Medicine Clinical Practice Research Articles

When math legitimizes knowledge: a step by step approach to Bayes’ rule in diagnostic reasoning

INTRODUCTION: Many mistakes in clinical practice arise from confusing the probability of a positive test in those with the disease and the probability of having the disease in those who test positive. This misunderstanding leads to overestimating disease probability, diagnosing diseases in healthy individuals, ordering invasive diagnostic tests, and prescribing unnecessary treatments, resulting in unjustified adverse effect, psychological stress, and increased cost. Probabilistic reasoning is an essential skill to mitigate this confusion, and Bayes theorem is an important tool to accomplish this goal. OBJECTIVE: To present a step-by-step demonstration of Bayes' formula for positive and negative predictive values, fostering understanding and enabling its adoption in evidence-based medicine education and clinical practice as a supporting tool in the decision-making process. METHODS: In this article, we explain the difference between deductive and inductive thinking and how diagnostic reasoning is predominantly inductive, where evidence (the test result) is used to predict the cause (the presence of disease), a path that involves reverse probability, for which our reasoning is hazier. Through a clinical example involving the diagnosis of systemic lupus erythematosus, we use the Bayesian framework as a tool to help understand the difference between sensitivity/specificity (forward probability; deductive) and positive/negative predictive values (reverse probability: inductive). CONCLUSIONS: Excellent doctors are masters at applying Bayesian reasoning without using any formulas: they understand that the most important component of the diagnostic process is the reasoning that originates it and the resulting clinical decision depends on interpreting results considering their interaction with the context, not in isolation. Bad clinical reasoning results in bad clinical decisions, despite how accurate the diagnostic test: garbage in, garbage out. We hope our step-by-step approach to Bayes' rule can help demystify this powerful statistical tool and strengthen the idea that the value of a diagnostic test is directly proportional to the quality of clinical reasoning that led to its request.

Precision Medicine in Anesthesia: Pharmacogenomics and Personalized Care

Precision medicine in anesthesia represents a transformative approach aimed at optimizing anesthetic care by tailoring interventions to individual patient characteristics, particularly their genetic profile. Pharmacogenomics, a cornerstone of precision medicine, explores the genetic factors influencing drug metabolism, efficacy, and adverse reactions. This article delves into the integration of pharmacogenomics in anesthesia, discussing its impact on drug selection, dosage adjustments, and patient outcomes. It also highlights the potential for reducing perioperative complications, enhancing patient safety, and improving recovery through personalized anesthetic care. Challenges such as the need for robust genetic databases, ethical considerations, and the cost-effectiveness of implementing precision medicine in clinical practice are also discussed. The future of anesthesia lies in harnessing pharmacogenomics to provide individualized care, ultimately advancing patient-centric anesthetic management.

Can AI hear me? Nine facts about the artificial intelligence scribe

This article summarizes important features of artificial intelligence scribe (AIS) and its application as a digital scribe through the utilization of voice recognition as it is integrated into the clinical practice of medicine. This discussion will include 1) digital scribe technology, 2) practical utility, 3) liability, 4) privacy, 5) integration to electronic health records (EHR), 6) technology burden, 7) case use, 8) AIS documentation styles, and 9) cost. The use of AIS technology in healthcare is a promising tool and will result in variability applications requiring healthcare providers to be aware of the complexities of the tool before utilization, during implementation, the effect of it on workflow, and its acceptance by the patients we serve. AIS technology promises to decrease the cognitive workload of the healthcare provider, through application by relieving the ever-increasing burden of documenting the medical record, organizing, and capturing relevant medical data, by improving integration of this data into cumbersome EHRs, thus providing better work life balance. The authors piloted a version of an AIS in a primarily Spanish patient population. This article provides a unique perspective towards the usability of an AIS in a Hispanic patient population.

Assessment of chronic pain: multidimensional tools, applicability, and practicality

Introduction: Chronic pain (CP) negatively impacts patients’ physical and psychological status. Thus, it has the potential to affect every aspect of everyday life. In Portugal, CP is a major public health problem that affects roughly 36.7% of adults. Nevertheless, assessment of this condition is still far from ideal. A Portuguese study showed that most of last year’s medical students and first-year residents did not routinely assess pain. Additionally, the best-known pain assessment tools are the ones that focus only on pain intensity, thus disregarding the multidimensional nature of pain. Objectives: This study aims to review pain assessment tools that consider the nature of pain and its impact on patients' functionality. The ultimate goal is to increase the knowledge and dissemination of such tools. Methods: Focus groups were conducted with a panel of 29 Portuguese physicians specialized in family medicine and orthopaedics. Several pain assessment tools were debated regarding applicability, practicality, and relevance. After group discussion, five pain assessment tools were considered particularly relevant. Results: The characteristics, advantages, and disadvantages of five pain assessment tools (ACT-UP, CAPA, Barthel index, BPI, and EQ-5D), and the need for their applicability in the family medicine clinical practice are summarized and highlighted. Functional assessment of CP patients is a key step to deciding the most adequate treatment regimen since the individual nature of patients will cause them to be differently affected by distinct limitations, even if the intensity of pain is similar. Conclusion: The implementation use of these tools in clinical practice will be crucial for the improvement of CP management.

Research Progress on the Pharmacological Mechanism of Traditional Chinese Medicine Danshen in the Treatment of Cerebral Ischemic Stroke

Cerebral ischemic stroke (CIS) is an acute cerebrovascular disease characterized by focal neurological deficits. Many modern scholars believe that the pathogenesis of CIS is related to factors such as endothelial injury, oxidative stress imbalance, neuroinflammation, cell apoptosis and autophagy, calcium overload, and excessive accumulation of oxygen free radicals. Traditional Chinese medicine believes that the pathogenesis of CIS is obstructed meridians, phlegm and blood stasis, and obstruction of the brain and orifices. Danshen, as a commonly used traditional Chinese medicine in clinical practice, has the effects of promoting blood circulation and removing blood stasis, unblocking meridians and relieving pain, clearing the heart and eliminating restlessness, cooling blood and eliminating carbuncle. In addition, modern pharmacological research has found that the specific pharmacological components of Salvia miltiorrhiza include tanshinone, salvianolic acid, shikimic acid, danshensu, protocatechualdehyde, etc. It has antioxidant stress, regulation of cell autophagy, anti-inflammatory factors, antiplatelet aggregation, and protection of vascular endothelium. This article aims to analyze and summarize the pharmacological mechanism of salvia miltiorrhiza in treating CIS, providing scientific basis for clinical application of salvia miltiorrhiza in treating CIS.

Identification of Necroptosis-related Molecular Subtypes and Construction of Necroptosis-related Gene Signature for Glioblastoma Multiforme.

Necroptosis is a highly regulated and genetically controlled process, and therefore, attention has been paid to the exact effects of this disorder on a variety of diseases, including cancer. An in-depth understanding of the key regulatory factors and molecular events that trigger necroptosis can not only identify patients at risk of cancer development but can also help to develop new treatment strategies. This study aimed to increase understanding of the complex role of necroptosis in glioblastoma multiforme (GBM) and provide a new perspective and reference for accurate prediction of clinical outcomes and gene-targeted therapy in patients with GBM. The objective of this study was to analyze the gene expression profile of necroptosis regulatory factors in glioblastoma multiforme (GBM) and establish a necroptosis regulatory factor-based GBM classification and prognostic gene signature to recognize the multifaceted impact of necroptosis on GBM. The necroptosis score of the glioblastoma multiforme (GBM) sample in TCGA was calculated by ssGSEA, and the correlation between each gene and the necroptosis score was calculated. Based on necroptosis score-related genes, unsupervised consensus clustering was employed to classify patients. The prognosis, tumor microenvironment (TME), genomic changes, biological signal pathways and gene expression differences among clusters were analyzed. The gene signature of GBM was constructed by Cox and LASSO regression analysis of differentially expressed genes (DEGs). Based on 34 necroptosis score-related genes, GBM was divided into two clusters with different overall survival (OS) and TME. A necroptosis-related gene signature (NRGS) containing 8 genes was developed, which could stratify the risk of GBM in both the training set and verification set and had good prognostic value. NRGS and age were both independent prognostic indicators of GBM, and a nomogram developed by the integration of both of them showed a better predictive effect than traditional clinical features. In this study, patients from public data sets were divided into two clusters and the unique TME and molecular characteristics of each cluster were described. Furthermore, an NRGS was constructed to effectively and independently predict the survival outcome of GBM, which provides some insights for the implementation of personalized precision medicine in clinical practice.

Treatment of restless legs syndrome and periodic limb movement disorder: an American Academy of Sleep Medicine clinical practice guideline.

This guideline establishes clinical practice recommendations for Treatment of Restless Legs Syndrome (RLS) and Periodic Limb Movement Disorder (PLMD) in adults and pediatric patients. The American Academy of Sleep Medicine (AASM) commissioned a task force of experts in sleep medicine to develop recommendations and assign strengths based on a systematic review of the literature and an assessment of the evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. The task force provided a summary of the relevant literature and the certainty of evidence, the balance of benefits and harms, patient values and preferences, and resource use considerations that support the recommendations. The AASM Board of Directors approved the final recommendations. The following good practice statement is based on expert consensus, and its implementation is necessary for the appropriate and effective management of patients with RLS. The following recommendations are intended as a guide for clinicians in choosing a specific treatment for RLS and PLMD in adults and children. Each recommendation statement is assigned a strength ("Strong" or "Conditional"). A "Strong" recommendation (i.e., "We recommend…") is one that clinicians should follow under most circumstances. The recommendations listed below are ranked in the order of strength of recommendations and grouped by class of treatments within each PICO question. Some recommendations include remarks that provide additional context to guide clinicians with implementation of this recommendation.

Escalating costs of innovative medicines: perspective and proposals.

Public healthcare systems are challenged by the soaring costs of medications that require increasing resources, often at the expense of other investments. The increasing pharmaceutical budget poses a threat to the allocation of funds for essential preventive and primary healthcare services while also raising concerns about equitable access, particularly in models where patients bear part of the costs out of their own pockets. Proposals on how to ensure ongoing and long-term accessibility, efficiency, and financial stability are required. The escalating costs of medicines may be explained in part by the mismatch between the traditional value-based pricing and reimbursement frameworks and the type of clinical development of targeted therapies and precision medicine in clinical practice. New appraisal methods and managed access strategies should be adapted to therapies targeting small populations and addressing increased uncertainty. Fair pricing strategies, transparent healthcare investments based on problems and outcomes, regulatory reforms, international cooperation, and critically examining the drug acquisition model are potential solutions. Transitioning from an industry-driven pricing approach to a health-driven payment model can help align the cost of treatments with actual health outcomes, establishing a foundation for a healthcare system that addresses immediate challenges and fosters long-term well-being. Acknowledging the lack of a universally applicable solution, the practical implementation of interventions requires a reframing of the pricing and access system and adaption to the targeted therapeutic approaches. Balancing innovation with financial sustainability necessitates a collaborative, adaptive, and transparent approach, as well as transitioning toward health-driven payment models, moving the focus from the cost of medications to the well-being of populations worldwide.

Comparative genomics and transcriptomics analysis of the bHLH gene family indicate their roles in regulating flavonoid biosynthesis in Sophora flavescens.

The basic helix-loop-helix (bHLH) transcription factors play crucial roles in various processes, such as plant development, secondary metabolism, and response to biotic/abiotic stresses. Sophora flavescens is a widely used traditional herbal medicine in clinical practice, known for its abundant flavonoids as the main active compounds. However, there has been no comprehensive analysis of S. flavescens bHLH (SfbHLH) gene family reported currently. In this study, we identified 167 SfbHLH genes and classified them into 23 subfamilies based on comparative genomics and phylogenetic analysis. Furthermore, widespread duplications significantly contributed to the expansion of SfbHLH family. Notably, SfbHLH042 was found to occupy a central position in the bHLH protein-protein interaction network. Transcriptome analysis of four tissues (leaf, stem, root and flower) revealed that most SfbHLH genes exhibited high expression levels exclusively in specific tissues of S. flavescens. The integrated analysis of transcriptomics and metabolomics during pod development stages revealed that SfbHLH042 may play a central role in connecting SfbHLH genes, flavonoids, and key enzymes involved in the biosynthesis pathway. Moreover, we also checked the expression of 8 SfbHLH genes using RT-qPCR analysis to realize the expression profiles of these genes among various tissues at different cultivated periods and root development. Our study would aid to understand the phylogeny and expression profile of SfbHLH family genes, and provide a promising candidate gene, SfbHLH042, for regulating the biosynthesis of flavonoids in S. flavescens.

Every problem is embedded in a greater whole.

Peter Drucker pointed out an important distinction between 'doing things right' and 'doing the right thing', which recognised that all problems are embedded in a context and thus can only be understood within their unique contextual setting. Contemporary research practices in clinical medicine often regards contextual factors as potential confounders that will bias effect estimates and thus must be avoided. However rigorous, research devoid of context ultimately deprives users of understanding of the support factors that make research transferable to policy decisions or managing care of individual patients-it stands in the way of 'doing the right thing' in 'real life' settings. Appreciating that all problems are embedded in a greater context means that one should not ignore their interconnected and interdependent systemic nature, that is, every variable is simultaneously dependent and independent. This is the reason for the cascading effects and feedback loops witnessed in disease progression and policy efforts. We discuss the need for researchers to a-priori consider the context of their research question as well as the structural relationships of the variables under investigation, which in turn provides the basis for choosing the most appropriate research design. We have a moral imperative to first 'do the right thing'-ask questions that address the contextual needs of our patients, and then to 'do it right'-choose the best research method to answer this contextually framed need. Only then will our research efforts have meaningful and lasting impacts on patient care.

An Innovative Hybrid Model for Automatic Detection of White Blood Cells in Clinical Laboratories.

Background: Microscopic examination of peripheral blood is a standard practice in clinical medicine. Although manual examination is considered the gold standard, it presents several disadvantages, such as interobserver variability, being quite time-consuming, and requiring well-trained professionals. New automatic digital algorithms have been developed to eliminate the disadvantages of manual examination and improve the workload of clinical laboratories. Objectives: Regular analysis of peripheral blood cells and careful interpretation of their results are critical for protecting individual health and early diagnosis of diseases. Because many diseases can occur due to this, this study aims to detect white blood cells automatically. Methods: A hybrid model has been developed for this purpose. In the developed model, feature extraction has been performed with MobileNetV2 and EfficientNetb0 architectures. In the next step, the neighborhood component analysis (NCA) method eliminated unnecessary features in the feature maps so that the model could work faster. Then, different features of the same image were combined, and the extracted features were combined to increase the model's performance. Results: The optimized feature map was classified into different classifiers in the last step. The proposed model obtained a competitive accuracy value of 95.6%. Conclusions: The results obtained in the proposed model show that the proposed model can be used in the detection of white blood cells.

A comprehensive review of artificial intelligence for pharmacology research.

With the innovation and advancement of artificial intelligence, more and more artificial intelligence techniques are employed in drug research, biomedical frontier research, and clinical medicine practice, especially, in the field of pharmacology research. Thus, this review focuses on the applications of artificial intelligence in drug discovery, compound pharmacokinetic prediction, and clinical pharmacology. We briefly introduced the basic knowledge and development of artificial intelligence, presented a comprehensive review, and then summarized the latest studies and discussed the strengths and limitations of artificial intelligence models. Additionally, we highlighted several important studies and pointed out possible research directions.

The imperative of teamwork in antimicrobial stewardship (AMS) interventions: insights from an ethnographic study with practitioners in Spain.

Teamwork-the activity of working together in a group towards a similar goal-is a defining feature of the practice of clinical medicine carried out in hospitals and other healthcare facilities. This Viewpoint suggests that teamwork is a defining feature of antimicrobial stewardship (AMS) programmes, and identifies six elements that characterise AMS team dynamics. These insights arise from an original ethnographic study of AMS carried out in Spain, where these programmes are known as Programas para la Optimización de Antimicrobianos. The study used qualitative research methods including ethnographic observations in public hospitals and scientific and educational fora, in-depth interviews and archival research. It calls for a reflection on the part of the global community of AMS practitioners on the role of team dynamics in building sustainable AMS interventions and the inclusion of teamwork skills in training curricula aimed at future practitioners.

Research on biomarkers using innovative artificial intelligence systems in breast cancer.

Cancer is highly diverse and heterogeneous. Accurate and rapid analysis of the characteristics of individual cancer cells, using a complex array of big data that includes various clinicopathological features and molecular mechanisms, is crucial for advancing precision medicine. In recent years, experts in biomedical sciences and data sciences have explored the potential of artificial intelligence (AI) to analyze such extensive data sets. The next phase of AI-based medical research on cancer should focus on the practical applications of AI tools and how they can be effectively used in actual medical research settings. Recently, translational research that leverages AI and comprehensive genetic analysis data has emerged as a significant research focus. This field represents an opportunity for groundbreaking discoveries to be shared globally. To further precision medicine in clinical practice, it is vital to develop sophisticated AI tools for cancer research. These tools should not only identify potential therapeutic targets through comprehensive genetic analysis but also predict therapeutic outcomes in clinical settings.

Advantages of SiPM-based digital PET/CT technology in nuclear medicine clinical practice: a systematic review—Part 1 oncological setting

Advantages of SiPM-based digital PET/CT technology in nuclear medicine clinical practice: a systematic review—Part 1 oncological setting

Advancing value-based laboratory medicine.

Following the COVID-19 pandemic, the concepts of value-based medicine (VBM) and value-based laboratory medicine (VBLM) are receiving increasing interest to improve the quality, sustainability and safety of healthcare. Laboratory medicine is well positioned to support the transition to value-based healthcare as it helps to improve clinical outcomes and healthcare sustainability by reducing the time to diagnosis, improving diagnostic accuracy, providing effective guidance for tailored therapies and monitoring, and supporting screening and wellness care. However, the perception of the value of laboratory medicine is still limited, to the extent that it has been defined a "profession without a face", often lacking visibility to patients and the public. In addition, in recent decades, clinical laboratories have sought to improve the ration between outcomes and costs by increasing efficiency and reducing the cost per test rather than improving clinical outcomes. The aim of this paper is to propose a 10-point manifesto for implementing value-based laboratory medicine in clinical practice.

Individual treatment effects of sodium-glucose co-transporter-2 inhibitors on the risk of chronic kidney disease in patients with type 2 diabetes: A counterfactual prediction model based on real-world data.

To estimate individual treatment effects (ITEs) of sodium-glucose co-transporter-2 inhibitors (SGLT2is) on lowering the risk of developing chronic kidney disease (CKD) in patients with type 2 diabetes (T2D) and to identify those most probable to benefit from treatment. This study followed a T2D cohort from Ramathibodi Hospital, Thailand, from 2015 to 2022. A counterfactual model was constructed to predict factual and counterfactual risks of CKD if patients did/did not receive SGLT2is. ITEs were estimated by subtracting the factual risk from the counterfactual risk of CKD. There were 1619 and 15 879 patients included in the SGLT2i and non-SGLT2i groups, respectively. The estimated ITEs varied from -1.19% to -17.51% with a median of -4.49%, that is, 50% of patients had a 4.49% or greater lower CKD risk if they received an SGLT2i. Patients who gained the greatest benefit from SGLT2is were more probable to be male, aged at least 60 years, with a history of diabetes duration of at least 3 months, hypertension, peripheral arterial disease, diabetic retinopathy and low high-density lipoprotein cholesterol. Our prediction model provides individualized information that helps target T2D patients who may benefit more from SGLT2is. This could help clinical decision making and implementation of personalized medicine in clinical practice, especially in resource-limited settings.

Advantages of SiPM-based digital PET/CT technology in nuclear medicine clinical practice: a systematic review– part 2

Advantages of SiPM-based digital PET/CT technology in nuclear medicine clinical practice: a systematic review– part 2

Characterization of the alcohol biomarker phosphatidylethanol in donor whole blood and apheresis red blood cells: Implications for transfusion recipients.

Phosphatidylethanol (PEth) is a long-term marker of alcohol consumption used frequently in clinical scenarios such as liver transplant evaluation. Recent cases have demonstrated that packed red blood cell (pRBC) transfusion creates the potential for artificial elevation or decrease of observed PEth concentrations in recipients. Very little is known about the prevalence or stability of PEth in pRBCs. Apheresis and whole-blood (WB) donations were tested for PEth using liquid chromatography - tandem mass spectrometry with limit of quantitation 10 ng/mL. Units were stored under routine blood bank conditions to evaluate the stability of PEth and the impact of irradiation. Over 40% of apheresis and WB donors had PEth ≥10 ng/mL (maximum observed 587 ng/mL). As WB units were processed into component pRBCs, PEth concentrations increased and were higher than donor WB levels (EDTA sample) prior to collection (maximum observed 711 ng/mL). Storage for up to 5 weeks post donation resulted in mean 17.3% decrease in PEth-positive units; in contrast to a prior report, we observed no PEth formation in units with negative (<10 ng/mL) baseline concentrations. Irradiation of pRBCs did not substantially affect PEth concentrations in either PEth-positive or PEth-negative units. PEth concentrations in healthy blood donors may potentially confound alcohol use or abstinence assessment in pRBC recipients. Transfusion medicine services and clinical practices such as transplantation and behavioral medicine should recognize this phenomenon and collaborate on testing protocols to appropriately interpret PEth in pRBC recipients.

Liberation from Mechanical Ventilation in Critically Ill Patients: Korean Society of Critical Care Medicine Clinical Practice Guidelines.

Successful liberation from mechanical ventilation is one of the most crucial processes in critical care, because it is the first step through which a respiratory failure patient begins to transition out of the intensive care unit, and return to normal life. Therefore, when devising appropriate strategies for removing mechanical ventilation, it is essential to consider scientific and systematic approaches, as well as the individual experiences of healthcare professionals. Recently, numerous studies have investigated methods and tools to identify when mechanically ventilated patients are ready to breathe on their own. The Korean Society of Critical Care Medicine therefore provides these recommendations to clinicians for liberation from the ventilator. Meta-analyses and comprehensive syntheses were used to thoroughly review, compile, and summarize the complete body of relevant evidence. All studies were meticulously assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method, and the outcomes were presented succinctly as evidence profiles. These evidence syntheses were discussed by a multidisciplinary committee of experts in mechanical ventilation, who then developed and approved the recommendations. Recommendations for nine questions on ventilator liberation about Population, Intervention, Comparator, and Outcome (PICO) are presented in this document. This guideline presents seven conditional recommendations, one expert consensus recommendation, and one conditional deferred recommendation. We developed these clinical guidelines for mechanical ventilation liberation to provide meaningful recommendations. These guidelines reflect the best treatment for patients seeking liberation from mechanical ventilation.