It is widely hoped that statistical models can improve decision-making related to medical treatments. Because of the cost and scarcity of medical outcomes data, this hope is typically based on investigators observing a model's success in one or two datasets or clinical contexts. We scrutinized this optimism by examining how well a machine learning model performed across several independent clinical trials of antipsychotic medication for schizophrenia. Models predicted patient outcomes with high accuracy within the trial in which the model was developed but performed no better than chance when applied out-of-sample. Pooling data across trials to predict outcomes in the trial left out did not improve predictions. These results suggest that models predicting treatment outcomes in schizophrenia are highly context-dependent and may have limited generalizability.

Illusory generalizability of clinical prediction models.

Machine-learning-based models found to have predictive abilities no better than chance in out-of-sample evaluations

2 Minute Medicine

Science

During surgery, various haemodynamic variables are monitored and optimised to maintain organ perfusion pressure and oxygen delivery - and to eventually improve outcomes. Important haemodynamic variables that provide an understanding of most pathophysiologic haemodynamic conditions during surgery include heart rate, arterial pressure, central venous pressure, pulse pressure variation/stroke volume variation, stroke volume, and cardiac output. A basic physiologic and pathophysiologic understanding of these haemodynamic variables and the corresponding monitoring methods is essential. We therefore revisit the pathophysiologic rationale for intraoperative monitoring of haemodynamic variables, describe the history, current use, and future technological developments of monitoring methods, and finally briefly summarise the evidence that haemodynamic management can improve patient-centred outcomes.

Haemodynamic monitoring during noncardiac surgery: past, present, and future.

Journal of Clinical Monitoring and Computing

The "2024 AHA/ACC/AMSSM/HRS/PACES/SCMR Guideline for the Management of Hypertrophic Cardiomyopathy" provides recommendations to guide clinicians in the management of patients with hypertrophic cardiomyopathy.

A comprehensive literature search was conducted from September 14, 2022, to November 22, 2022, encompassing studies, reviews, and other evidence on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through May 23, 2023, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate.

Hypertrophic cardiomyopathy remains a common genetic heart disease reported in populations globally. Recommendations from the "2020 AHA/ACC Guideline for the Diagnosis and Treatment of Patients With Hypertrophic Cardiomyopathy" have been updated with new evidence to guide clinicians.

2024 AHA/ACC/AMSSM/HRS/PACES/SCMR Guideline for the Management of Hypertrophic Cardiomyopathy: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines.

Circulation

The prevalence of obesity in older adults (people aged &gt;60 years) is increasing in line with the demographic shift in global populations. Despite knowledge of obesity-related complications in younger adults (increased risk of type 2 diabetes, liver and cardiovascular disease and malignancy), these considerations may be outweighed, in older adults, by concerns regarding weight-loss induced reduction in skeletal muscle and bone mass, and the awareness of the 'obesity paradox'. Obesity in the elderly contributes to various obesity-related complications from cardiometabolic disease and cancer, to functional decline, worsening cognition, and quality of life, that will have already suffered an age-related decline. Lifestyle interventions remain the cornerstone of obesity management in older adults, with emphasis on resistance training for muscle strength and bone mineral density preservation. However, in older adults with obesity refractory to lifestyle strategies, pharmacotherapy, using anti-obesity medicines (AOMs), can be a useful adjunct. Recent evidence suggests that intentional weight loss in older adults with overweight and obesity is effective and safe, hence a diminishing reluctance to use AOMs in this more vulnerable population. Despite nine AOMs being currently approved for the treatment of obesity, limited clinical trial evidence in older adults predominantly focuses on incretin therapy with glucagon-like peptide-1 receptor agonists (liraglutide, semaglutide, and tirzepatide). AOMs enhance weight loss and reduce cardiometabolic events, while maintaining muscle mass. Future randomised controlled trials should specifically evaluate the effectiveness of novel AOMs for long-term weight management in older adults with obesity, carefully considering the impact on body composition and functional ability, as well as health economics.

Obesity pharmacotherapy in older adults: a narrative review of evidence.

International Journal of Obesity

Albumin is commonly employed across a wide range of clinical settings to improve hemodynamics, facilitate fluid removal, and manage complications of cirrhosis. The International Collaboration for Transfusion Medicine Guidelines developed guidelines for the use of albumin in patients requiring critical care, undergoing cardiovascular surgery, kidney replacement therapy, or experiencing complications of cirrhosis.

Co-chairs oversaw the guideline development process and the panel included researchers, clinicians, methodologists, and a patient representative. The evidence informing this guideline arises from a systematic review of randomized clinical trials and systematic reviews, in which multiple databases were searched (inception to November 23, 2022). The panel reviewed the data and formulated the guideline recommendations using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. The guideline was revised after public consultation.

The panel made 14 recommendations on albumin use in adult critical care (3 recommendations), pediatric critical care (1 recommendation), neonatal critical care (2 recommendations), cardiovascular surgery (2 recommendations), kidney replacement therapy (1 recommendation), and complications of cirrhosis (5 recommendations). Of the 14 recommendations, 2 had moderate certainty of evidence, 5 had low certainty of evidence, and 7 had very low certainty of evidence. Two of the 14 recommendations suggested conditional use of albumin for patients with cirrhosis undergoing large volume paracentesis or with spontaneous bacterial peritonitis. Twelve of 14 recommendations did not suggest albumin use in a wide variety of clinical situations where albumin is commonly transfused.

There are currently few evidence-based indications that support the routine use of albumin in clinical practice to improve patient outcomes. This guideline provides clinicians with actionable recommendations on the use of albumin.

Use of Intravenous Albumin: A Guideline from the International Collaboration for Transfusion Medicine Guidelines.

Chest

Antibiotics have played a pivotal role in modern medicine, drastically reducing mortality rates associated with bacterial infections. Despite their significant contributions, the emergence of antibiotic resistance has become a formidable challenge, necessitating a re-evaluation of antibiotic use practices. The widespread belief in clinical practice that bactericidal antibiotics are inherently superior to bacteriostatic ones lacks consistent support from evidence in randomized controlled trials (RCTs). With the latest evidence, certain infections have demonstrated equal or even superior efficacy with bacteriostatic agents. Furthermore, within clinical practice, there is a tendency to indiscriminately order urine cultures for febrile patients, even in cases where alternative etiologies might be present. Consequently, upon obtaining a positive urine culture result, patients often receive antimicrobial prescriptions despite the absence of clinical indications warranting such treatment.&#xa0;Furthermore, it is a prevailing notion among physicians that extended durations of antibiotic therapy confer potential benefits and mitigate the emergence of antimicrobial resistance. Contrary to this belief, empirical evidence refutes such assertions. This article aims to address common myths and misconceptions within the field of infectious diseases.

''Myth Busting in Infectious Diseases'': A Comprehensive Review.

Curēus

Some of the most common conditions affecting people are kidney diseases. Among them, we distinguish chronic kidney disease and acute kidney injury. Both entities pose serious health risks, so new drugs are still being sought to treat and prevent them. In recent years, such a role has begun to be assigned to sodium-glucose cotransporter-2 (SGLT2) inhibitors. They increase the amount of glucose excreted in the urine. For this reason, they are currently used as a first-line drug in type 2 diabetes mellitus. Due to their demonstrated cardioprotective effect, they are also used in heart failure treatment. As for the renal effects of SGLT2 inhibitors, they reduce intraglomerular pressure and decrease albuminuria. This results in a slower decline in glomelular filtration rate (GFR) in patients with kidney disease. In addition, these drugs have anti-inflammatory and antifibrotic effects. In the following article, we review the evidence for the effectiveness of this group of drugs in kidney disease and their nephroprotective effect. Further research is still needed, but meta-analyses indicate SGLT2 inhibitors' efficacy in kidney disease, especially the one caused by diabetes. Development of new drugs and clinical trials on specific patient subgroups will further refine their nephroprotective effects.

Illusory generalizability of clinical prediction models.

Paper Summary

Machine-learning-based models found to have predictive abilities no better than chance in out-of-sample evaluations

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Illusory generalizability of clinical prediction models.

Paper Summary

Machine-learning-based models found to have predictive abilities no better than chance in out-of-sample evaluations

Full text links

Related Resources

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