Tag: statistics

J Eat Disord. 2024 Dec 30;12(1):216. doi: 10.1186/s40337-024-01174-x.

ABSTRACT

BACKGROUND: Training gaps regarding the diagnosis and management of eating disorders in diverse populations, including racial, ethnic, sexual, and gender minoritized groups, have not been thoroughly examined.

OBJECTIVE: This study aimed to examine resident physicians’ knowledge and attitudes regarding eating disorders in diverse populations, with a focus on areas for improved training and intervention.

METHODS: Ninety-two resident physicians in internal medicine, emergency medicine, obstetrics/gynecology, psychiatry, and surgery at an academic center completed an online survey from 12/1/2020-3/1/2021, which comprised multiple choice and vignette-style open-ended questions to assess knowledge and attitudes toward the management and clinical presentations of eating disorders. Overall, the survey response rate was 25.7%. Descriptive statistics were reported. Vignette-style questions were analyzed using inductive coding and the frequency of responses was reported.

RESULTS: A minority of resident physicians self-reported confidence in their knowledge of the medical complications (n = 42, 45%), risk factors (n = 38, 41%), and clinical presentations (n = 32, 35%) associated with eating disorders. Responses to vignette-style questions correctly identified relevant management methods (such as electrolyte monitoring and referral to specialty care), but demonstrated limited knowledge of the clinical presentation of eating disorders. Furthermore, most respondents reported a lack of knowledge regarding eating disorders in sexual and gender minoritized patients (n = 68, 73.9%) as well as racial and ethnic minoritized patients (n = 64, 69.6%).

CONCLUSIONS: Our findings suggest concerning gaps in knowledge and confidence among resident physicians with regard to the diagnosis and treatment of eating disorders, particularly in racial, ethnic, sexual, and gender minoritized patients. Moreover, responses to vignette-like questions indicate significant homogeneity in respondents’ perceptions of the clinical presentation of eating disorders, reflecting cultural biases which associate eating disorders with underweight, young, female patients. The majority did not feel competent in treating eating disorders in diverse populations and expressed desire for additional training in this area. More research is needed to better understand and address these gaps in eating disorder training, with the goal of increasing equity in patient outcomes.

PMID:39736744 | DOI:10.1186/s40337-024-01174-x

BMC Health Serv Res. 2024 Dec 31;24(1):1665. doi: 10.1186/s12913-024-12184-5.

ABSTRACT

BACKGROUND: The demand for quality healthcare is rising worldwide, and nurses in South Africa are under pressure to provide care with limited resources. This demanding work environment leads to burnout and exhaustion among nurses. Understanding the specific factors leading to these issues is critical for adequately supporting nurses and informing policymakers. Currently, little is known about the unique factors associated with burnout and emotional exhaustion among nurses in South Africa. Furthermore, whether these factors can be predicted using demographic data alone is unclear. Machine learning has recently been proven to solve complex problems and accurately predict outcomes in medical settings. In this study, supervised machine learning models were developed to identify the factors that most strongly predict nurses reporting feelings of burnout and experiencing emotional exhaustion.

METHODS: The PyCaret 3.3 package was used to develop classification machine learning models on 1165 collected survey responses from nurses across South Africa in medical-surgical units. The models were evaluated on their accuracy score, Area Under the Curve (AUC) score and confusion matrix performance. Additionally, the accuracy score of models using demographic data alone was compared to the full survey data models. The features with the highest predictive power were extracted from both the full survey data and demographic data models for comparison. Descriptive statistical analysis was used to analyse survey data according to the highest predictive factors.

RESULTS: The gradient booster classifier (GBC) model had the highest accuracy score for predicting both self-reported feelings of burnout (75.8%) and emotional exhaustion (76.8%) from full survey data. For demographic data alone, the accuracy score was 60.4% and 68.5%, respectively, for predicting self-reported feelings of burnout and emotional exhaustion. Fatigue was the factor with the highest predictive power for self-reported feelings of burnout and emotional exhaustion. Nursing staff’s confidence in management was the second highest predictor for feelings of burnout whereas management who listens to employees was the second highest predictor for emotional exhaustion.

CONCLUSIONS: Supervised machine learning models can accurately predict self-reported feelings of burnout or emotional exhaustion among nurses in South Africa from full survey data but not from demographic data alone. The models identified fatigue rating, confidence in management and management who listens to employees as the most important factors to address to prevent these issues among nurses in South Africa.

PMID:39736726 | DOI:10.1186/s12913-024-12184-5

BMC Nurs. 2024 Dec 30;23(1):958. doi: 10.1186/s12912-024-02629-x.

ABSTRACT

BACKGROUND: Stroke is considered one of the leading causes of both mortality and morbidity on a global scale. The significant impact on the health and quality of life of stroke survivors and their caregivers is well-acknowledged due to the stressful consequences of dependency and the need for home care. This study aims to examine the impact of online training utilizing a stroke educational program on the patient’s quality of life and their caregivers’ care burden.

MATERIALS AND METHODS: From March to August 2024, a randomized, controlled trial was conducted. In this study, a total of 60 dyads consisting of stroke patients and their caregivers participated. Participants were selected by convenient sampling method and then randomly allocated into intervention and control groups using research randomizer software. The participants in the intervention group received the educational content through the WhatsApp application during a series of fifteen sessions, each lasting between 45 and 60 min. The control group was given standard hospital education. The data collection and analysis process entailed the utilization of questionnaires, which encompassed demographics, the Stroke Specific Quality of Life Scale (SS-QOL), and the Zarit burden of care questionnaires.

RESULTS: In the intervention group, the average age of patients and caregivers was 60.23 ± 12.41 and 51.56 ± 10.42, respectively, while in the control group, it was 61.73 ± 12.61 and 53.60 ± 9.03, respectively. The intervention group demonstrated a statistically significant difference in the mean score of patient’s quality of life, comparing the baseline with the post-intervention periods (134.73 ± 33.51 vs. 90.56 ± 6.51 and 130.46 ± 30.67 vs. 90.56 ± 6.51; p < 0.05). Furthermore, a statistically significant difference in the mean score of caregiver’s care burden was noted between the baseline and post-intervention periods (80.23 ± 7.99 vs. 65.43 ± 16.52 and 80.23 ± 7.99 vs. 60.53 ± 21.34; p < 0.05).

CONCLUSION: The implementation of an online training program focused on stroke education, resulted in an improvement in the quality of life for stroke patients, as well as a reduction in the care burden for their caregivers. As a result, it is essential to provide education to patients and their caregivers to improve patient care and minimize stroke complications.

TRIAL REGISTRATION: IRCT20240609062065N1, 2024/08/31.

PMID:39736718 | DOI:10.1186/s12912-024-02629-x

J Neuroeng Rehabil. 2024 Dec 30;21(1):232. doi: 10.1186/s12984-024-01540-5.

ABSTRACT

INTRODUCTION: Neck pain affects 203 million people globally and is prevalent in various settings due to factors like poor posture, lack of exercise, and occupational hazards. Therefore, addressing ergonomic issues with solutions like a wearable robotic device is crucial. This research presents a novel assistive exosuit, characterized by its slim and lightweight structure and intuitive control without the use of hands, designed to mitigate muscle fatigue in the neck and shoulders during prolonged flexed neck posture. The efficacy of the exosuit was confirmed through human experiments and user surveys.

METHODS: The preliminary feasibility experiment was conducted with five subjects for 15 min to verify the effect of supporting the weight of the head with a wire on reducing neck muscle fatigue. The prime experiment was conducted with 26 subjects for 15 min to quantitatively evaluate the reduction in muscle fatigue achieved by wearing the exosuit and to assess its qualitative usability from the user’s perspective. For all experiments, surface electromyography (sEMG) data was measured from upper trapezius (UT) and splenius capitis (SC) muscles, the two representative superficial muscles responsible for sustaining flexed neck posture. The analysis of the device’s efficiency utilized two parameters: the normalized root mean square value (nRMS), which was employed to assess muscle activity, and the normalized median frequency (nMDF), which was utilized to gauge the extent of muscle fatigue. These parameters were statistically analyzed with the IBM SPSS statistic program.

RESULTS: When wearing the exosuit, the nMDF of UT and SC increased by 7.18% (p < 0.05) and 5.38% (p < 0.05), respectively. For the nRMS, no significant differences were observed in either muscle. The nMDF slope of UT and SC increased by 0.63%/min (p < 0.01) and 0.34%/min (no significance). In the context of the nRMS slope, UT exhibited a reduction of 0.021% MVC/min (p < 0.05), while SC did not demonstrate any statistically significant outcomes. The exosuit received an average system usability scale score of 66.83.

CONCLUSIONS: Based on both qualitative and quantitative evaluations, our proposed assistive exosuit demonstrated that it promises the significant reduction of muscle fatigue in the neck and shoulders.

PMID:39736717 | DOI:10.1186/s12984-024-01540-5

World J Surg Oncol. 2024 Dec 31;22(1):354. doi: 10.1186/s12957-024-03649-2.

ABSTRACT

OBJECTIVE: Postoperative venous thromboembolism (VTE) is a potentially life-threatening complication. This study aimed to develop a predictive model to identify independent risk factors and estimate the likelihood of VTE in patients undergoing surgery for cervical cancer.

METHODS: We conducted a retrospective cohort study involving 1,174 patients who underwent surgery for cervical carcinoma between 2019 and 2022. The cohort was randomly divided into training and validation sets at 7:3. Univariate and multivariate logistic regression analyses were used to determine the independent factors associated with VTE. The results of the multivariate logistic regression were used to construct a nomogram. The nomogram’s performance was assessed via the concordance index (C-index) and calibration curve. Additionally, its clinical utility was assessed through decision curve analysis (DCA).

RESULTS: The predictive nomogram model included factors such as age, pathology type, FIGO stage, history of chemotherapy, the neutrophil-lymphocyte ratio (NLR), fibrinogen degradation products (FDP), and D-dimer levels. The model demonstrated robust discriminative power, achieving a C-index of 0.854 (95% CI: 0.799-0.909) in the training cohort and 0.757 (95% CI: 0.657-0.857) in the validation cohort. Furthermore, the nomogram showed excellent calibration and clinical utility, as evidenced by the calibration curve and decision curve analysis (DCA) results.

CONCLUSIONS: We developed a high-performance nomogram that accurately predicts the risk of VTE in cervical cancer patients undergoing surgery, providing valuable guidance for thromboprophylaxis decision-making.

PMID:39736708 | DOI:10.1186/s12957-024-03649-2

Parasit Vectors. 2024 Dec 30;17(1):548. doi: 10.1186/s13071-024-06629-3.

ABSTRACT

BACKGROUND: The frequent communication between African and Southeast Asian (SEA) countries has led to the risk of imported malaria cases in the China-Myanmar border (CMB) region. Therefore, tracing the origins of new malaria infections is important in the maintenance of malaria-free zones in this border region. A new genotyping tool based on a robust mitochondrial (mt) /apicoplast (apico) barcode was developed to estimate genetic diversity and infer the evolutionary history of Plasmodium falciparum across the major distribution ranges. However, the mt/apico genomes of P. falciparum isolates from the CMB region to date are poorly characterized, even though this region is highly endemic to P. falciparum malaria.

METHODS: We have sequenced the whole mt/apico genome of 34 CMB field isolates and utilized a published data set of 147 mt/apico genome sequences to present global genetic diversity and to revisit the evolutionary history of the CMB P. falciparum.

RESULTS: Genetic differentiation based on mt/apico genome of P. falciparum revealed that the CMB (Lazan, Myanmar) isolates presented high genetic diversity with several characteristics of ancestral populations and shared many of the genetic features with West Thailand (Mae Sot; WTH) and to some extent West African (Banjul, Gambia; Navrongo, Ghana; WAF) isolates. The reconstructed haplotype network displayed that the CMB and WTH P. falciparum isolates have the highest representation (five) in the five ancestral (central) haplotypes (H1, H2, H4, H7, and H8), which are comparatively older than isolates from other SEA populations as well as the WAF populations. In addition, the highest estimate of the time to the Most Recent Common Ancestor (TMRCA) of 42,400 (95% CI 18,300-82100) years ago was presented by the CMB P. falciparum compared to the other regional populations. The statistically significant negative values of Fu’s Fs with unimodal distribution in pairwise mismatch distribution curves indicate past demographic expansions in CMB P. falciparum with slow population expansion between approximately 12,500-20,000 ybp.

CONCLUSIONS: The results on the complete mt/apico genome sequence analysis of the CMB P. falciparum indicated high genetic diversity with ancient population expansion and TMRCA, and it seems probable that P. falciparum might have existed in CMB, WTH, and WAF for a long time before being introduced into other Southeast Asian countries or regions. To reduce the impact of sample size or geographic bias on the estimate of the evolutionary timeline, future studies need to expand the range of sample collection and ensure the representativeness of samples across geographic distributions. Additionally, by mapping global patterns of mt/apico genome polymorphism, we will gain valuable insights into the evolutionary history of P. falciparum and optimised strategies for controlling P. falciparum malaria at international borders.

PMID:39736695 | DOI:10.1186/s13071-024-06629-3

BMC Med Educ. 2024 Dec 30;24(1):1553. doi: 10.1186/s12909-024-06573-x.

ABSTRACT

BACKGROUND: Historically, women have been shown to underestimate their abilities, while men often assess themselves more accurately or overestimate. This study aims to determine self-assessment accuracy during online Objective Structured Clinical Examinations (OSCEs) according to gender.

METHODS: A prospective study was conducted among fourth-year medical students at Paris Cité University during faculty training OSCEs, utilizing Zoom® software for remote participation. Students and evaluators assessed performances using 5-point Likert scales for medical knowledge, interpersonal skills, and overall performance. Additionally, students predicted their grade out of twenty. The assessment covered three independent stations.

RESULTS: This study included 259 medical students (177 women, 81 men, one non-binary (excluded from further analyses)) evaluated by 130 physicians. Evaluator scores did not differ according to students’ gender (total score out of 20: men: 10.25 ± 3.45, women: 10.23 ± 3.44 p = 0.817) nor students’ self-assessments (total score out of 20: men: 11.22 ± 3.02, women: 11.00 ± 3.03; p = 0.466) whatever the domains and stations (all p > 0.05). The difference (delta) between self-assessment and evaluator scores for medical knowledge (men: 0.73 ± 1.00, women: 0.64 ± 1.02; p = 0.296), interpersonal skills (men: 1.02 ± 1.06, women: 0.93 ± 1.09; p = 0.296), and total score (men: 0.98 ± 3.41, women: 0.68 ± 3.42; p = 0.296) showed no gender differences. Further analysis categorized students based on their self-assessment accuracy, revealing that both men and women displayed a high ratio of accurate self-assessments (78.1% for overall performance across all stations), with minimal overestimation observed in both genders (20.9% for overall performance across all stations). Instances of overestimation or underestimation were rare and not consistent over the 3 stations, indicating that such misjudgments are likely situational rather than inherent traits.

DISCUSSION: This study reveals similar self-assessment accuracy according to gender in online training OSCEs suggesting a shift towards gender-equitable self-perceptions among medical students compared to previous studies. Research remains necessary to corroborate these results and explore the underlying factors contributing to this shift in self-perception.

PMID:39736694 | DOI:10.1186/s12909-024-06573-x

Lipids Health Dis. 2024 Dec 31;23(1):427. doi: 10.1186/s12944-024-02415-3.

ABSTRACT

BACKGROUND: With metabolic disorders on the rise globally, the cardiometabolic index (CMI) has emerged as a crucial predictor of mortality risks linked to cancer, cardiovascular disease, and diabetes. This novel index, which combines lipid metabolism and body composition, is the focus of this study, aimed at exploring its association with all-cause and specific mortality in an all-age adult population.

METHODS: A longitudinal cohort study including 5,728 participants aged over 18 from nine cycles between 2001 and 2018 was enrolled and assessed. CMI served as the exposure variable, while outcomes included all-cause mortality and mortality due to cardiovascular disease, cancer, and diabetes. The Cox frailty model and average marginal effects were employed to evaluate the contribution of CMI to all-cause and specific mortality collectively. Restricted cubic spline analyses and stratified analyses were conducted to investigate potential nonlinear effects and interactions.

RESULTS: The decreased participants exhibited considerably higher CMI than the alive’s. A positive association was found between CMI and all-cause mortality (HR=1.05, 95% CI=1.01-1.10). Notably, CMI was linked to an increased risk of cancer mortality (HR=1.02) and a reduced risk of cardiovascular disease mortality (HR=0.85). Furthermore, the average marginal effect of CMI on diabetes mortality was the largest (AME=0.499). The RCS curves revealed that participants had the lowest risk of all-cause mortality at a CMI of 0.618. Sensitivity analyses further supported these findings.

CONCLUSION: This study represents the first comprehensive assessment on the contribution of CMI to mortality across an all-age adult population, providing some insights for the comprehensive assessment of health and disease states.

PMID:39736689 | DOI:10.1186/s12944-024-02415-3

BMC Musculoskelet Disord. 2024 Dec 30;25(1):1093. doi: 10.1186/s12891-024-08233-z.

ABSTRACT

BACKGROUND: This study aims to evaluate the optimal dose of intravenous tranexamic acid (TXA) for reducing blood loss in spinal surgery.

METHODS: A systematic search was conducted in the PubMed, Embase, Cochrane Library database from inception until November 2023. Randomized controlled trials (RCTs) incorporating diverse TXA dosing regimens for spinal surgery were included. The surface under the cumulative ranking curve (SUCRA) analysis was employed to determine ranking order. R software with gemtc package was used for all analyses, with a significance threshold set at P < 0.05.

RESULTS: Twenty-four RCTs were considered eligible and finally included. All TXA treatments demonstrated superior efficacy compared to the placebo, with statistically significant differences (P < 0.05). SUCRA values indicated that Treatment I (100 mg/kg + 10 mg.kg/h) claimed the top rank (SUCRA, 80.3%), followed by Treatment F (15 mg/kg + 2 mg.kg/h) in second place (SUCRA, 76.7%), and Treatment E (10 mg/kg + 2 mg.kg/h) in third place (SUCRA, 75.2%). Conversely, the placebo ranked the lowest (SUCRA, 0.3%). Additionally, Treatment I (100 mg/kg + 10 mg.kg/h) held the top rank (SUCRA, 95.6%), followed by Treatment N (30 mg/kg + 10 mg.kg/h) in second place (SUCRA, 81.0%), and Treatment K (15 mg/kg + 6 mg.kg/h) in third place (SUCRA, 74.8%). Importantly, no statistically significant differences were observed between any TXA treatments and the placebo concerning the occurrence of deep vein thrombosis (DVT) (P > 0.05).

CONCLUSIONS: This network meta-analysis underscores that intravenous TXA is associated with decreased overall blood loss in multilevel spine surgery. Notably, the highest dose in this network meta-analysis (100 mg/kg + 10 mg.kg/h) emerged as the only regimen demonstrating significant benefits in pairwise comparisons with other TXA doses. Although this regimen did not significantly increase DVT risk, careful consideration of safety data for higher doses remains essential.

PMID:39736682 | DOI:10.1186/s12891-024-08233-z

Trials. 2024 Dec 30;25(1):855. doi: 10.1186/s13063-024-08669-7.

ABSTRACT

BACKGROUND: We previously published the protocol and statistical analysis plan for a randomized controlled trial of Proportional Assist Ventilation for Minimizing the Duration of Mechanical Ventilation: the PROMIZING study in Trials ( https://doi.org/10.1186/s13063-023-07163-w ). This update summarizes changes made to the statistical analysis plan for the trial since the publication of the original protocol and statistical analysis plan.

METHODS/DESIGN: The Proportional Assist Ventilation for Minimizing the Duration of Mechanical Ventilation (PROMIZING) study is a multi-center, open-label, randomized controlled trial designed to determine if ventilation with proportional assist ventilation with load-adjustable gain factors will result in a shorter duration of time spent on mechanical ventilation compared to ventilation with pressure support ventilation for patients with acute respiratory failure. The statistical analysis plan for the trial was incorporated into the original publication of the protocol in Trials ( https://doi.org/10.1186/s13063-023-07163-w ) and was based on version 5.0 of the study protocol and version 1.0 of the statistical analysis plan (SAP), which included plans for both frequentist and Bayesian analyses. We have since updated the SAP to refine the Bayesian analysis plan, update the multistate model diagram, and include plans for a cluster analysis to determine if there is heterogeneity of treatment effect. This update summarizes the changes made and their rationale and provides a refined SAP for the PROMIZING trial with additional background information, in adherence with guidelines for the prospective reporting of SAPs for randomized controlled trials.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02447692 prospectively registered May 19, 2015.

PMID:39736673 | DOI:10.1186/s13063-024-08669-7