Tag: statistics

Clin Exp Dent Res. 2025 Feb;11(1):e70113. doi: 10.1002/cre2.70113.

ABSTRACT

OBJECTIVES: To evaluate the level of oral health-related knowledge, attitudes, and behavior among a group of mothers with kindergarten (KG) children aged 3-5 years toward their own and their children’s oral health and assess its influence on their children’s oral health status.

MATERIAL AND METHODS: This was a cross-sectional study conducted in Jeddah, Saudi Arabia. The sample was selected randomly from public and private KGs in Jeddah. Self-administrated questionnaires were distributed to the mothers of KG schoolchildren aged 3-5 years, which contained translated and validated Mothers’ Behavior Questionnaire about their own oral health behaviors, Mothers’ Attitude Questionnaire about their children’s oral health, and Mothers’ Knowledge Questionnaire about their children’s oral health. The oral health of the KG school children was examined to determine the decayed, missed, and filled index (dmft).

RESULTS: A total of 461 child-mother pairs completed the study. The mean values of dmft were 5.41 ± 4.81. The children’s oral health (dental caries) and the mothers’ oral health-related knowledge, attitudes, and behavior were significantly associated with KG type (public vs. private), mothers’ age, mothers’ education, and family income. A multiple linear regression model indicated that younger mothers (< 30-40 years), highly educated mothers, high family income, and mothers with higher knowledge scores were significantly associated with lower dmft scores.

CONCLUSIONS: Mothers whose children attended private KGs exhibited better oral health-related attitudes, habits, and knowledge. School type, mother’s age, mother’s education level, and monthly income were factors that strongly impacted the behaviors, attitudes, and knowledge of the mothers. Dental caries was lower among children whose mothers were young, well-educated, from high family income families, and had higher knowledge related to oral health. Implementing targeted educational programs for mothers, particularly those with lower educational attainment and from low-income backgrounds, is essential for enhancing the oral health of children in kindergarten age.

PMID:40066470 | DOI:10.1002/cre2.70113

BJUI Compass. 2025 Jan 31;6(3). doi: 10.1002/bco2.424. eCollection 2025 Mar.

ABSTRACT

BACKGROUND AND OBJECTIVE: Prostate cancer (PCa) is a significant global health concern, ranking as the second most prevalent cancer among men worldwide. Genetic factors, particularly germline pathogenic variants (PVs) in DNA repair genes (DRGs), play a crucial role in PCa predisposition. Our study aimed to assess patients’ adherence to a targeted PCa screening program targeting high-risk individuals with DRG PVs and evaluate the potential reduction in biopsy and MRI rates by employing our screening protocol.

METHODS: We conducted a prospective ongoing trial evaluating targeted PCa screening in men with documented PVs in DRGs. Screening involved annual assessment of medical history, physical examination, prostate-specific antigen (PSA) testing, Prostate Health Index (PHI), and multiparametric magnetic resonance imaging (mpMRI) when indicated. Descriptive statistics were used to analyse patient characteristics, and adherence to screening was evaluated at three time points: baseline (T0), one year (T1), and two years (T2) from enrolment.

KEY FINDINGS AND LIMITATIONS: A total of 101 high-risk individuals were enrolled, with a median age of 52 years. Adherence to screening was high, with 72.3% of patients attending the first annual follow-up (T1) and 100% attending the second follow-up (T2). Despite elevated PSA levels in some patients, no PCa was detected during the study period. However, our screening protocol demonstrated the potential in reducing unnecessary biopsies and MRIs, particularly in patients with elevated PSA but low PHI values. Limitations include the ongoing nature of the study, small sample size, and lack of non-carrier controls.

CONCLUSIONS AND CLINICAL IMPLICATIONS: Our findings described a new PCa screening strategy integrated with genetic risk factors. The incorporation of PHI shows promise in improving the efficiency of diagnostic procedures while minimizing unnecessary interventions. High adherence among high-risk individuals underscores the potential effectiveness of targeted screening programs.

PMID:40066468 | PMC:PMC11891281 | DOI:10.1002/bco2.424

Front Pediatr. 2025 Feb 24;13:1533877. doi: 10.3389/fped.2025.1533877. eCollection 2025.

ABSTRACT

BACKGROUND: Artificial Intelligence (AI) has the potential to revolutionize Pediatric Intensive Care Units (PICUs) by enhancing diagnostic accuracy, improving patient outcomes, and streamlining routine tasks. However, integrating AI into PICU environments poses significant ethical and data privacy challenges, necessitating effective governance and robust regulatory frameworks to ensure safe and ethical implementation. This study aimed to explore valuable insights into healthcare professionals’ current perceptions and readiness to adopt AI in pediatric critical care, highlighting the opportunities and challenges ahead.

METHODS: A cross-sectional study conducted an online survey among healthcare practitioners at King Abdulaziz University Hospital in Jeddah, Saudi Arabia. The survey included questions about professional roles, experience, and familiarity with AI, their opinions on AI’s role, trust in AI-driven decisions, and ethical and privacy concerns. Statistical analyses were performed using IBM SPSS.

RESULTS: Results found varying familiarity with AI among healthcare professionals, with many expressing limited knowledge of AI applications in PICU settings. Despite this, there was growing recognition of AI’s current applications. Trust in AI-driven decisions for PICU management was mixed, with most expressing partial trust. Opinions on AI’s role in enhancing diagnostic accuracy and improving patient outcomes varied. Ethical considerations, data privacy, and effective governance to address regulatory and ethical challenges were highlighted as critical concerns.

CONCLUSION: Healthcare practitioners in the PICU preferred using AI for routine patient monitoring but had concerns about its use in diagnoses and advanced healthcare. Concerns were held regarding data privacy, security breaches, and patient confidentiality.

PMID:40066464 | PMC:PMC11891184 | DOI:10.3389/fped.2025.1533877

Med Care. 2025 Apr 1;63(4):293-299. doi: 10.1097/MLR.0000000000002116. Epub 2025 Jan 3.

ABSTRACT

OBJECTIVES: This study illustrates how the statistical reliability of an individual measure relates to the overall reliability of a composite metric, as understanding this relationship provides additional information when evaluating measures for endorsement.

BACKGROUND: National quality measure endorsement processes typically evaluate individual metrics on criteria such as importance and scientific acceptability (eg, reliability). In practice, quality measures may be used in composite rating systems, which aid in the interpretation of overall quality differences.

METHODS: We define an individual measure’s reliability by its intraclass correlation and analytically establish the relationship between a composite’s reliability and the reliability of its components. We use real data to confirm this relationship under various scenarios. We are motivated by 8 quality measures, which comprise the Quality of Patient Care Star Ratings on Dialysis Facility Care Compare. These measure 4 primary outcomes (mortality, hospitalizations, readmissions, and blood transfusions), vascular access (2 measures), and facility processes (2 measures).

RESULTS: Depending on the reliability of the individual measures, their respective weights in the composite, and their pairwise correlations, there are circumstances when adding a new measure, even if it is less reliable, increases the composite’s reliability. For the dialysis facility Star Ratings, we find that the combined reliability of measures grouped within certain domains of care exceeded the reliability of the individual measures within those domains.

CONCLUSIONS: New quality measures may add utility to a composite rating system under certain circumstances-a consideration that should, in part, factor into quality measure endorsement processes.

PMID:40064621 | DOI:10.1097/MLR.0000000000002116

Community Dent Oral Epidemiol. 2025 Mar 10. doi: 10.1111/cdoe.13037. Online ahead of print.

ABSTRACT

OBJECTIVES: To evaluate and compare the rates of antibiotic prescribing by dental practitioners across the constituent countries of the United Kingdom between March 2020 and August 2023 and to estimate the total ‘excess’ prescribing that occurred during this interval beyond the rates predicted based upon trends between March 2016 and February 2020.

METHODS: Retrospective pharmacoepidemiological study of dental practitioners’ antibiotic prescribing, by secondary analysis of population-level National Health Service dispensing data from England, Scotland, Wales and Health and Social Care dispensing data from Northern Ireland.

RESULTS: Effective August 2023, the antibiotic items dispensed rate for each country remained in excess of that predicted based upon pre-pandemic trends. Between March 2020 and August 2023, those rates were 175.6, 227.2, 195.0 and 321.8 antibiotic items per 1000 population for England, Scotland, Wales and Northern Ireland, respectively. Those represented estimated total ‘excesses’ of 27.7% (95% confidence limit [CL], 14.8, 43.7), 43.3% (95% CL, 29.9, 60.0), 33.2% (95% CL, 20.4, 49.0) and 42.9% (95% CL, 27.6, 62.3). Pairwise comparisons showed statistically significant differences between England and Scotland, England and Northern Ireland, and Wales and Northern Ireland (p < 0.001), Scotland and Wales (p = 0.001), and Scotland and Northern Ireland (p = 0.009). There was no statistically significant difference between England and Wales.

CONCLUSIONS: With shared prescribing guidelines and a single professional regulatory framework, it was unsurprising that similar antibiotic prescribing trends were found across the United Kingdom. Further research is required to investigate the reasons for the differences.

PMID:40064619 | DOI:10.1111/cdoe.13037

Clin Chem Lab Med. 2025 Mar 11. doi: 10.1515/cclm-2024-1193. Online ahead of print.

ABSTRACT

R language has gained traction in laboratory medicine for its statistical power and dynamic tools like RMarkdown and RShiny. However, there is limited literature summarizing R packages and functions tailored for laboratory medicine, making it difficult for clinical laboratory workers to access these tools. Additionally, varying algorithms across R packages can lead to inconsistencies in published reports. This review addresses these challenges by providing an overview of R’s evolution and its key features, followed by a summary of statistical methods implemented in R, including platform comparisons, precision verification, factor analysis, and the establishment of reference intervals (RIs). We also highlight the development and validation of predictive models using techniques such as linear and logistic regression, decision trees, random forests, support vector machines, naive Bayes, K-Nearest Neighbors, k-means clustering, and backpropagation neural networks – all implemented in R. To ensure transparency and reproducibility in research, a checklist is provided for authors publishing papers using R for data analysis in laboratory medicine. In the final section, the potential of R in big data analytics is explored, focusing on standardized reporting through RMarkdown and the creation of user-friendly data visualization platforms with RShiny. Moreover, the integration of large language models (LLMs), such as ChatGPT, is discussed for their benefits in enhancing R programming, automating reporting, and offering insights from data analysis, thus improving the efficiency and accuracy of laboratory data analysis.

PMID:40064613 | DOI:10.1515/cclm-2024-1193

Nurs Health Sci. 2025 Mar;27(1):e70076. doi: 10.1111/nhs.70076.

ABSTRACT

Nursing care for older people with advanced cancer who live alone during outpatient chemotherapy should address their difficulties while respecting their lives. However, their lived experiences remain underexplored. Therefore, we conducted a descriptive qualitative study to explore and describe their lives. The participants were purposively sampled, older patients (≥ 65 years) with advanced cancer who lived alone and were receiving outpatient cancer chemotherapy. Semi-structured interviews were conducted using an interview guide, and thematic analysis was applied. There were 12 participants. Nine categories and 49 subcategories were extracted. The core category was “Getting by through endurance, ingenuity, and effort in one’s increasingly fragile ‘own vessel,’ in order to survive a little longer and fulfill one’s life.” Effective support should not only address their challenges, but also respect their convictions, leverage their strengths, and enhance their self-efficacy. Further, early implementation of advance care planning (ACP) is crucial to proactively identify the needs of these patients, who rarely express their concerns. This approach facilitates their transition from full independence to autonomy, enabling them to choose and integrate necessary support into their daily lives.

PMID:40064605 | DOI:10.1111/nhs.70076

Pharm Stat. 2025 Mar-Apr;24(2):e70009. doi: 10.1002/pst.70009.

ABSTRACT

A new measure was recently developed in the context of survival analysis that can be interpreted as a weighted arithmetic mean of the hazards with the survival function as the weight. However, when the average hazard is desired, it is more appropriate to use the harmonic mean rather than the arithmetic mean. Therefore, in this article, we derive the average hazard as a harmonic mean version of the expectation for hazards and show it to be equal to the previous weighted arithmetic mean. Furthermore, we demonstrate that the average hazard should be estimated using only the times at which the event is observed, while previous studies have allowed estimating the average hazard even when the truncation time is set to a time at which the event is not observed.

PMID:40064601 | DOI:10.1002/pst.70009

World J Surg. 2025 Mar 10. doi: 10.1002/wjs.12522. Online ahead of print.

ABSTRACT

INTRODUCTION: Multiple endocrine neoplasia type 1 (MEN1) syndrome is characterized by presenting different pathologies with different degrees of tumor aggressiveness, which can greatly affect the quality of life of affected patients.

OBJECTIVES: To determine the quality of life of MEN1 patients and to analyze the influence of socio-personal, clinical, and therapeutic variables.

METHODS: A study was conducted on MEN1 patients in a tertiary hospital [2018-2020]. The 36-Item Short Form Health Survey (SF-36) scores were compared with those of a control group (CG) of a healthy population.

STATISTICAL ANALYSIS: Student’s t-test/ANOVA test or the Mann-Whitney U test/Kruskal-Wallis H test. A multivariate analysis was applied to assess the SP, clinical, and therapeutic variables affecting the quality of life.

RESULTS: The quality of life scores of 101 MEN 1 patients, who presented lower levels of quality of life in various dimensions compared to the control group, (p < 0.05) were analyzed. Patients with pancreatic pathology showed a worsening in most dimensions of the SF-36 questionnaire (p < 0.05). In addition, pancreatic surgery influenced 3/9 dimensions and the mental component score (MCS) (p < 0.05). In the multivariate analysis, occupational status and pancreatic surgery were the variables most related to the quality of life of patients with MEN1 (p < 0.05) in addition to the existence of a carcinoid tumor, which influenced the physical component score (PCS) (p < 0.05).

CONCLUSION: MEN1 patients have a worse quality of life than the general population. Of the socio-personal variables analyzed, the best predictor is being unemployed. Pancreatic and carcinoid pathology affected quality of life. Pancreatic surgery fundamentally influences the mental component score, whereas total pancreatectomy influences the physical component score.

PMID:40064591 | DOI:10.1002/wjs.12522

Psychooncology. 2025 Mar;34(3):e70119. doi: 10.1002/pon.70119.

ABSTRACT

BACKGROUND: The COVID-19 pandemic exacerbated mental health challenges. This study aimed to investigate the mental health impact of the pandemic on cancer survivors from diverse backgrounds using the All of Us Research Program’s COVID-19 Participant Experience (COPE) survey.

METHODS: This analysis included respondents of the COPE survey with average depression, anxiety, and self-harm metrics computed for individuals completing multiple survey iterations. Multivariable logistic regression assessed the relationship between cancer survivorship, demographic factors, and mental health outcomes. Sensitivity analyses were conducted to investigate peak mental health challenges and time trend.

RESULTS: Among 100,203 respondents, 20,561 (20.5%) were cancer survivors. Cancer survivors differed demographically from the general population, tending to be older and more likely to report higher socioeconomic status. Cancer survivors exhibited significantly higher odds of self-harm (aOR = 1.09, 95% CI 1.01-1.18). Sensitivity analyses focusing on peak mental health scores revealed that cancer survivors had significantly increased odds of experiencing anxiety (aOR = 1.11, 95% CI 1.06-1.17), depression (aOR = 1.11, 95% CI 1.06-1.17), and self-harm tendencies (aOR = 1.09, 95% CI 1.01-1.18) compared to non-cancer survivors. Within the cancer survivor subgroup, younger age, gender and sexual minority status, lower income, and widowed/separated/divorced status were associated with worse mental health outcomes.

CONCLUSION: During the COVID-19 pandemic, cancer survivors exhibited significantly higher odds of depression, anxiety, and self-harm compared to non-survivors, with certain subgroups demonstrating heightened vulnerability. Our study highlights the critical need for integrated mental health services in cancer survivorship care programs, especially among those from underserved groups who are at high risk, as we continue to evolve with the pandemic.

PMID:40064590 | DOI:10.1002/pon.70119