injectable naltrexone) and non-FDA-approved MAUDs (baclofen, gabapentin, and topiramate) was determined.

RESULTS: The study cohort included 43 913 individuals receiving PrEP (mean [SD] age, 35.8 [10.94] years; 35 027 [90.1%] male assigned at birth). There were 6274 individuals (14.29%) who had an AUD diagnosis, with 1245 (2.84%) and 5029 (11.45%) receiving their diagnosis before and after PrEP initiation, respectively. The sociodemographic and clinical factors that were associated with an AUD diagnosis were similar whether AUD was diagnosed before or after PrEP initiation, including male sex assigned at birth (before: adjusted odds ratio [aOR], aOR, 0.62; 95% CI, 0.52-0.73; after: aOR, 0.81; 95% CI, 0.73-0.90) and the presence of other mental health diagnoses such as depression (before: aOR, 3.26; 95% CI, 2.78-3.84; after: aOR, 3.17; 95% CI, 2.88-3.49), anxiety (before: aOR, 2.16; 95% CI, 1.83-2.55; after: aOR, 2.24; 95% CI, 2.04-2.46), and any substance use disorder (before: aOR, 14.54; 95% CI, 12.46-16.96; after: aOR, 13.09; 95% CI, 11.82-14.49). There were 531 individuals with AUD diagnosis (8.46%) who received an FDA-approved MAUD and 883 (14.07%) who had a claim for a non-FDA-approved MAUD.

CONCLUSIONS AND RELEVANCE: This population-based cohort study found that nearly 15% of individuals who took PrEP had an AUD diagnosis within 6 months of PrEP initiation; individuals with an AUD diagnosis were more likely to have co-occurring mental health conditions, and less than 9% received any FDA-approved MAUD. These findings suggest that interventions are needed to improve AUD services among individuals who take PrEP.

PMID:40279125 | DOI:10.1001/jamanetworkopen.2025.7295

Biometrics. 2025 Apr 2;81(2):ujaf042. doi: 10.1093/biomtc/ujaf042.

ABSTRACT

The coexistences of high dimensionality and strong correlation in both responses and predictors pose unprecedented challenges in identifying important predictors. In this paper, we propose a model-free conditional feature screening method with false discovery rate (FDR) control for ultrahigh-dimensional multi-response setting. The proposed method is built upon partial distance correlation, which measures the dependence between two random vectors while controlling effect for a multivariate random vector. This screening approach is robust against heavy-tailed data and can select predictors in instances of high correlation among predictors. Additionally, it can identify predictors that are marginally unrelated but conditionally related with the response. Leveraging the advantageous properties of partial distance correlation, our method allows for high-dimensional variables to be conditioned upon, distinguishing it from current research in this field. To further achieve FDR control, we apply derandomized knockoff-e-values to establish the threshold for feature screening more stably. The proposed FDR control method is shown to enjoy sure screening property while maintaining FDR control as well as achieving higher power under mild conditions. The superior performance of these methods is demonstrated through simulation examples and a real data application.

PMID:40279121 | DOI:10.1093/biomtc/ujaf042

Biometrics. 2025 Apr 2;81(2):ujaf040. doi: 10.1093/biomtc/ujaf040.

ABSTRACT

Many studies employ the analysis of time-to-event data that incorporates competing risks and right censoring. Most methods and software packages are geared towards analyzing data that comes from a continuous failure time distribution. However, failure-time data may sometimes be discrete either because time is inherently discrete or due to imprecise measurement. This paper introduces a new estimation procedure for discrete-time survival analysis with competing events. The proposed approach offers a major key advantage over existing procedures and allows for straightforward integration and application of widely used regularized regression and screening-features methods. We illustrate the benefits of our proposed approach by a comprehensive simulation study. Additionally, we showcase the utility of the proposed procedure by estimating a survival model for the length of stay of patients hospitalized in the intensive care unit, considering 3 competing events: discharge to home, transfer to another medical facility, and in-hospital death. A Python package, PyDTS, is available for applying the proposed method with additional features.

PMID:40279120 | DOI:10.1093/biomtc/ujaf040

Biometrics. 2025 Apr 2;81(2):ujaf044. doi: 10.1093/biomtc/ujaf044.

ABSTRACT

Valid statistical inference is notoriously challenging when the sample is subject to nonresponse bias. We approach this difficult problem by employing multiple candidate models for the propensity score (PS) function combined with empirical likelihood. By incorporating multiple working PS models into the internal bias calibration constraint in the empirical likelihood, the selection bias can be safely eliminated as long as the working PS models contain the true model and their expectations are equal to the true missing rate. The bias calibration constraint for the multiple PS models is called the multiple bias calibration. The study delves into the asymptotic properties of the proposed method and provides a comparative analysis through limited simulation studies against existing methods. To illustrate practical implementation, we present a real data analysis on body fat percentage using the National Health and Nutrition Examination Survey dataset.

PMID:40279119 | DOI:10.1093/biomtc/ujaf044

Biometrics. 2025 Apr 2;81(2):ujaf041. doi: 10.1093/biomtc/ujaf041.

ABSTRACT

Dynamic treatment regimes (DTRs) are sequences of functions that formalize the process of precision medicine. DTRs take as input patient information and output treatment recommendations. A major focus of the DTR literature has been on the estimation of optimal DTRs, the sequences of decision rules that result in the best outcome in expectation, across the complete population if they were to be applied. While there is a rich literature on optimal DTR estimation, to date, there has been minimal consideration of the impacts of nonadherence on these estimation procedures. Nonadherence refers to any process through which an individual’s prescribed treatment does not match their true treatment. We explore the impacts of nonadherence and demonstrate that, generally, when nonadherence is ignored, suboptimal regimes will be estimated. In light of these findings, we propose a method for estimating optimal DTRs in the presence of nonadherence. The resulting estimators are consistent and asymptotically normal, with a double robustness property. Using simulations, we demonstrate the reliability of these results, and illustrate comparable performance between the proposed estimation procedure adjusting for the impacts of nonadherence and estimators that are computed on data without nonadherence.

PMID:40279118 | DOI:10.1093/biomtc/ujaf041

JAMA Health Forum. 2025 Apr 4;6(4):e250724. doi: 10.1001/jamahealthforum.2025.0724.

ABSTRACT

IMPORTANCE: The US Centers for Medicare & Medicaid Services launched the Accountable Care Organization (ACO) Realizing Equity, Access, and Community Health (REACH) payment model in January 2023. In contrast to prior ACO initiatives, such as the Medicare Shared Savings Program (MSSP), ACO REACH includes equity-focused measures and payment adjustments, including an equity plan and financial risk adjustment for ACOs with higher proportions of underserved beneficiaries. However, it is unknown whether these changes have incented participation from organizations that serve beneficiaries from marginalized communities.

OBJECTIVE: To compare characteristics between participants in ACO REACH with those in MSSP and the broader pool of Medicare beneficiaries, organizations, and clinicians.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study included all Medicare beneficiaries clinicians, and ACOs enrolled in fee-for-service Medicare, MSSP, and ACO REACH from January 2022 to January 2023.

EXPOSURE: Enrollment in fee-for-service Medicare, MSSP, or ACO REACH.

MAIN OUTCOMES AND MEASURES: Beneficiary, clinician, and ACO characteristics.

RESULTS: In 2023, among 35 801 118 beneficiaries in the overall fee-for-service Medicare program, 18 911 213 (52.8%) were female, and 163 706 (0.5%) were American Indian or Alaska Native, 1 251 553 (3.5%) were Asian or Pacific Islander, 2 952 244 (8.2%) were Black, 2 396 771 (6.7%) were Hispanic, 27 642 765 (77.2%) were White, and 1 394 079 (3.9%) were another race (includes individuals who did not identify with a listed race, including those who self-identified as multiracial) or unknown race. A total of 1 958 881 beneficiaries were attributed to ACO REACH, and 11 340 987 were attributed to MSSP. A total of 132 ACOs participated in ACO REACH, while 456 ACOs participated in the MSSP. Compared with Medicare beneficiaries overall, REACH beneficiaries were older (85 years or older: 14.2% vs 10.3%; standardized mean difference [SMD], 0.44) and more often White (80.2% vs 77.2%) and less often Black (5.9% vs 8.2%) or Hispanic (5.8% vs 6.7%) (SMD, 0.24). REACH beneficiaries were slightly less likely to have Medicare entitlement due to disability (15.2% vs 17.6%) or be dually enrolled (15.1% vs 15.8%) (SMD, 0.07). REACH beneficiaries were less likely to be rural (3.9% vs 8.4%; SMD, 0.19) and less likely to reside in highly vulnerable geographic areas based on the Social Vulnerability Index (27.7% vs 29.4%; SMD, 0.08) compared with beneficiaries overall.

CONCLUSIONS AND RELEVANCE: These findings suggest that, in its first year, ACO REACH did not achieve its goal of enrolling organizations that serve beneficiaries with high levels of social risk. Without broader participation, ACO REACH is unlikely to achieve its goal of reducing health inequities.

PMID:40279112 | DOI:10.1001/jamahealthforum.2025.0724