Tag: pubmed

BMC Oral Health. 2026 Feb 17. doi: 10.1186/s12903-026-07925-3. Online ahead of print.

ABSTRACT

BACKGROUND: Pain perception during dental procedures is a common cause of patient anxiety. The aim of this study was to compare the pain perception during anesthetic injection and patient preference between a conventional local anesthesia technique and a computer-controlled local anesthesia delivery (CCLAD) system.

METHODS: A randomized, crossover clinical trial was conducted with 40 patients who received both conventional and computerized local anesthesia using the SOGA Smart II device. A 2% lidocaine with epinephrine (1.8 ml, 1:100,000) was used for both techniques. In maxilla, infiltration technique was used and in mandible, Inferior Alveolar Nerve Block was administered. The pain during injection was assessed using a Visual Analogue Scale (VAS). Statistical analysis was performed using paired t-tests.

RESULTS: The mean VAS score for conventional anesthesia was 4.20 ± 1.16, and for the CCLAD system was 2.23 ± 1.23. The difference was statistically significant (p < 0.001). No gender-based differences in VAS scores were observed. The majority of patients expressed a preference for the computerized system.

CONCLUSION: The SOGA Smart II CCLAD system significantly reduces pain perception compared to conventional techniques. Most patients favored the electronic delivery method, suggesting its potential role as a patient-centered approach to reducing injection-related discomfort in selected clinical settings.

TRIAL REGISTRATION: Trial was registered retrospectively with the registration number: TCTR20250517004, dated 17th May, 2025.

PMID:41703537 | DOI:10.1186/s12903-026-07925-3

BMC Pediatr. 2026 Feb 17. doi: 10.1186/s12887-025-06379-w. Online ahead of print.

ABSTRACT

BACKGROUND: Because the respiratory system of extremely/very preterm infants is immature, respiratory support is essential to their care; however, the effects of invasive and non-invasive ventilation modes on prognosis and complications remain controversial. The efficacy and safety of invasive mechanical ventilation (IMV), nasal continuous positive airway pressure (NCPAP), and non-invasive high-frequency oscillatory ventilation (NHFOV) were to be compared in extremely/very preterm infants. METHODS: Clinical data from 220 extremely/very preterm infants admitted between January 2024 and March 2025 were retrospectively analyzed. Infants were stratified by initial ventilation modality into the invasive group (AG, n = 87), the non-invasive NCPAP group (BG, n = 82), and the non-invasive NHFOV group (CG, n = 51); treatment outcomes and complications were compared. RESULTS: The CG had the shortest total ventilation time (8.5 ± 2.8 days), the lowest rate of reintubation (17.6%), and the highest weaning success rate (88.2%), all of which were superior to the other groups (P < 0.05); the AG had the highest incidence of bronchopulmonary dysplasia (37.9%) and intracranial hemorrhage (13.8%) (P < 0.05). Mortality, necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), and sepsis incidence not statistically significant among the three groups (P > 0.05).

CONCLUSION: Non-invasive ventilation, especially NHFOV, was found to optimize treatment outcomes and reduce complications in extremely/very preterm infants; its preferential use was recommended.

PMID:41703503 | DOI:10.1186/s12887-025-06379-w

BMC Public Health. 2026 Feb 17. doi: 10.1186/s12889-026-26591-2. Online ahead of print.

ABSTRACT

BACKGROUND: New York City has recorded a historically low supply of housing affecting disproportionally low-resourced areas, including the Bronx. Affordable housing buildings are being built, however, little is known about the quality of life of residents living in affordable housing, nor what the impact of housing is on their quality of life or health.

METHODS: A pilot cross sectional study without a comparison group was conducted, to characterize the health-related quality-of-life (HRQoL) of residents from an affordable housing development located in Mott Haven, in the South East area of the Bronx in NYC. It also examined the impact of individual, health-related and housing domains of physical and mental health HRQoL outcomes. Data was collected on two occasions at two affordable housing developments. Descriptive statistics, contingency table analysis, and one-way analysis of variance (ANOVA) were used to compare SF-12 v2^® variables across the levels of 14 predictor variables categorized into 3 domains: demographics, housing, and health status. In addition, each of the SF-12 v2^® scales and subscales was analyzed in a multiple regression framework to estimate Cohen’s f² effect size statistics on these domains. The SF-12v2^® was scored by the PRO CoRE software.

RESULTS: The total sample was of 188 residents self-idenitifed with the following characteristics: 79% were females; 67.3% were older than 35 years; 58.0% were Hispanics; 57.4% have more than a high school education, while 12.2% have less than a high school education; 53.5% were single-parent households; 21.6% were two parents households with dependents that are minors; and 37.3% had an annual income of less than $15,000. The statistically significant results show that having a disability and a greater number of morbidities are associated with having a lower HRQoL in the Physical Composite Summary (PCS) and Mental Composite Summary (MCS), and in all of their subscales. Aging showed to be statistically significant in the PCS and its subscales. The regression analyses indicate that the health status domains have the highest effect on HRQoL subscales for physical and mental health, and the lowest size effect was on the housing domain.

CONCLUSION: This study serves as a baseline to increase the understanding on how to study the relationship between housing and HRQoL. Results suggest that older adult residents, those with multiple co-morbidities, and with disabilities need to be prioritized when developing interventions or programs in housing developents. This pilot investigation is among the few that focuses on housing developments in the Bronx and has the potential to inform how to develop housing developments with a focus on promoting health and the well-being of their residents.

PMID:41703492 | DOI:10.1186/s12889-026-26591-2

BMC Infect Dis. 2026 Feb 17. doi: 10.1186/s12879-026-12904-8. Online ahead of print.

NO ABSTRACT

PMID:41703469 | DOI:10.1186/s12879-026-12904-8

BMC Cardiovasc Disord. 2026 Feb 17. doi: 10.1186/s12872-026-05631-0. Online ahead of print.

NO ABSTRACT

PMID:41703467 | DOI:10.1186/s12872-026-05631-0

BMC Geriatr. 2026 Feb 18. doi: 10.1186/s12877-026-07161-y. Online ahead of print.

ABSTRACT

BACKGROUND: With the accelerating aging of the global population, muscle health issue occurs commonly as an age-related process in older people. The conventional low muscle mass screening and diagnosis reliant on bulky and costly instruments, remain challenging for regular self-monitoring. If routine physical examination information from primary healthcare settings is integrated and analyzed using appropriate statistical methods, it may be possible to derive robust predictions for low muscle mass screening. By doing so, we seek to explore an interpretable machine learning-based screening manner for low muscle mass among Chinese community-dwelling older adults.

METHODS: We recruited aged ≥ 60 years older adults from the baseline of the elderly nutrition and health cohort. Low muscle mass was assessed by BIA-measured appendicular skeletal muscle mass index (ASMI) using AWGS 2019 consensus cut-offs. Following physical examination in community health settings, individual information about the participants was measured and gathered, including general information, medical history, physical measurements and biochemical indicators. The primary objective of this study was to explore an interpretable machine learning-based screening manner for low muscle mass. For predicting low muscle mass (by classification) or ASMI (by regression), three representative supervised machine learning models were constructed. To make the prediction behavior of the model transparent and ease clinical use, SHAP algorithm and Shiny framework were utilized, respectively.

RESULTS: 569 Chinese community-dwelling older adult were enrolled. Among them, 99 participants (17.4%) were assessed with low muscle mass. Among three models tested, the random forest model exhibited superior overall performance and better generalizability for low muscle mass (AUC = 0.872 in test set), and the elastic net showed the best prediction performance for ASMI (R² = 0.763 in test sets). The identified key predictors of low muscle mass based SHAP algorithm revealed expected patterns, such as the importance of BMI, age, calf circumference, MNA score, but also unexpected variables, such as HDL. The final optimal prediction model was deployed in an interactive and user-friendly decision support application to facilitate the clinical application.

CONCLUSIONS: This study demonstrates that routine physical examination information could be a valuable component to incorporate into targeted assessments to screen low muscle mass among community-dwelling older adults. Building on this foundation, an interpretable machine learning approach was explored, which proves well-suited as a screening manner for low muscle mass to guide further standard assessment. Its suitability stems from superior predictive performance and operational feasibility in resource-constrained community health settings.

PMID:41703458 | DOI:10.1186/s12877-026-07161-y

J Public Health Dent. 2026 Feb 17. doi: 10.1111/jphd.70047. Online ahead of print.

ABSTRACT

OBJECTIVE: The Interim Canada Dental Benefit (CDB) provided financial support to families to cover dental care expenses for children < 12 years of age. The purpose of this study was to investigate oral health professionals’ (OHPs) views of the Interim CDB.

METHODS: OHPs in Manitoba, Canada were invited by e-mail to complete an online questionnaire. Data analysis included descriptive statistics (frequencies, means, and standard deviations), bivariate analysis (chi-squared and t-test), and multivariable logistic regression. A p-value < 0.05 was considered significant.

RESULTS: Overall, 383 OHPs participated, the majority being women (80.9%), from metropolitan areas (77.8%), and working for 16.6 ± 12.9 years. Main respondents included dentists (24.3%), dental hygienists (23.3%), and dental assistants (38.7%). Awareness of the benefit was high (92.7%) yet 45.8% were uncertain whether it increased public awareness of children’s oral health. Encouragement to apply was low (39.3%), although 56.5% believed that the Interim CDB improved access to children’s oral care. Multivariate logistic regression showed that rural OHPs encouraged application 43% more than those working in urban areas. Significantly more positive responses were observed among rural-based OHPs and women toward the benefit’s ability to improve access to oral health for children.

CONCLUSIONS: Overall, awareness was high among the OHPs, but uncertainty remained whether the benefit improved access to care for young children. OHPs in rural areas were more likely to believe that the Interim CDB improved access to care and were more likely to promote the program to families.

PMID:41703436 | DOI:10.1111/jphd.70047

Eur J Cardiovasc Nurs. 2026 Feb 18:zvaf223. doi: 10.1093/eurjcn/zvaf223. Online ahead of print.

ABSTRACT

AIMS: To generally explore the relative importance of factors influencing medication adherence after percutaneous coronary intervention (PCI), and to provide a new perspective on the theoretical framework of medication adherence intervention.

METHODS AND RESULTS: A single-centre, cross-sectional study was conducted. Primary outcomes were indicators of medication nonadherence, including incorrect implementation behaviour, medication taking proportion <90% and discontinuation. Potential influencing factors included baseline characteristics at PCI and barriers to medication adherence after PCI. Binary logistic regression was used to analyse factors associated with the indicators. A total of 901 cases with valid data were identified. Incorrect implementation behaviour, medication taking proportion <90%, and discontinuation after PCI were 39.3%, 16.6%, and 8.9%, respectively. Rural residence, lacking medication necessary, and medication side effects were common factors associated with the above three indicators, and complex prescriptions, disturbing routine, age (at this PCI), number of coronary stents (up to this PCI), economic difficulties, memory decline, inconvenience, busy, and extensive travel were uncommon factors associated with these three indicators.

CONCLUSION: Exploring the relative importance of factors influencing medication adherence after PCI provides a new perspective for integrating multifaceted and tailored interventions as a new system.

PMID:41703427 | DOI:10.1093/eurjcn/zvaf223

Clin Trials. 2026 Feb 17:17407745251415538. doi: 10.1177/17407745251415538. Online ahead of print.

ABSTRACT

BACKGROUND: An estimand is a clear description of the treatment effect a study aims to quantify. The ICH E9(R1) addendum lists five attributes that should be described as part of the estimand definition. However, the addendum was primarily developed for individually randomised trials. Cluster randomised trials, in which groups of individuals are randomised, have additional considerations for defining estimands (e.g. how individuals and clusters are weighted, how cluster-level intercurrent events are handled). However, it is currently unknown if estimands are being used in cluster randomised trials, or whether the considerations specific to cluster randomised trials are being described.

METHODS: We reviewed 73 cluster randomised trials published between October 2023 and January 2024 that were indexed in MEDLINE. For each trial, we assessed whether the estimand for the primary outcome was described, or if not, whether it could be inferred from the statistical methods. We also assessed whether considerations specific to cluster randomised trials were described or inferable, how trials were analysed and whether key assumptions being made in the analysis (e.g. ‘no informative cluster size’) could be identified.

RESULTS: No trials attempted to describe the estimand for their primary outcome. We were able to infer the five attributes outlined in ICH E9(R1) in only 49% of trials, and when including additional considerations specific to cluster randomised trials, this figure dropped to 21%. Key drivers of this ambiguity were lack of clarity around whether individual- or cluster-average effects were of interest (unclear in 63% of trials), and how cluster-level intercurrent events were handled (unclear in 21% of trials for which this was applicable). Over half of trials used mixed-effects models or generalising estimating equations with an exchangeable correlation structure, which make the assumption that there is no informative cluster size; however, only one of these trials performed sensitivity analyses to evaluate robustness of results to deviations from this assumption. There were 14% of trials that used independence estimating equations or the analysis of cluster-level summaries; however, because no trials stated whether they were targeting the individual- or cluster-average effect, it was impossible to determine whether these methods implemented the appropriate weighting scheme and were thus unbiased.

CONCLUSION: The uptake of estimands in published cluster randomised trial articles is low, making it difficult to ascertain which questions were being investigated or whether statistical estimators were appropriate for those questions. This highlights an urgent need to develop guidelines on defining estimands that cover unique aspects of cluster randomised trials to ensure clarity of research questions in these trials.

PMID:41703418 | DOI:10.1177/17407745251415538

J Appl Clin Med Phys. 2026 Feb;27(2):e70509. doi: 10.1002/acm2.70509.

ABSTRACT

PURPOSE: The InTempo adaptive imaging system is an important component of the Accuray CyberKnife System, designed to enhance the system’s ability to track and correct tumor motion during treatment. However, a limitation of this feature is the reduction of available nodes for treatment planning. The impact of a reduced number of nodes on the quality of InTempo-based treatment plans has not previously been evaluated. This retrospective study aims to compare the dosimetry of CyberKnife plans with and without The InTempo path set for both prostate and lung stereotactic body radiotherapy (SBRT).

METHODS: This study included twelve consecutive prostate SBRT patients and twenty selected lung SBRT patients. The selection criteria for the 20 lung patients were motivated by being able to construct a data set representative of common treatment tracking methods and dose prescriptions. To evaluate the impact of InTempo imaging, treatment plans were re-optimized using the same optimization parameters and machine settings, except for the path set with the maximum number of nodes. To ensure a fair comparison, the study plans were prescribed using identical planning target volume coverage as the clinical treatment plans. Statistical analyses were performed using mean and standard deviation, dose metric plots, and a two-sided Wilcoxon signed rank test with multiple testing correction to compare dose metrics between different path sets.

RESULTS: No statistically significant differences were observed among the Prostate, Prostate_Short, and their corresponding InTempo path sets in at least 8 of the 14 evaluated plan metrics, including prostate clinical tumor volume (CTV) V40Gy(%), conformity index, and homogeneity index. For example, the mean prostate CTV V40Gy (%) for the Prostate, Prostate_Short, and their corresponding InTempo path sets was 90.8 ± 4.7, 89.4 ± 4.7, 90.2 ± 3.9, 91.0 ± 7.0, respectively. However, compared with the Prostate path set, the Prostate_InTempo path set exhibited a statistically significant reduction in delivery time (p = 0.0010), number of beams, and bladder V18Gy (%), along with a statistically significant increase in the number of imaging beams (p = 0.0010). Additionally, Prostate_Short demonstrated statistically significant reductions in delivery time and number of beams compared with the Prostate path set, while the number of imaging beams remained statistically equivalent. In contrast, the Reduced_Prostate and Reduced_Prostate_InTempo sets consistently resulted in inferior dosimetric outcomes, with several plans deemed unoptimizable due to insufficient node availability. For lung SBRT, statistically significant differences were observed in delivery time and the number of imaging beams between plans with and without InTempo. However, no statistical differences were found in dose distribution metrics between these two lung groups.

CONCLUSIONS: InTempo-compatible path sets do not significantly compromise plan quality for prostate or lung SBRT, provided adequate node availability. Specifically, the Prostate_InTempo and Prostate_Short path sets demonstrated a reduction in delivery time and an increase in adaptive imaging frequency compared with the Prostate path set. However, the Reduced_Prostate and Reduced_Prostate_InTempo result in inferior plan quality and reduced deliverability and should be used with caution. These findings support the selective use of InTempo imaging in SBRT planning without sacrificing dosimetric integrity.

PMID:41703417 | DOI:10.1002/acm2.70509