Annals of medicine
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The purpose of this study is to explore the risk factors of gallbladder stone (GBS) in patients with type 2 diabetes mellitus (T2DM) and also develop a simple-to-use nomogram for GBS in patients with T2DM. ⋯ The nomogram is accurate to a certain degree and provides a clinical basis for predicting the incidence of GBS in patients with T2DM, which has a certain predictive value.
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Lean Non-alcoholic Fatty Liver Disease (NAFLD) shares a similar disease burden to those of their overweight counterparts and should be detected early. We hypothesized that the adiponectin-leptin ratio (AL ratio) could be a good marker for early detection of lean NAFLD independent of insulin resistance. ⋯ The study revealed that the AL ratio could be a good biomarker to early distinguish lean NAFLD patients from lean controls independent of insulin resistance. [AQ3]Key messagesThe prevalence of non-alcoholic fatty liver disease (NAFLD) increases globally and is related to liver diseases and metabolic dysfunctions. Lean subset of NAFLD shares a similar disease burden to those of their overweight counterparts and should be detected early.Adiponectin-leptin ratio were associated with the severity of steatosis and was a predictor of obese NAFLD better than each single adipokine. To date, there is no investigation that explores specifically for the relationship between lean NAFLD and AL ratio.Our study found that adiponectin-leptin ratio is a sole independent marker regardless of insulin resistance in lean NAFLD. Having lean NAFLD for the highest versus the lowest tertile of adiponectin-leptin ratio was 0.28(95%CI: 0.12-0.69) after adjustment of age, sex, current smoking, exercise habits, HOMA-IR and AST/ALT. ROC for the NAFLD performance is good for the early detection (0.85; 95% CI: 0.82-0.88). Further rigorous investigation is necessary and should be promptly performed.
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Determining tumor necrosis factor-alpha inhibitors (anti-TNF-α) failure is still a challenge in the management of moderate-to-severe psoriasis. Thus, our comprehensive systematic literature review aimed to gather information on the criteria used to define anti-TNF-α failure. We also aimed to discover the main reasons for anti-TNF-α failure and define subsequently administered treatments. ⋯ Our findings suggest a need to standardize the management of anti-TNF-α failure and reflect the incorporation of new targets, such as IL-inhibitors, in the treatment sequence.KEY MESSAGESIn the treatment of psoriasis, the primary and secondary anti-TNF-α failure criteria differ widely in the scientific literature.The strictest efficacy criteria for defining anti-TNF-α failure, or those recommended by guidelines such as PASI75, were underused both in clinical trials and observational studies.Most studies failed to consider patient-reported outcomes in assessing psoriasis treatment efficacy, which contrasts with recent recommendations on the inclusion of patient-reported HRQoL as a supporting criterion when considering clinical outcomes.
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Probabilistic graphical modelling (PGM) can be used to predict risk at the individual patient level and show multiple outcomes and exposures in a single model. ⋯ The causal predictors of surgical outcome for DCM were sex, dementia and PreJOA score. Therefore, PGM may be a useful personalized medicine tool for predicting the outcome of patients with DCM.
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The persistent spread of SARS-CoV-2 makes diagnosis challenging because COVID-19 symptoms are hard to differentiate from those of other respiratory illnesses. The reverse transcription-polymerase chain reaction test is the current golden standard for diagnosing various respiratory diseases, including COVID-19. However, this standard diagnostic method is prone to erroneous and false negative results (10% -15%). Therefore, finding an alternative technique to validate the RT-PCR test is paramount. Artificial intelligence (AI) and machine learning (ML) applications are extensively used in medical research. Hence, this study focused on developing a decision support system using AI to diagnose mild-moderate COVID-19 from other similar diseases using demographic and clinical markers. Severe COVID-19 cases were not considered in this study since fatality rates have dropped considerably after introducing COVID-19 vaccines. ⋯ The promising results suggest using this decision support system to diagnose COVID-19 from other similar respiratory illnesses.