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Public Health Jun 2024To describe the trends in the nature of general practices in Scotland between 2014/15 and 2023.
OBJECTIVES
To describe the trends in the nature of general practices in Scotland between 2014/15 and 2023.
STUDY DESIGN
Descriptive ecological study.
METHODS
We obtained data from Public Health Scotland and used general practitioner (GP) practice codes, practice names, and the General Medical Council (GMC) numbers of their listed GPs to describe trends in practice characteristics and to identify individual practices that were likely to be operating as a single entity.
RESULTS
Defining practice entities is difficult because different GP practice codes are often retained when GPs are performing across multiple practices. If GP practice codes alone are used, the median practice list size increased from 5094 to 5881, and the mean from 5588 to 6289, between 2013/14 and 2020/21. There was one outlier practice that grew to have over 45,000 patients registered by 2020/21. However, this underestimates the extent of this new mega-practice phenomenon. Using the GMC numbers of GPs listed as performers to identify where the same GPs are working across multiple GP practice codes, we identified a series of mega-practices that span across health board areas and which have experienced a dramatic increase in their list size (with the two largest having list sizes of over 101,000 and 77,000 patients, respectively).
CONCLUSIONS
Further research is needed to better understand: how mega-practices provide services and whether this differs from other practices; where financial rewards accumulate within mega-practices; differences in staffing between mega-practices and other models; and the impacts mega-practices have on the quality and continuity of care and on health and inequality outcomes.
PubMed: 38908308
DOI: 10.1016/j.puhe.2024.05.026 -
Aesthetic Plastic Surgery Jun 2024Plastic surgeons increasingly use social media to market their practices and educate prospective patients. Previous studies have investigated plastic surgery content on...
BACKGROUND
Plastic surgeons increasingly use social media to market their practices and educate prospective patients. Previous studies have investigated plastic surgery content on Instagram from the angle of hashtags and most popular plastic surgeons. However, very little is understood about what plastic surgeons themselves post on Instagram and what plastic surgery content average users engage with.
OBJECTIVES
The aim of this study was to analyze Instagram posts from accounts related to plastic surgeons in the USA to establish suggestions for growing one's practice with this powerful platform to reach patients.
METHODS
Board-certified plastic surgeons from all US regions that were active from February 1, 2023 to April 12, 2023 were randomly chosen. Their Instagram accounts were accessed for post analysis. For procedural posts, engagement statistics and multiple variables were collected. Dixon's outlier test was used to determine outliers in the data. ANCOVA and Tukey analysis was used to determine whether procedure type influenced engagement.
RESULTS
120 surgeon accounts were identified with 2157 posts analyzed, yielding notable differences in posts among regions. Most posts were aesthetic procedures (94.4%) and of female patients (90.3%). Surgical procedures were also predominant (86.1%). In addition, Reels had higher engagement than photograph posts. Users engaged with Body procedures at the highest rate.
CONCLUSIONS
This cross-sectional analysis shows plastic surgeons tend to overwhelmingly post female patients, aesthetic procedures, and surgical content. These insights may be used to guide social media content and improve the effectiveness of Instagram as a tool for marketing or education.
LEVEL OF EVIDENCE IV
This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
PubMed: 38907051
DOI: 10.1007/s00266-024-04144-5 -
European Journal of Vascular and... Jun 2024Complex abdominal aortic aneurysms (cAAA) pose a clinical challenge. The aim of this study was to assess the 30 day mortality and morbidity for open aneurysm repair...
OBJECTIVE
Complex abdominal aortic aneurysms (cAAA) pose a clinical challenge. The aim of this study was to assess the 30 day mortality and morbidity for open aneurysm repair (OAR) and fenestrated/branched endovascular aortic repair (F/BEVAR), and the effect of hospital volume in patients with asymptomatic cAAA in Switzerland.
METHODS
Retrospective, cohort study using data from Switzerland's national registry for vascular surgery, Swissvasc, including patients treated from 1 January 2019 to 31 December 2022. All patients with asymptomatic, true, non-infected cAAA were identified. Primary outcome was 30 day mortality and morbidity reported using the Clavien-Dindo classification. Outcomes were compared between OAR and F/BEVAR after propensity score weighting.
RESULTS
Of the 461 patients identified, 333 underwent OAR and 128 underwent F/BEVAR for cAAA. At 30 days, overall mortality rate was 3.3% after OAR and 3.1% after F/BEVAR (p = .76). Propensity scores weighted analysis indicated similar morbidity rates for both approaches: F/BEVAR (OR 0.69, 95% CI 0.45 - 1.05, p = .055); intestinal ischaemia (1.8% after OAR, 3.1% after F/BEVAR, p = .47) and renal failure requiring dialysis (1.5% after OAR, 5.5% after F/BEVAR, p = .024) were associated with highest morbidity and mortality. Treatment specific complications with high morbidity were abdominal compartment syndrome and lower limb compartment syndrome following F/BEVAR. Overall treatment volume was low for most of the hospitals treating cAAA in Switzerland; outliers with increased mortality were identified among low volume hospitals.
CONCLUSION
Comparable 30 day mortality and morbidity rates were found between OAR and F/BEVAR for cAAA in Switzerland; lack of centralisation was also highlighted. Organ specific complications driving mortality were renal failure, intestinal ischaemia, and limb ischaemia, specifically after F/BEVAR. Treatment in specialised high volume centres, alongside efforts to reduce peri procedural kidney injury and mesenteric ischaemia, offers potential to lower morbidity and mortality in elective cAAA treatment.
PubMed: 38906370
DOI: 10.1016/j.ejvs.2024.06.022 -
Computers in Biology and Medicine Jun 2024Traumatic bone marrow lesions (BML) are frequently identified on knee MRI scans in patients following an acute full-thickness, complete ACL tear. BMLs coincide with...
INTRODUCTION
Traumatic bone marrow lesions (BML) are frequently identified on knee MRI scans in patients following an acute full-thickness, complete ACL tear. BMLs coincide with regions of elevated localized bone loss, and studies suggest these may act as a precursor to the development of post-traumatic osteoarthritis. This study addresses the labour-intensive manual assessment of BMLs by using a 3D U-Net for automated identification and segmentation from MRI scans.
METHODS
A multi-task learning approach was used to segment both bone and BML from T2 fat-suppressed (FS) fast spin echo (FSE) MRI sequences for BML assessment. Training and testing utilized datasets from individuals with complete ACL tears, employing a five-fold cross-validation approach and pre-processing involved image intensity normalization and data augmentation. A post-processing algorithm was developed to improve segmentation and remove outliers. Training and testing datasets were acquired from different studies with similar imaging protocol to assess the model's performance robustness across different populations and acquisition conditions.
RESULTS
The 3D U-Net model exhibited effectiveness in semantic segmentation, while post-processing enhanced segmentation accuracy and precision through morphological operations. The trained model with post-processing achieved a Dice similarity coefficient (DSC) of 0.75 ± 0.08 (mean ± std) and a precision of 0.87 ± 0.07 for BML segmentation on testing data. Additionally, the trained model with post-processing achieved a DSC of 0.93 ± 0.02 and a precision of 0.92 ± 0.02 for bone segmentation on testing data. This demonstrates the approach's high accuracy for capturing true positives and effectively minimizing false positives in the identification and segmentation of bone structures.
CONCLUSION
Automated segmentation methods are a valuable tool for clinicians and researchers, streamlining the assessment of BMLs and allowing for longitudinal assessments. This study presents a model with promising clinical efficacy and provides a quantitative approach for bone-related pathology research and diagnostics.
PubMed: 38905892
DOI: 10.1016/j.compbiomed.2024.108791 -
Clinical Imaging Jun 2024Esophageal cancer remains a global challenge due to late diagnoses and limited treatments. Lymph node metastasis (LNM) is crucial for prognosis, yet traditional... (Review)
Review
BACKGROUND
Esophageal cancer remains a global challenge due to late diagnoses and limited treatments. Lymph node metastasis (LNM) is crucial for prognosis, yet traditional diagnostics fall short. Integrating radiomics and deep learning (DL) with CT imaging for LNM diagnosis could revolutionize prognostic assessment and treatment planning.
METHODS
A systematic review and meta-analysis were conducted by searching PubMed, Scopus, Web of Science, and Embase up to October 1, 2023. The focus was on studies developing CT-based radiomics and/or DL models for preoperative LNM detection in esophageal cancer. Methodological quality was assessed using the METhodological RadiomICs Score (METRICS).
RESULTS
Twelve studies were reviewed, and seven were included in the meta-analysis, most showing excellent methodological quality. Training sets revealed a pooled AUC of 87 % (95 % CI: 78 %-90 %), and internal validation sets showed an AUC of 85 % (95 % CI: 76 %-89 %), with no significant difference (p = 0.39). Sensitivity and specificity for training sets were 78.7 % and 81.8 %, respectively, with validation sets at 81.2 % and 76.2 %. DL models in training sets showed better diagnostic accuracy than radiomics (p = 0.054), significant after removing outliers (p < 0.01). Incorporating clinical data improved sensitivity in validation sets (p = 0.029). No significant difference was found between models based on CE or non-CE imaging (p = 0.281) or arterial or venous phase imaging (p = 0.927).
CONCLUSION
Integrating CT-based radiomics and DL improves LNM detection in esophageal cancer. Including clinical data could enhance model performance. Future research should focus on multicenter studies with independent validations to confirm these findings and promote broader clinical adoption.
PubMed: 38905878
DOI: 10.1016/j.clinimag.2024.110225 -
Medicine Jun 2024Maintaining a balanced bile acids (BAs) metabolism is essential for lipid and cholesterol metabolism, as well as fat intake and absorption. The development of obesity...
Maintaining a balanced bile acids (BAs) metabolism is essential for lipid and cholesterol metabolism, as well as fat intake and absorption. The development of obesity may be intricately linked to BAs and their conjugated compounds. Our study aims to assess how BAs influence the obesity indicators by Mendelian randomization (MR) analysis. Instrumental variables of 5 BAs were obtained from public genome-wide association study databases, and 8 genome-wide association studies related to obesity indicators were used as outcomes. Causal inference analysis utilized inverse-variance weighted (IVW), weighted median, and MR-Egger methods. Sensitivity analysis involved MR-PRESSO and leave-one-out techniques to detect pleiotropy and outliers. Horizontal pleiotropy and heterogeneity were assessed using the MR-Egger intercept and Cochran Q statistic, respectively. The IVW analysis revealed an odds ratio of 0.94 (95% confidence interval: 0.88, 1.00; P = .05) for the association between glycolithocholate (GLCA) and obesity, indicating a marginal negative causal association. Consistent direction of the estimates obtained from the weighted median and MR-Egger methods was observed in the analysis of the association between GLCA and obesity. Furthermore, the IVW analysis demonstrated a suggestive association between GLCA and trunk fat percentage, with a beta value of -0.014 (95% confidence interval: -0.027, -0.0004; P = .04). Our findings suggest a potential negative causal relationship between GLCA and both obesity and trunk fat percentage, although no association survived corrections for multiple comparisons. These results indicate a trend towards a possible association between BAs and obesity, emphasizing the need for future studies.
Topics: Mendelian Randomization Analysis; Humans; Obesity; Genome-Wide Association Study; Bile Acids and Salts; Causality
PubMed: 38905395
DOI: 10.1097/MD.0000000000038610 -
Frontiers in Genetics 2024Previous studies have shown that Alzheimer's disease (AD) can cause myocardial damage. However, whether there is a causal association between AD and non-ischemic...
The causal effect of Alzheimer's disease and family history of Alzheimer's disease on non-ischemic cardiomyopathy and left ventricular structure and function: a Mendelian randomization study.
BACKGROUND
Previous studies have shown that Alzheimer's disease (AD) can cause myocardial damage. However, whether there is a causal association between AD and non-ischemic cardiomyopathy (NICM) remains unclear. Using a comprehensive two-sample Mendelian randomization (MR) method, we aimed to determine whether AD and family history of AD (FHAD) affect left ventricular (LV) structure and function and lead to NICM, including hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM).
METHODS
The summary statistics for exposures [AD, paternal history of AD (PH-AD), and maternal history of AD (MH-AD)] and outcomes (NICM, HCM, DCM, and LV traits) were obtained from the large European genome-wide association studies. The causal effects were estimated using inverse variance weighted, MR-Egger, and weighted median methods. Sensitivity analyses were conducted, including Cochran's Q test, MR-Egger intercept test, MR pleiotropy residual sum and outlier, MR Steiger test, leave-one-out analysis, and the funnel plot.
RESULTS
Genetically predicted AD was associated with a lower risk of NICM [odds ratio (OR) 0.9306, 95% confidence interval (CI) 0.8825-0.9813, = 0.0078], DCM (OR 0.8666, 95% CI 0.7752-0.9689, = 0.0119), and LV remodeling index (OR 0.9969, 95% CI 0.9940-0.9998, = 0.0337). Moreover, genetically predicted PH-AD was associated with a decreased risk of NICM (OR 0.8924, 95% CI 0.8332-0.9557, = 0.0011). MH-AD was also strongly associated with a decreased risk of NICM (OR 0.8958, 95% CI 0.8449-0.9498, = 0.0002). Different methods of sensitivity analysis demonstrated the robustness of the results.
CONCLUSION
Our study revealed that AD and FHAD were associated with a decreased risk of NICM, providing a new genetic perspective on the pathogenesis of NICM.
PubMed: 38903751
DOI: 10.3389/fgene.2024.1379865 -
BMC Women's Health Jun 2024Previous observational studies have indicated an inverse correlation between circulating sex hormone binding globulin (SHBG) levels and the incidence of polycystic ovary...
BACKGROUND
Previous observational studies have indicated an inverse correlation between circulating sex hormone binding globulin (SHBG) levels and the incidence of polycystic ovary syndrome (PCOS). Nevertheless, conventional observational studies may be susceptible to bias. Consequently, we conducted a two-sample Mendelian randomization (MR) investigation to delve deeper into the connection between SHBG levels and the risk of PCOS.
METHODS
We employed single-nucleotide polymorphisms (SNPs) linked to serum SHBG levels as instrumental variables (IVs). Genetic associations with PCOS were derived from a meta-analysis of GWAS data. Our primary analytical approach relied on the inverse-variance weighted (IVW) method, complemented by alternative MR techniques, including simple-median, weighted-median, MR-Egger regression, and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) testing. Additionally, sensitivity analyses were conducted to assess the robustness of the association.
RESULTS
We utilized 289 SNPs associated with serum SHBG levels, achieving genome-wide significance, as instrumental variables (IVs). Our MR analyses revealed that genetically predicted elevated circulating SHBG concentrations were linked to a reduced risk of PCOS (odds ratio (OR) = 0.56, 95% confidence interval (CI): 0.39-0.78, P = 8.30 × 10) using the IVW method. MR-Egger regression did not detect any directional pleiotropic effects (P intercept = 0.626). Sensitivity analyses, employing alternative MR methods and IV sets, consistently reaffirmed our results, underscoring the robustness of our findings.
CONCLUSIONS
Through a genetic epidemiological approach, we have substantiated prior observational literature, indicating a potential causal inverse relationship between serum SHBG concentrations and PCOS risk. Nevertheless, further research is needed to elucidate the underlying mechanism of SHBG in the development of PCOS.
Topics: Humans; Sex Hormone-Binding Globulin; Polycystic Ovary Syndrome; Female; Polymorphism, Single Nucleotide; Mendelian Randomization Analysis; Genome-Wide Association Study; Genetic Predisposition to Disease; Risk Factors
PubMed: 38902677
DOI: 10.1186/s12905-024-03144-6 -
Wiener Klinische Wochenschrift Jun 2024To investigate the genetic level causal association among hyperthyroidism, hypothyroidism, and rheumatoid arthritis (RA).
OBJECTIVE
To investigate the genetic level causal association among hyperthyroidism, hypothyroidism, and rheumatoid arthritis (RA).
METHODS
We utilized the genome-wide association studies (GWAS) summary data for exposure (hyperthyroidism and hypothyroidism) and outcome (RA) from the IEU OpenGWAS database. We used two different sets of data (test cohort and validation cohort) for causal assessment of exposure and outcome. To establish a causal relationship between these conditions, we conducted a two-sample Mendelian randomization (MR) analysis. Subsequently, we evaluated the MR analysis results for heterogeneity, horizontal pleiotropy, and outliers, aiming to assess the validity and reliability of the findings. Moreover, we conducted additional analyses to examine the robustness of the MR results, including a "Leave one out" analysis and the MR robust adjusted profile score (MR-RAPS) method, ensuring the robustness and adherence to normal distribution assumptions.
RESULTS
The findings from the test cohort indicated that hyperthyroidism did not exhibit a genetic causal association with RA (P = 0.702, odds ratio [OR] 95% confidence interval [CI] = 1.021 [0.918-1.135]). Conversely, hypothyroidism displayed a positive genetic causal relationship with RA (P < 0.001, OR 95% CI = 1.239 [1.140-1.347]). The analysis results of the validation cohort are consistent with those of the test cohort. Notably, our MR analysis results demonstrated no evidence of heterogeneity, horizontal pleiotropy, or outliers. Furthermore, our MR analysis results remained unaffected by any single nucleotide polymorphism (SNP) and exhibited a normal distribution.
CONCLUSION
The results of this study showed that hypothyroidism was positively correlated with RA, while hyperthyroidism was not causally correlated with RA. Hypothyroidism may as a risk factor of RA should be paid attention to in clinical work. Future studies are needed to further confirm this finding.
PubMed: 38902562
DOI: 10.1007/s00508-024-02386-6 -
Clinical Nutrition ESPEN Aug 2024The emerging role of vitamin D has drawn the attention of researchers around the world, including its involvement in cardiovascular complications among individuals with... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The emerging role of vitamin D has drawn the attention of researchers around the world, including its involvement in cardiovascular complications among individuals with diabetes.
AIM
This study aimed to obtain comprehensive evidence on the association between serum vitamin D level and the risk of cardiovascular disease among patients with diabetes.
METHODS
Systematic search was performed on July 1st, 2023, to identify and screen published literature reporting the association between vitamin D and cardiovascular disease among diabetic patients in six databases. Each eligible study was appraised for its quality using modified Newcastle Ottawa Scale for cross-sectional and cohort studies. Meta-analysis was performed using Dersimonian-Laird random effect model or fix-effect model. The heterogeneity and publication bias were judged based on percentage of I and the symmetry of Begg's funnel plot, respectively.
RESULTS
As many as 22 studies were found eligible for the systematic review. A meta-analysis from 13 studies comprising of 3850 and 1797 (control and exposure groups, respectively) revealed that serum vitamin D level was significantly lower in patients with diabetes and cardiovascular diseases (Z = 4.89; p-total<0.001; SMD = 0.68 [95%CI: 0.41-0.95]), yet the heterogeneity was high. Following the adjustment of removing the potential outliers, the same results were still observed (Z = 6.19; p-total<0.001; SMD = 0.35 [95%CI: 0.24-0.46]). Though decreased, high heterogeneity could not be resolved, resulting in moderate level of this evidence. Another pooled analysis of 7 studies with 4211 patients in control group and 2381 patients in exposure group revealed that lower level of serum vitamin D is a risk factor for cardiovascular disease incidence among diabetic patients (Z = 4.89; p-total<0.001; OR: 1.76 [95%CI: 1.4-2.2]).
CONCLUSION
Serum vitamin D level status is a risk factor for developing cardiovascular diseases among diabetic patients, hence should be carefully monitored and maintained.
PROSPERO REGISTRATION
CRD42023437698.
Topics: Humans; Cardiovascular Diseases; Vitamin D; Risk Factors; Vitamin D Deficiency; Diabetes Mellitus; Cross-Sectional Studies
PubMed: 38901950
DOI: 10.1016/j.clnesp.2024.04.018