Tag: pubmed

Diabet Med. 2023 Sep 3:e15219. doi: 10.1111/dme.15219. Online ahead of print.

ABSTRACT

AIM: To better understand the prevalence of self-reported psychosocial burdens and the unmet needs identified by people with diabetes in relation to routine diabetes visits.

METHODS: An English language, online survey was distributed via social media, key stakeholder networks, charity and advocacy groups to adults with type 1 diabetes or type 2 diabetes. Survey items were designed by members of the FDA RESCUE Collaborative Community Governing Committee prior to pilot testing with potential participants. Descriptive statistical analyses were conducted; as well as thematic analyses on free text responses using NVivo v14.

RESULTS: 478 participants completed the survey. 373 (78%) had type 1 diabetes, 346 (73%) identified as a woman and 433 (91%) were white. Most participants had experienced self-reported (rather than diagnosed) anxiety and depression (n=323 and n=313 respectively), as well as fear of low blood sugars (n=294), low mood (n=290) and diabetes-related distress (n=257). 68% reported diabetes had negatively affected self-esteem and 62% to feelings of loneliness but 93% reported friends/family/work colleagues were supportive when needed. 272 (57%) reported their diabetes team had never raised the topic of mental health. The overwhelming majority stated the best thing their diabetes team could do to help was to simply ask about mental well-being; listen with empathy and without judgement; and practice skills to understand psychosocial issues in diabetes.

CONCLUSION: Integrating psychosocial discussions and support within routine healthcare visits is crucial to improve outcomes for people with diabetes. Such a biopsychosocial model of healthcare has long been advocated by regulatory bodies.

PMID:37660355 | DOI:10.1111/dme.15219

Orv Hetil. 2023 Sep 3;164(35):1367-1372. doi: 10.1556/650.2023.32854. Print 2023 Sep 3.

ABSTRACT

INTRODUCTION: The COVID-19 pandemic influenced not only the elective, but the acute surgeries also, all around the world. Some authors found more delayed cases and more orchiectomies performed in childhood because of testicular torsions during the pandemic.

OBJECTIVE: To examine the impact of the COVID-19 pandemic on the treatment of childhood testicular torsion and the frequency of semicastration due to torsion at the first author’s institute.

METHODS: A retrospective observational cohort study was performed in a representative Hungarian centre. Boys under 18 years of age operated with testicular torsion were divided into two groups: before COVID-19 (BC; 01/07/2017-31/12/2019) and during COVID-19 (DC; 01/01/2020-30/06/2022) pandemic.

PARAMETERS: elapsed time between the first symptom and arrival at the hospital (<24 h or >24 h), elapsed time to start the surgical procedure since the arrival to the hospital and the rate of semicastration were analysed. For statistical analysis, Mann-Whitney U and chi2 tests were used.

RESULTS: During the study period, altogether, 100 patients (45 BC and 55 DC) were operated on testicular torsion. Statistically significant difference was found between the two timeframes: in the elapsed time from the first symptom and arrival at the hospital (p = 0.048). During the pandemic surgeries started earlier (1.5; 2.5 h) than before the pandemic (1.5; 3.25 h, p = 0.01). No difference was found in the frequency of semicastration between the groups (p = 0.594).

DISCUSSION: Contrary to the literature, during the COVID-19 pandemic, patients with testicular torsion arrived earlier at the hospital, and surgeries were started earlier, than before the pandemic at the investigated institute.

CONCLUSION: The reason behind this accelerated care pathway might be the absence of less severe cases during the COVID-19 period. When people are more prone to stay home, if it does not seem necessary to seek help for any kind of non-urgent medical problem. Orv Hetil. 2023; 164(35): 1367-1372.

PMID:37660346 | DOI:10.1556/650.2023.32854

Biostatistics. 2023 Aug 31:kxad022. doi: 10.1093/biostatistics/kxad022. Online ahead of print.

ABSTRACT

Despite growing interest in estimating individualized treatment rules, little attention has been given the binary outcome setting. Estimation is challenging with nonlinear link functions, especially when variable selection is needed. We use a new computational approach to solve a recently proposed doubly robust regularized estimating equation to accomplish this difficult task in a case study of depression treatment. We demonstrate an application of this new approach in combination with a weighted and penalized estimating equation to this challenging binary outcome setting. We demonstrate the double robustness of the method and its effectiveness for variable selection. The work is motivated by and applied to an analysis of treatment for unipolar depression using a population of patients treated at Kaiser Permanente Washington.

PMID:37660312 | DOI:10.1093/biostatistics/kxad022

Biostatistics. 2023 Aug 31:kxad021. doi: 10.1093/biostatistics/kxad021. Online ahead of print.

ABSTRACT

Along with the increasing availability of health data has come the rise of data-driven models to inform decision making and policy. These models have the potential to benefit both patients and health care providers but can also exacerbate health inequities. Existing “algorithmic fairness” methods for measuring and correcting model bias fall short of what is needed for health policy in two key ways. First, methods typically focus on a single grouping along which discrimination may occur rather than considering multiple, intersecting groups. Second, in clinical applications, risk prediction is typically used to guide treatment, creating distinct statistical issues that invalidate most existing techniques. We present novel unfairness metrics that address both challenges. We also develop a complete framework of estimation and inference tools for our metrics, including the unfairness value (“u-value”), used to determine the relative extremity of unfairness, and standard errors and confidence intervals employing an alternative to the standard bootstrap. We demonstrate application of our framework to a COVID-19 risk prediction model deployed in a major Midwestern health system.

PMID:37660301 | DOI:10.1093/biostatistics/kxad021

STAR Protoc. 2023 Sep 2;4(3):102541. doi: 10.1016/j.xpro.2023.102541. Online ahead of print.

ABSTRACT

Here, we describe the use of TriNet to predict peptides with anticancer and antimicrobial properties by a tri-fusion neural network. We detail the use of TriNet for both the offline Python script version and the online service, thereby demonstrating its convenience for users. In addition, we provide a detailed explanation of the training process of TriNet to enhance the understanding of researchers seeking to leverage deep learning techniques for peptide classification. For complete details on the use and execution of this protocol, please refer to Zhou et al.¹.

PMID:37660298 | DOI:10.1016/j.xpro.2023.102541

Eur Heart J Qual Care Clin Outcomes. 2023 Sep 2:qcad050. doi: 10.1093/ehjqcco/qcad050. Online ahead of print.

ABSTRACT

AIMS: To conduct a contemporary cost-effectiveness analysis examining the use of implantable cardioverter defibrillators (ICD) for primary prevention in patients with hypertrophic cardiomyopathy (HCM).

METHODS: A discrete-time Markov model was used to determine the cost-effectiveness of different ICD decision-making rules for implantation. Several scenarios were investigated including the reference scenario of implantation rates according to observed real world practice. A 12-year time horizon with an annual cycle length was used. Transition probabilities used in the model were obtained using Bayesian analysis. The study has been reported according to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist.

RESULTS: Using a 5-year SCD risk threshold of 6% was cheaper than current practice and has marginally better total quality adjusted life years (QALYs). This is the most cost-effective of the options considered, with an incremental cost effectiveness ratio of £834 per QALY. Sensitivity analyses highlighted that this decision is largely driven by what health related quality of life (HRQL) is attributed to ICD patients and time horizon.

CONCLUSION: We present a timely new perspective on HCM ICD cost-effectiveness, using methods reflecting real-world practice. While we have shown that a 6% 5-year SCD risk cut-off provides the best cohort stratification to aid ICD decision-making, this will also be influenced by the particular values of costs and HRQL for subgroups or at a local level. The process of explicitly demonstrating the main factors which drive conclusions from such an analysis will help to inform shared decision-making in this complex area for all stakeholders concerned.

PMID:37660245 | DOI:10.1093/ehjqcco/qcad050

Prostate Cancer Prostatic Dis. 2023 Sep 2. doi: 10.1038/s41391-023-00714-x. Online ahead of print.

ABSTRACT

BACKGROUND: This study aimed to evaluate the histopathological concordance rates between prostate biopsies and radical prostatectomy specimens according to the applied biopsy approach (transrectal or transperineal).

METHODS: We studied patients who had been newly diagnosed with clinically significant prostate cancer and who underwent a radical prostatectomy between 2018 and 2022. Patients were included if they underwent a prebiopsy magnetic resonance imaging and if they had not been previously treated for prostate cancer. Histopathological grading on prostate biopsies was compared with that on radical prostatectomy specimens. Univariable and multivariable logistic regression analyses were performed to assess the effect of the applied biopsy approach on histopathological concordance. Additional analyses were performed to assess the effect of the applied biopsy approach on American Urological Association risk group migration, defined as any change in risk group after radical prostatectomy.

RESULTS: In total, 1058 men were studied, of whom 49.3% (522/1058) and 50.7% (536/1058) underwent transrectal and transperineal prostate biopsies, respectively. Histopathological disconcordance was observed in 37.8% (400/1058) of men while American Urological Association risk group migration was observed in 30.2% (320/1058) of men. A transperineal biopsy approach was found to be independently associated with higher histopathological concordance rates (OR 1.33 [95% CI 1.01-1.75], p = 0.04) and less American Urological Association risk group migration (OR 0.70 [95% CI 0.52-0.93], p = 0.01).

CONCLUSIONS: The use of a transperineal biopsy approach improved histopathological concordance rates compared to the use of a transrectal biopsy approach. A transperineal biopsy approach may provide more accurate risk stratification for clinical decision-making. Despite recent improvements, histopathologic concordance remains suboptimal and should be considered before initiating management.

PMID:37660218 | DOI:10.1038/s41391-023-00714-x

Int J Impot Res. 2023 Sep 2. doi: 10.1038/s41443-023-00758-6. Online ahead of print.

ABSTRACT

The prevalence of penile calcification in the population remains uncertain. This retrospective multicenter study aimed to determine the prevalence and characteristics of penile calcification in a large cohort of male patients undergoing non-contrast pelvic tomography. A total of 14 545 scans obtained from 19 participating centers between 2016 and 2022 were retrospectively analyzed within a 3-months period. Eligible scans (n = 12 709) were included in the analysis. Patient age, penile imaging status, presence of calcified plaque, and plaque measurements were recorded. Statistical analysis was performed to assess the relationships between calcified plaque, patient age, plaque characteristics, and plaque location. Among the analyzed scans, 767 (6.04%) patients were found to have at least one calcified plaque. Patients with calcified plaque had a significantly higher median age (64 years (IQR 56-72)) compared to those with normal penile evaluation (49 years (IQR 36-60) (p < 0.001). Of the patients with calcified plaque, 46.4% had only one plaque, while 53.6% had multiple plaques. There was a positive correlation between age and the number of plaques (r = 0.31, p < 0.001). The average dimensions of the calcified plaques were as follows: width: 3.9 ± 5 mm, length: 5.3 ± 5.2 mm, height: 3.5 ± 3.2 mm, with an average plaque area of 29 ± 165 mm² and mean plaque volume of 269 ± 3187 mm³. Plaques were predominantly located in the proximal and mid-penile regions (44.1% and 40.5%, respectively), with 77.7% located on the dorsal side of the penis. The hardness level of plaques, assessed by Hounsfield units, median of 362 (IQR 250-487) (range: 100-1400). Patients with multiple plaques had significantly higher Hounsfield unit values compared to those with a single plaque (p = 0.003). Our study revealed that patients with calcified plaques are older and have multiple plaques predominantly located on the dorsal and proximal side of the penis.

PMID:37660216 | DOI:10.1038/s41443-023-00758-6

Sci Rep. 2023 Sep 2;13(1):14441. doi: 10.1038/s41598-023-41093-6.

ABSTRACT

Customer churn remains a critical challenge in telecommunications, necessitating effective churn prediction (CP) methodologies. This paper introduces the Enhanced Gradient Boosting Model (EGBM), which uses a Support Vector Machine with a Radial Basis Function kernel (SVM_RBF) as a base learner and exponential loss function to enhance the learning process of the GBM. The novel base learner significantly improves the initial classification performance of the traditional GBM and achieves enhanced performance in CP-EGBM after multiple boosting stages by utilizing state-of-the-art decision tree learners. Further, a modified version of Particle Swarm Optimization (PSO) using the consumption operator of the Artificial Ecosystem Optimization (AEO) method to prevent premature convergence of the PSO in the local optima is developed to tune the hyper-parameters of the CP-EGBM effectively. Seven open-source CP datasets are used to evaluate the performance of the developed CP-EGBM model using several quantitative evaluation metrics. The results showed that the CP-EGBM is significantly better than GBM and SVM models. Results are statistically validated using the Friedman ranking test. The proposed CP-EGBM is also compared with recently reported models in the literature. Comparative analysis with state-of-the-art models showcases CP-EGBM’s promising improvements, making it a robust and effective solution for churn prediction in the telecommunications industry.

PMID:37660198 | DOI:10.1038/s41598-023-41093-6

Sci Rep. 2023 Sep 2;13(1):14409. doi: 10.1038/s41598-023-41751-9.

ABSTRACT

The flame of converter mouth can well reflect the change of temperature and composition of molten steel in the furnace. The flame characteristics of converter mouth collected by device can well predict the smelting process of converter. Based on the flame spectrum data set of converter mouth, this paper uses the BEADS algorithm and rough set attribute reduction algorithm optimized by genetic algorithm to extract the features of 2048-dimensional wavelength data. Through the model, eight indexes that contribute greatly to temperature and carbon content are selected, which are f-507, f-520, f-839, f-1073, f-1371, f-1528, f-1727 and f-1826. The MIC coefficients of the eight indicators with temperature and carbon content are calculated, and the MIC coefficients of the variables is small, and the selected indicators are representative. There was a significant correlation between temperature and C content. In BP neural network of temperature prediction model, it is found that the prediction accuracy of the training set is 0.99, the prediction accuracy of the test set is 0.99, the prediction accuracy of the verification set is 0.99, and the prediction accuracy of the whole set is 0.99. Through statistics, it is found that the hit rate of the temperature model in the range of ± 5 K is 88.7%, and the hit rate in the range of ± 10 K is 98.4%. and the RMSE parameter analysis shows that the average prediction error is 3.85 K. In BP neural network of carbon content prediction model, it is found that the prediction accuracy of the training set is 0.99, the prediction accuracy of the test set is 0.99, the prediction accuracy of the verification set is 0.98, and the prediction accuracy of the whole set is 0.99. Through statistics, it is found that the hit rate of the carbon contents model in the range of ± 0.05% is 94.0%, and the hit rate in the range of ± 0.10% is 98.3%, and the RMSE parameter analysis shows that the average prediction error is 0.021%. Finally, the universality of the model is verified by MIV algorithm.

PMID:37660162 | DOI:10.1038/s41598-023-41751-9