Project description:BackgroundCardiovascular disease (CVD) is common among women and is a leading cause of death in the United States. This study assessed the impact of CVD on compliance with the US Preventive Services Task Force guidelines for cervical and breast cancer screening among U.S. adult women.MethodsA cross-sectional study was conducted on 17,408 women using data from the National Health Interview Survey 2013. A total of 11,788 respondents (21-65 years old) with complete information on Pap smear and 11,409 women (40+ years old) with complete information on mammography compliance were included. Multivariate logistic regression models were used to assess the impact of CVD on cervical and breast cancer screening practices.ResultsWomen with CVD were marginally more likely to have had a mammogram in accordance with guidelines (odds ratio 1.17; 95% confidence interval 1.04-1.31) than those without CVD. However, compliance with Pap tests was similar (80.6% vs 82.3%, p>0.05) between the two groups. Myocardial infarction was associated with reduced odds of Pap smear compliance (odds ratio: 0.30; 95% confidence interval 0.18-0.51).ConclusionsWomen with prior myocardial infarction should be encouraged to continue receiving regular Pap smears. More research is needed to assess whether observed differences in Pap testing between patients with and without a history of myocardial infarction result from lack of provider recommendation or from patient noncompliance with their recommendations.
Project description:Formalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data. We optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.. Samples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with TPM > 4). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.9 ng/ul and 2.08 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.82 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.848 in predicting QC status (pass/fail) of FFPE samples. We provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.7 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.
Project description:The purpose of this study was to develop a machine learning model for predicting 30-day readmission after bariatric surgery based on laboratory tests. Data were collected from patients who underwent bariatric surgery between 2018 and 2023. Laboratory test indicators from the preoperative stage, one day postoperatively, and three days postoperatively were analyzed. Least absolute shrinkage and selection operator regression was used to select the most relevant features. Models constructed included support vector machine (SVM), generalized linear model, multi-layer perceptron, random forest, and extreme gradient boosting. Model performance was evaluated and compared using the area under the receiver operating characteristic curve (AUROC). A total of 1262 patients were included, of which 7.69% of cases were readmitted. The SVM model achieved the highest AUROC (0.784; 95% CI 0.696-0.872), outperforming other models. This suggests that machine learning models based on laboratory test data can effectively identify patients at high risk of readmission after bariatric surgery.
Project description:BackgroundNew screening tests for colorectal cancer continue to emerge, but the evidence needed to justify their adoption in screening programs remains uncertain.MethodsA review of the literature and a consensus approach by experts was undertaken to provide practical guidance on how to compare new screening tests with proven screening tests.ResultsFindings and recommendations from the review included the following: Adoption of a new screening test requires evidence of effectiveness relative to a proven comparator test. Clinical accuracy supported by programmatic population evaluation in the screening context on an intention-to-screen basis, including acceptability, is essential. Cancer-specific mortality is not essential as an endpoint provided that the mortality benefit of the comparator has been demonstrated and that the biologic basis of detection is similar. Effectiveness of the guaiac-based fecal occult blood test provides the minimum standard to be achieved by a new test. A 4-phase evaluation is recommended. An initial retrospective evaluation in cancer cases and controls (Phase 1) is followed by a prospective evaluation of performance across the continuum of neoplastic lesions (Phase 2). Phase 3 follows the demonstration of adequate accuracy in these 2 prescreening phases and addresses programmatic outcomes at 1 screening round on an intention-to-screen basis. Phase 4 involves more comprehensive evaluation of ongoing screening over multiple rounds. Key information is provided from the following parameters: the test positivity rate in a screening population, the true-positive and false-positive rates, and the number needed to colonoscope to detect a target lesion.ConclusionsNew screening tests can be evaluated efficiently by this stepwise comparative approach.
Project description:BackgroundAccurate diagnosis is a fundamental aspect of appropriate healthcare. However, clinicians need guidance when implementing diagnostic tests given the number of tests available and resource constraints in healthcare. Practitioners of health often feel compelled to implement recommendations in guidelines, including recommendations about the use of diagnostic tests. However, the understanding about diagnostic tests by guideline panels and the methodology for developing recommendations is far from completely explored. Therefore, we evaluated the factors that guideline developers and users need to consider for the development of implementable recommendations about diagnostic tests.MethodsUsing a critical analysis of the process, we present the results of a case study using the Grading of Recommendations Applicability, Development and Evaluation (GRADE) approach to develop a clinical practice guideline for the diagnosis of Cow Milk Allergy with the World Allergy Organization.ResultsTo ensure that guideline panels can develop informed recommendations about diagnostic tests, it appears that more emphasis needs to be placed on group processes, including question formulation, defining patient-important outcomes for diagnostic tests, and summarizing evidence. Explicit consideration of concepts of diagnosis from evidence-based medicine, such as pre-test probability and treatment threshold, is required to facilitate the work of a guideline panel and to formulate implementable recommendations.DiscussionThis case study provides useful guidance for guideline developers and clinicians about what they ought to demand from clinical practice guidelines to facilitate implementation and strengthen confidence in recommendations about diagnostic tests. Applying a structured framework like the GRADE approach with its requirement for transparency in the description of the evidence and factors that influence recommendations facilitates laying out the process and decision factors that are required for the development, interpretation, and implementation of recommendations about diagnostic tests.
Project description:ObjectiveTo quantify the resource use of revising breast cancer screening guidelines to include average-risk women aged 40-49 years across Canada from 2024 to 2043 using a validated microsimulation model.SettingOncoSim-Breast microsimulation platform was used to simulate the entire Canadian population in 2015-2051.MethodsWe compared resource use between current screening guidelines (biennial screening ages 50-74) and alternate screening scenarios, which included annual and biennial screening for ages 40-49 and ages 45-49, followed by biennial screening ages 50-74. We estimated absolute and relative differences in number of screens, abnormal screening recalls without cancer, total and negative biopsies, screen-detected cancers, stage of diagnosis, and breast cancer deaths averted.ResultsCompared with current guidelines in Canada, the most intensive screening scenario (annual screening ages 40-49) would result in 13.3% increases in the number of screens and abnormal screening recalls without cancer whereas the least intensive scenario (biennial screening ages 45-49) would result in a 3.4% increase in number of screens and 3.8% increase in number of abnormal screening recalls without cancer. More intensive screening would be associated with fewer stage II, III, and IV diagnoses, and more breast cancer deaths averted.ConclusionsRevising breast cancer screening in Canada to include average-risk women aged 40-49 would detect cancers earlier leading to fewer breast cancer deaths. To realize this potential clinical benefit, a considerable increase in screening resources would be required in terms of number of screens and screen follow-ups. Further economic analyses are required to fully understand cost and budget implications.
Project description:PurposeTo verify the accuracy of smartphone apps to identify hearing loss.Research strategiesA systematic review followed the PRISMA-DATA checklist. The search strategies were applied across four databases (Lilacs, PubMed, Scopus and Web of Science) and grey literature (Google Scholar, OpenGrey, and ProQuest Dissertations and Thesis).Selection criteriaThe acronym PIRD was used in review. This included populations of any gender and all age groups. The Index test is the smartphone-based hearing screening test; the Reference test is the pure-tone audiometry, which is considered the gold reference for hearing diagnostics; the diagnosis was performed via validity data (sensitivity and specificity) to identify hearing loss and diagnostic studies.Data analysisTwo reviewers selected the studies in a two-step process. The risk of bias was assessed according to the criteria of the QUADAS-2.ResultsOf 1395 articles, 104 articles were eligible for full-text reading and 17 were included. Only four met all criteria for methodological quality. All of the included studies were published in English between 2015 and 2020. The applications Digits-in noise Test (5 articles), uHear (4 articles), HearScreen (2 articles), hearTest (2 articles) and Hearing Test (2 articles) were the most studied. All this application showed sensitivity and specificity values between 75 and 100%. The other applications were EarScale, uHearing Test, Free field hearing (FFH) and Free Hearing Test.ConclusionuHear, Digit-in-Noise Test, HearTest and HearScreen have shown significant values of sensitivity and specificity and can be considered as the most accurate methods for screening of hearing impairment.
Project description:BackgroundAs basketball match-play requires players to possess a wide range of physical characteristics, many tests have been introduced in the literature to identify talent and quantify fitness in various samples of players. However, a synthesis of the literature to identify the most frequently used tests, outcome variables, and normative values for basketball-related physical characteristics in adult male basketball players is yet to be conducted.ObjectiveThe primary objectives of this systematic review are to (1) identify tests and outcome variables used to assess physical characteristics in adult male basketball players across all competition levels, (2) report a summary of anthropometric, muscular power, linear speed, change-of-direction speed, agility, strength, anaerobic capacity, and aerobic capacity in adult male basketball players based on playing position and competition level, and (3) introduce a framework outlining recommended testing approaches to quantify physical characteristics in adult male basketball players.MethodsA systematic review of MEDLINE, PubMed, SPORTDiscus, Scopus, and Web of Science was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify relevant studies. To be eligible for inclusion, studies were required to: (1) be original research articles; (2) be published in a peer-reviewed journal; (3) have full-text versions available in the English language; and (4) include the primary aim of reporting tests used and/or the physical characteristics of adult (i.e., ≥ 18 years of age) male basketball players. Additionally, data from the top 10 draft picks who participated in the National Basketball Association combined from 2011-12 to 2020-21 were extracted from the official league website to highlight the physical characteristics of elite 19- to 24-year-old basketball players.ResultsA total of 1684 studies were identified, with 375 being duplicates. Consequently, the titles and abstracts of 1309 studies were screened and 231 studies were eligible for full-text review. The reference list of each study was searched, with a further 59 studies identified as eligible for review. After full-text screening, 137 studies identified tests, while 114 studies reported physical characteristics in adult male basketball players.ConclusionsPhysical characteristics reported indicate a wide range of abilities are present across playing competitions. The tests and outcome variables reported in the literature highlight the multitude of tests currently being used. Because there are no accepted international standards for physical assessment of basketball players, establishing normative data is challenging. Therefore, future testing should involve repeatable protocols that are standardised and provide outcomes that can be monitored across time. Recommendations for testing batteries in adult male basketball players are provided so improved interpretation of data can occur.Clinical trial registrationThis review was registered with the International Prospective Register of Systematic Reviews and allocated registration number CRD42020187151 on 28 April, 2020.
Project description:BackgroundADHD is classically seen as a childhood disease, although it persists in one out of two cases in adults. The diagnosis is based on a long and multidisciplinary process, involving different health professionals, leading to an under-diagnosis of adult ADHD individuals. We therefore present a psychometric screening scale for the identification of adult ADHD which could be used both in clinical and experimental settings.MethodWe designed the scale from the DSM-5 and administered it to n = 110 control individuals and n = 110 ADHD individuals. The number of items was reduced using multiple regression procedures. We then performed factorial analyses and a machine learning assessment of the predictive power of the scale in comparison with other clinical scales measuring common ADHD comorbidities.ResultsInternal consistency coefficients were calculated satisfactorily for TRAQ10, with Cronbach's alpha measured at .9. The 2-factor model tested was confirmed, a high correlation between the items and their belonging factor. Finally, a machine-learning analysis showed that classification algorithms could identify subjects' group membership with high accuracy, statistically superior to the performances obtained using comorbidity scales.ConclusionsThe scale showed sufficient performance for its use in clinical and experimental settings for hypothesis testing or screening purpose, although its generalizability is limited by the age and gender biases present in the data analyzed.