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Nevin Manimala Statistics

Construction of physical activity promoting indicators system for older adults with subjective cognitive decline using Delphi method

BMC Public Health. 2024 Nov 18;24(1):3206. doi: 10.1186/s12889-024-20762-9.

ABSTRACT

BACKGROUND: For older adults with subjective cognitive decline (SCD), physical activity is now recognized as an effective means to reduce the risk of Alzheimer’s disease. However, this population often exhibits lower levels of physical activity. This study aimed to establish physical activity promoting indicators system for older adults with SCD, providing comprehensive targets for interventions and promoting relevant policies.

METHOD: A modified Delphi technique was used to seek opinions from experts about what should be used and prioritised as indicators of promoting physical activity in older adults with SCD. Expert consultations were conducted from January to March 2024. Data were analyzed using SPSS 27.0 and Excel software. Descriptive statistics were used for expert demographics, while coefficients were calculated to assess expert authority (Cr), and coordination (Kendall’s W). Weights for indicators were determined through the order diagram.

RESULTS: Based on a literature review and the Wuli-Shili-Renli system framework, we initially identified 59 indicators, comprising primary (3 dimensions), secondary (11 items), and tertiary (45 items) indicators. Fifteen expert panelists were invited to participate in the study. Of these, 11 out of 18 completed round 1 (61.1% response rate), all 11 completed round 2 (100.0% response rate), and all 11 completed the third and final round (100.0% response rate). Ultimately, consensus was reached on 3 primary, 9 secondary, and 44 tertiary indicators. The order diagram determined weights for primary indicators as follows: foundational system (0.4242), operational system (0.2879), and personnel system (0.2879).

CONCLUSION: The system of 56 physical activity-promoting indicators constructed for older adults with SCD through the Delphi method provides theoretical support for policy formulation and allocation of funds to comprehensively promote physical activity behaviors among this population.

PMID:39558309 | DOI:10.1186/s12889-024-20762-9

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Construction and SHAP interpretability analysis of a risk prediction model for feeding intolerance in preterm newborns based on machine learning

BMC Med Inform Decis Mak. 2024 Nov 18;24(1):342. doi: 10.1186/s12911-024-02751-5.

ABSTRACT

OBJECTIVE: To construct a highly accurate and interpretable feeding intolerance (FI) risk prediction model for preterm newborns based on machine learning (ML) to assist medical staff in clinical diagnosis.

METHODS: In this study, a sample of 350 hospitalized preterm newborns were retrospectively analysed. First, dual feature selection was conducted to identify important feature variables for model construction. Second, ML models were constructed based on the logistic regression (LR), decision tree (DT), support vector machine (SVM) and eXtreme Gradient Boosting (XGBoost) algorithms, after which random sampling and tenfold cross-validation were separately used to evaluate and compare these models and identify the optimal model. Finally, we apply the SHapley Additive exPlanation (SHAP) interpretable framework to analyse the decision-making principles of the optimal model and expound upon the important factors affecting FI in preterm newborns and their modes of action.

RESULTS: The accuracy of XGBoost was 87.62%, and the area under the curve (AUC) was 92.2%. After the application of tenfold cross-validation, the accuracy was 83.43%, and the AUC was 89.45%, which was significantly better than those of the other models. Analysis of the XGBoost model with the SHAP interpretable framework showed that a history of resuscitation, use of probiotics, milk opening time, interval between two stools and gestational age were the main factors affecting the occurrence of FI in preterm newborns, yielding importance scores of 0.632, 0.407, 0.313, 0.313, and 0.258, respectively. A history of resuscitation, first milk opening time ≥ 24 h and interval between stools ≥ 3 days were risk factors for FI, while the use of probiotics and gestational age ≥ 34 weeks were protective factors against FI in preterm newborns.

CONCLUSIONS: In practice, we should improve perinatal care and obstetrics with the aim of reducing the occurrence of hypoxia and preterm delivery. When feeding, early milk opening, the use of probiotics, the stimulation of defecation and other measures should be implemented with the aim of reducing the occurrence of FI.

PMID:39558307 | DOI:10.1186/s12911-024-02751-5

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Analysis of the efficacy of Endobutton plate combined with high-strength suture Nice knot fixation in the treatment of distal clavicle fractures with coracoclavicular ligament injuries

BMC Musculoskelet Disord. 2024 Nov 19;25(1):927. doi: 10.1186/s12891-024-08044-2.

ABSTRACT

OBJECTIVE: To investigate the efficacy of Endobutton plate combined with high-strength suture Nice knot fixation in the treatment of distal clavicular fractures with coracoclavicular ligament injuries.

METHODS: A retrospective analysis was performed on 43 patients who sustained distal clavicular fractures along with injuries to the coracoclavicular ligament. These patients were treated between January 2017 and December 2023. The fractures were classified according to the fixation method: high-strength Nice knot suture fixation (experimental group, n = 23) and acromioclavicular Kirschner wire fixation (control group, n = 20). The basic information of the two groups of patients, including age, gender, cause of injury, fracture classification, hospitalization duration, fracture healing time and complications, was collected and analyzed. The increase rate of coracoclavicular space on the affected side was collected and analyzed. The pain level of the affected shoulder was assessed using the visual analog scale (VAS). The shoulder joint function was assessed using the American Shoulder and Elbow Surgeons (ASES) scores and Constant-Murley scores before and after surgery.

RESULTS: No significant differences were observed in the general demographic data, including age, gender, injury etiology, Craig classification, and hospitalization duration between the two groups (p > 0.05). Both groups were followed for a period ranging from 12 to 33 months, with an average follow-up of 20.53 ± 5.16 months. The bone healing time in the experimental group was significantly shorter than in the control group (12.82 ± 1.12 weeks vs. 17.25 ± 1.71 weeks, p < 0.05). At the final follow-up, The increase rate of coracoclavicular space was (9.25 ± 2.53) % in the experimental group and (8.10 ± 2.53) % in the control group, which was not significantly different (p > 0.05). Both groups demonstrated significant improvements in VAS scores, Constant-Murley scores, and ASES scores post-operatively compared to pre-operative values (p < 0.05). One month after surgery, the Constant-Murley and ASES scores were significantly superior in the experimental group compared to the control group (p < 0.05). However, no statistical difference was observed three months post-surgery or during the final follow-up (p > 0.05). The control group reported one case of infection related to the Kirschner wire and one case of Kirschner wire displacement postoperatively. Conversely, no significant complications were reported in the experimental group.

CONCLUSION: In the management of distal clavicle fractures accompanied by coracoclavicular ligament injuries, particularly oblique fractures or those with butterfly-shaped fragments, the application of a high-strength Nice knot suture in conjunction with Endobutton plate fixation can effectively stabilize the fracture site. This approach not only mitigates complications associated with Kirschner wire fixation but also enhances fracture healing, leading to favorable postoperative outcomes.

PMID:39558301 | DOI:10.1186/s12891-024-08044-2

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Prevalence of dual use of combustible tobacco and E-cigarettes among pregnant smokers: a systematic review and meta-analysis

BMC Public Health. 2024 Nov 18;24(1):3200. doi: 10.1186/s12889-024-20746-9.

ABSTRACT

BACKGROUND: As e-cigarettes gain popularity as potential tobacco cessation aids, concerns arise about their dual use with traditional cigarettes, especially among pregnant women, potentially subjecting both women and fetuses to heightened risks. This systematic review and meta-analysis aimed to determine the overall prevalence of dual use of tobacco smoking and e-cigarette use in pregnant women.

METHODS: A literature search was conducted across databases including PubMed, Embase, Web of Science, and Cochrane on October 20, 2023. The included studies reported the number of pregnant women and the count of those who were dual users. Quality assessment was undertaken using the JBI tool. The pooled prevalence of dual use was determined via a random-effects model. All statistical analyses were executed using R software, version 4.3.

PROSPERO: CRD42023486020.

RESULTS: Eighteen studies were analyzed, encompassing 5,983,363 pregnant women. The meta-analysis indicated an overall prevalence of 4.6% (95% CI: 2.0-10.3) for dual users with significant heterogeneity (I2 = 100%). Subgroup analysis based on the country showed a prevalence of 4.9% (95% CI: 2.0 to 11.6) for USA and 8.1% (95% CI: 0.00 to 1.00) for UK. Meta-regression revealed reduction of prevalence of dual use from 2019 to 2023. A potential publication bias was indicated by the LFK index and the Doi plot.

CONCLUSION: The dual consumption of e-cigarettes and traditional tobacco in pregnant women is a significant health concern, with a notable prevalence. Given the established risks of tobacco smoking during pregnancy and the uncertainties surrounding e-cigarettes, more comprehensive research and public health interventions are urgently needed to address this issue.

PMID:39558300 | DOI:10.1186/s12889-024-20746-9

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Impact of multidisciplinary team discrepancies on comparative lung cancer outcome analyses and treatment equality

BMC Cancer. 2024 Nov 18;24(1):1423. doi: 10.1186/s12885-024-13188-4.

ABSTRACT

INTRODUCTION: This study aimed to evaluate the consistency of lung cancer case assessments across multidisciplinary team (MDT) sites in Denmark. The goal was to appraise the comparability of outcomes between hospitals in a real-world context.

METHODS: We prepared sixty comprehensive, fictitious lung cancer case stories, complete with images, and distributed them to the four primary lung cancer MDT conferences in Denmark. These cases were subsequently evaluated as had they been ordinary patients during regular MDT meetings. We compared the conclusions on assigned TNM stage and proposed treatment intent using Kappa statistics.

RESULTS: The consensus on assigned stage (Stages IA-B, IIA-B, IIIA-B, IV, and undetermined) corresponded to a Fleiss’ Kappa-value of 0.62 (95% CI: 0.52-0.71). The overall assessment of curability, categorized as Curable, Incurable, and Undetermined, corresponded to a Kappa-value of 0.72 (CI: 0.61-0.84). However, for cases unanimously judged by all MDT sites to be Stage III, the concordance on treatment intent was poor, with an agreement coefficient of only 0.32 (95% CI: -0.27-0.97).

CONCLUSION: In detail, the level of agreement on assigned stages was less than desired. In consequence, comparative analyses of treatment results from different hospitals or centres may be prone to bias caused by systematic differences in stage assessment or intent of treatment. The least consensus was observed for cases in Stage III, indicating a need for quality improvement efforts to ensure a higher degree of consistency in MDT decisions.

PMID:39558297 | DOI:10.1186/s12885-024-13188-4

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A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach

BMC Med Inform Decis Mak. 2024 Nov 18;24(1):344. doi: 10.1186/s12911-024-02753-3.

ABSTRACT

BACKGROUND: Lung cancer is characterized by high morbidity and mortality due to the lack of practical early diagnostic and prognostic tools. The present study uses machine learning algorithms to construct a clinical predictive model for non-small cell lung cancer (NSCLC) patients.

METHODS: Laboratory indices of the NSCLC patients at their initial visit were collected for quality control and exploratory analysis. By comparing the levels of the above indices between the survival and death groups, the statistically significant indices were selected for subsequent machine learning modeling. Ten machine learning algorithms were then employed to develop the predictive models with survival and recurrence as outcomes, respectively. Moreover, regression models were constructed using the random survival forest algorithm by incorporating the survival time dimension. Finally, critical variables in the optimal model were screened based on the interpretable algorithms to build a decision tree to facilitate clinical application.

RESULTS: 682 patients were enrolled according to the inclusion and exclusion criteria. The preliminary comparison results revealed that except for fast blood glucose, CD3+T cell proportion, NK cell proportion, and CA72-4, there were significant statistical differences in other tumor markers, inflammation, metabolism, and immune-related indices between the survival and death groups (p < 0.01). Subsequently, indices with statistical differences were incorporated into machine learning modeling and evaluation. The results showed that among the ten prognostic models constructed using survival status as the outcome, the neural network model obtained the best predictive performance, with accuracy, sensitivity, specificity, AUC, and precision values of 0.993, 0.987, 1.000, 0.994, and 1.000, respectively. The corresponding SHAP16 algorithm revealed that the top five variables in terms of importance were interleukin6 (IL-6), soluble interleukin2 receptor (sIL-2R), cholesterol, CEA, and Cy211, respectively. The random survival forest model also confirmed the critical role of CEA, sIL-2R, and IL-6 in predicting the prognosis of NSCLC patients. A decision tree model with seven cut-off points based on the above three indices was eventually built for clinical application.

CONCLUSION: The neural network model exhibited ideal predictive performance in the survival status of NSCLC patients, and the decision tree model constructed based on selected important variables was conducive to rapid bedside prognosis assessment and decision-making.

PMID:39558294 | DOI:10.1186/s12911-024-02753-3

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Investigating the mechanism of supraspinatus tendinopathy induced by type 2 diabetes mellitus in rats using untargeted metabolomics analysis

BMC Musculoskelet Disord. 2024 Nov 18;25(1):920. doi: 10.1186/s12891-024-08061-1.

ABSTRACT

OBJECTIVE: To assess the mechanism of supraspinatus tendinopathy induced by type 2 diabetes mellitus (T2DM) in rats using untargeted metabolomics analysis.

METHODS: The liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics approach was used to screen tendon biomarkers of supraspinatus tendinopathy in rats with T2DM. Seventy-eight Sprague-Dawley rats were divided into normal group (NG) and T2DM groups. Rats in T2DM groups were divided into 12-week (T2DM-12w), and 24-week (T2DM-24w) subgroups according to the time point of the establishment of the T2DM rat model. Histological evaluation (modified Bonar score) and biomechanical testing were used to analyze the adverse effects of type 2 diabetes on the tendon of the supraspinatus muscle in rats.Three comparable groups were set up, including T2DM-12w group vs. NG, T2DM-24w group vs. NG, and T2DM-24w group vs. T2DM-12w group. Differentially expressed metabolites (DEMs) in the supraspinatus tendons in the three groups of rats were analyzed using LC-MS, and data were analyzed using multivariate statistical methods to screen potential biomarkers. The DEMs included in the intersection of the three groups were identified as those associated with the development of diabetic supraspinatus tendinopathy, and trend analysis and pathway topology analysis were performed.

RESULTS: With the progression of diabetes, the tendinopathy of the supracinatus muscle of diabetic rats gradually intensified, mainly manifested as inflammatory reactions, disordered collagen fibers, fat infiltration, and increased modified Bonar score. The intersection of DEMs among the three comparable groups was resulted in the identification of 10 key DEMs, in which melezitose and raffinose showed a continuous increasing trend with the prolongation of disease course. By pathway topology analysis, 10 DEMs (P < 0.01) were mainly associated with the pathways of galactose metabolism, which could be involved in the development of diabetes-induced supraspinatus tendinopathy.

CONCLUSION: T2DM causes tendinopathy of the supraspinatus muscle in rats. 10 key DEMs obtained by untargeted metabolomics assay suggested that the development of diabetes-induced supraspinatus tendinopathy was associated with changes in metabolic pathways, such as galactose metabolism. melezitose and raffinose hold promise as a biomarker for disease discrimination and/or disease indication in diabetic supraspinatus tendinopathy.

PMID:39558291 | DOI:10.1186/s12891-024-08061-1

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The effectiveness of diabetes training of psychiatric health professionals on individuals with diabetes and psychiatric disorders – a pragmatic controlled trial in Denmark

BMC Med Educ. 2024 Nov 18;24(1):1323. doi: 10.1186/s12909-024-06288-z.

ABSTRACT

BACKGROUND: Individuals with diabetes and co-existing psychiatric disorders have more diabetes complications and lower life expectancy than those with diabetes but no co-existing psychiatric disorders. Psychiatric health professionals may have a role in improving these outcomes but often lack diabetes knowledge and skills. This study aims to examine the effectiveness of a diabetes training course for psychiatric health professionals on their diabetes knowledge and skills and clinical outcomes, diabetes support and diabetes distress among individuals with diabetes and psychiatric disorders treated in psychiatric outpatient clinics.

METHODS: A pragmatic non-randomized controlled cluster trial was conducted in eight psychiatric outpatient clinics in Denmark. All psychiatric health professionals from four clinics participated in the diabetes training course (the intervention) and completed a questionnaire on experience of the training course and a 20-item pre- and post-test to measure diabetes knowledge and skills. Difference in pre- and post-tests were analyzed using t-tests. From August 2018 – June 2019, individuals with diabetes were recruited from the intervention clinics (n = 49) and from four control clinics continuing usual clinical practice (n = 57). Differences in clinical outcomes, diabetes support and diabetes distress between the intervention and control groups at six and 12 months after the training course, were analyzed using logistic and linear regression models adjusted for baseline levels.

RESULTS: Psychiatric health professionals (n = 64) had more correct answers after completing the course, with a mean increase of 6.3 [95% CI 5.6 to 7.0] correct answers. A total of 49 and 57 individuals were recruited for the intervention and control group, respectively. At follow-up, individuals treated in the intervention group had lower levels (clinical improvement) of systolic blood pressure, but had lower receipt of annual assessment of blood pressure, and body mass index (BMI) (worsening of process measures). While there were observed differences in odds and means for several other outcomes, none of these received statistical significance (see Table 2 and Fig. 2).

CONCLUSIONS: Training psychiatric health professionals in diabetes care improved their diabetes knowledge and skills and improved clinical levels of systolic blood pressure in individuals treated in the intervention group. However, this training intervention was associated with a lower likelihood of receiving annual assessment of blood pressure and BMI.

TRIAL REGISTRATION: ISRCTN registry registration number ISRCTN15523920, registration date: 02/10/2019.

PMID:39558289 | DOI:10.1186/s12909-024-06288-z

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Does higher serum 25-hydroxyvitamin D levels will harm bone mineral density?: a cross-sectional study

BMC Endocr Disord. 2024 Nov 18;24(1):250. doi: 10.1186/s12902-024-01760-9.

ABSTRACT

OBJECTIVE: Vitamin D plays a critical role in the prevention and management of osteoporosis. However, there is an ongoing debate regarding the most effective vitamin D supplementation strategies for maintaining optimal bone mineral density (BMD) levels in adults. This study sought to establish the correlation between serum 25-hydroxyvitamin D [25(OH)D] levels and total BMD in a substantial population sample.

METHODS: Data from the National Health and Nutrition Examination Survey (NHANES) for the 2011-2018 cycles, encompassing 11,375 adult participants, were analyzed. The primary variables of interest were serum 25(OH)D levels and BMD. A multivariable logistic regression model was utilized to account for relevant variables associated with these correlations.

RESULTS: A U-shaped relationship between serum 25(OH)D levels and BMD was observed. In males, a significant positive association was identified for 25(OH)D levels below 84.8 nmol/L (p < 0.0001), while levels above this threshold showed no significant correlation (p = 0.3377). In females, those with 25(OH)D levels below 31.4 nmol/L exhibited a significant positive association with BMD (p = 0.0010), but this association weakened and became marginally significant above this threshold (p = 0.0650).

CONCLUSIONS: For adult males, the optimal serum 25(OH)D level is 84.8 nmol/L, beyond which higher levels do not lead to increased BMD. A deficiency threshold for adult females should be above 31.4 nmol/L, as lower 25(OH)D levels are not conducive to BMD. These findings underscore the importance of maintaining appropriate vitamin D levels for bone health in both genders.

PMID:39558288 | DOI:10.1186/s12902-024-01760-9

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BlephEx-treatment for blepharitis: a prospective randomized placebo-controlled trial

BMC Ophthalmol. 2024 Nov 18;24(1):503. doi: 10.1186/s12886-024-03765-3.

ABSTRACT

BACKGROUND: Blepharitis is a chronic inflammatory condition of the eyelids that affects a large proportion of patients in eye care settings. First-line treatments provide only partial relief for many patients. The BlephEx™ device provides automated eyelid debridement and aims to remove pathogenic biofilms from the eyelid margin to treat blepharitis long-term. However, evidence supporting the efficacy of BlephEx™ is limited.

METHODS: In this double-masked randomized controlled trial, 42 patients with symptomatic blepharitis refractory to treatment were assigned to the BlephEx™ treatment or sham treatment group. Outcome measures including Ocular surface disease index (OSDI), tear break-up time (TBUT), Schirmer test, and Efron grading scale scores were assessed at baseline and after 4 weeks. A crossover design in which the treatment groups were swapped after 4 weeks was used as a recruitment tool. After receiving treatment, two patients (one per group) were lost to follow-up.

RESULTS: The sham group exhibited a significant decrease in the Efron Grading Scale score. No significant differences were observed in the other outcomes between the two groups. The BlephEx™ group showed slightly greater decreases in the OSDI and Efron grading scale scores and an increase in the TBUT than did the sham group, but these differences were not statistically significant. Mild discomfort was the most common side effect and occurred equally in both groups.

CONCLUSIONS: No significant difference in outcomes was observed between patients who underwent BlephEx™ therapy and those who received sham treatment. BlephEx™ treatment cannot be recommended for treating blepharitis.

TRIAL REGISTRATION: Retrospectively registered on February 16, 2024 in the DRKS (German Clinical Trials Register under https://drks.de/search/de/trial/DRKS00033492 ) under the trial registration number DRKS00033492.

PMID:39558272 | DOI:10.1186/s12886-024-03765-3