Lymphomatosis Cerebri: A diagnostic dilemma.

Background: Lymphomatosis cerebri (LC) is a rare manifestation of primary central nervous system lymphoma (PCNSL) with only a few cases reported in the literature, appearing as diffuse infiltrating process rather than a solitary mass. It is a non-Hodgkin's type of lymphoma and is usually of the B-cell type origin. Purpose: We intend to report this unique case of LC which came across as a diagnostic challenge. Methods: A 53-year-old gentleman presented with complaints of two episodes of seizures 24 h apart followed by postictal confusion for 10-15 min. He underwent multiple MRI scans and underwent a biopsy of the lesion which reported infection, but he did not benefit from the treatment. Result: The imaging was reviewed, suspicion of LC was raised and a review of histopathology was requested which later confirmed primary CNS lymphoma. Conclusion: LC is a rare but established manifestation of PCNSL which mimics multiple other conditions. Understanding of the imaging pattern is important in making the diagnosis and differentiating it from other mimic conditions.

[Significance and application of quality improvement in clinical medicine]. / 质量改进在临床医学中的意义和应用.

Quality improvement is a methodology which was initially developed and employed in the field of industrial manufacturing. This approach involves implementing a series of interventions aimed at elevating the existing quality standards to a higher level. In daily medical work, there are often spontaneous quality improvements. Medical quality improvements supported by scientific methodology can evaluate medical quality more scientifically and provide objective feedback on the quality of medical work for healthcare professionals. This article provides a concise introduction to quality improvement and shows its application and significance in the field of clinical medicine through examples.

Storylines of family medicine VIII: clinical approaches.

Storylines of Family Medicine is a 12-part series of thematically linked mini-essays with accompanying illustrations that explore the many dimensions of family medicine as interpreted by individual family physicians and medical educators in the USA and elsewhere around the world. In 'VIII: clinical approaches', authors address the following themes: 'Evaluation, diagnosis and management I-toward a working diagnosis', 'Evaluation, diagnosis and management II-process steps', 'Interweaving integrative medicine and family medicine', 'Halfway-the art of clinical judgment', 'Seamless integration in family medicine-team-based care', 'Technology-uncovering stories from noise' and 'Caring for patients with multiple long-term conditions'. May readers recognise in these essays the uniqueness of a family medicine approach to care.

Storylines of family medicine IX: people and places-diverse populations and locations of care.

Storylines of Family Medicine is a 12-part series of thematically linked mini-essays with accompanying illustrations that explore the many dimensions of family medicine as interpreted by individual family physicians and medical educators in the USA and elsewhere around the world. In 'IX: people and places-diverse populations and locations of care', authors address the following themes: 'LGBTQIA+health in family medicine', 'A family medicine approach to substance use disorders', 'Shameless medicine for people experiencing homelessness', '''Difficult" encounters-finding the person behind the patient', 'Attending to patients with medically unexplained symptoms', 'Making house calls and home visits', 'Family physicians in the procedure room', 'Robust rural family medicine' and 'Full-spectrum family medicine'. May readers appreciate the breadth of family medicine in these essays.

Allogeneic platelet-rich plasma for knee osteoarthritis in patients with primary immune thrombocytopenia: A randomized clinical trial.

The treatment of painful KOA in adult patients with ITP has not been well studied yet. We conducted a prospective, double-blind, randomized, placebo-controlled trial to evaluate the efficacy of intra-articular allogeneic PRP injections on symptoms and joint structure in patients with KOA and ITP. 80 participants were randomly allocated in a 1:1 ratio to allogeneic PRP group or saline group. The primary outcome was the WOMAC total score at 12 months post-injection. The number of patients in each group who achieved MCID of primary outcome showed a statistically significant difference only at 3-month (27/39 vs. 5/39, p = 0.001) and 6-month (15/39 vs. 3/38, p = 0.032). The difference in WOMAC total score exceeded the MCID only at 3 month (mean difference of -15.1 [95% CI -20.7 to -9.5], p < 0.001). Results suggest that allogeneic PRP was superior to placebo only with respect to symptoms at 3-month of follow-up.

Adverse drug effect in the context of drug shortage: the CIRUPT prospective study from the French pharmacovigilance network.

OBJECTIVES: Drug shortages are of increasing concern to worldwide public health. The consequences of drug shortages for patient safety have been little studied, especially from a pharmacovigilance point of view. In this context, the network of French pharmacovigilance centres conducted the CIRUPT study (Conséquences Iatrogènes des RUPTures de stock/iatrogenic consequences of drug shortages) based on a prospective campaign of adverse effects occurring in the context of drug shortage notifications. METHODS: All notifications involving a shortage drug submitted to the French pharmacovigilance centres between 1 January 2020 and 30 June 2021 were collected and registered in the French national pharmacovigilance database with the standardised high level term 'product supply and availability issues' and with predefined keywords in the narrative section. RESULTS: 224 cases were included, involving mainly adverse drug reactions (ADRs) (n=131/224, 59%) and medication errors (n=51/224, 23%); 29% of the cases were serious. The most represented classes of shortage drugs were: vaccines (n=78/224, 35%); drugs for acid-related disorders (H2-receptor antagonists) (n=27/224, 12%); antineoplastic agents (n=17/224, 8%); and antiepileptics (n=15/224, 7%). In 82% of cases, the involved shortage drug was the subject of information delivered to health professionals by the National Agency for the Safety of Medicines and Health Products. Drug shortages were associated with an ADR related to replacement drugs in 59% (n=131/224) of the cases, drug inefficacy in 18% (n=41/224), and/or an aggravation of the underlying disease in 11% (n=25/224). CONCLUSIONS: From a pharmacovigilance point of view, a large diversity of anatomical therapeutic classes is involved and the risk related to drug shortages is not limited to drugs registered on 'major therapeutic interest or essential drug' lists. Information from health agencies is not sufficient to avoid the risks, and further strategies should be developed.

Investigation of the hospital pharmacy profession in Europe.

OBJECTIVE: From 1995, the European Association of Hospital Pharmacists (EAHP) has regularly investigated the progress of the hospital pharmacy profession in Europe, and identified key barriers and drivers of this. The most recent 'Investigation of the Hospital Pharmacy Profession in Europe' was conducted from November 2022 to March 2023. METHODS: The online questionnaire was sent to all hospital pharmacies in EAHP member countries. The investigation was drafted using the same questions as the 2015 baseline survey. Where possible and relevant, responses were compared with the data from previous surveys that monitored the implementation of the EAHP statements. Keele University, Centre for Medicines Optimisation, School of Pharmacy and Bioengineering, UK analysed the data. RESULTS: The overall number of responses was 653, with a better response rate of 19% compared with 14% in 2018 statements survey. The findings indicated that participating hospital pharmacies have similar characteristics to previous surveys. Section 1 (Introductory statements and governance), section 2 (Selection, procurement and distribution), section 3 (Production and compounding), section 5 (Patient safety and quality assurance) questions were generally answered positively, with results ranging from 52% to 90%. However, results for section 4 (Clinical pharmacy services) returned lower levels of positivity, with responses from 8 of the 15 questions being less than 60%. When asked what is preventing hospital pharmacists from achieving implementation of these activities, most answers were limited capacity, not considered to be a priority by managers, or other healthcare professionals do this. The last section focused on self-assessment and action planning, with fewer than 50% of positive responses; COVID-19 preparedness and vaccines with mixed positive and negative responses. Furthermore, implementation of the falsified medicines directive impacted the medication handling processes in 50% or more of the answers. Regarding sustainability, the majority (59%) of respondents felt a greater focus should be on sustainability from an organisational or management perspective. CONCLUSION: Results offer valuable insights into the hospital pharmacy profession throughout Europe. While there have been improvements in certain areas, challenges remain, particularly in implementing clinical pharmacy services. The findings provide a foundation for further dialogue, advocacy, and strategic planning to advance the role of hospital pharmacists and enhance patient care in Europe's healthcare systems.

Blockchain: What is the use case for physicians in 2024? A rapid review of the literature.

Blockchain is topical in many areas of science. The impact on clinical care of physicians is not known. We undertook a rapid review of the literature to identify areas of interest for clinicians in active practice focusing on evidence relevant to clinical care. We found limited evidence for use blockchain in clinical practice with most studies focusing on technical aspects of prototypes and implementation with no evidence of standardised metric to measure impact for patients, clinicians, and organisations. Personal Health Records for use across organisational and geographic boundaries emerged as the strongest clinical use-case. Defined metrics by professional bodies might aid research, development, and future impact.

Performance of GPT-4 in Membership of the Royal College of Paediatrics and Child Health-style examination questions.

The large language model (LLM) ChatGPT has been shown to have considerable utility across medicine and healthcare. This paper aims to explore the capabilities of GPT-4 (Generative Pre-trained Transformer 4) in answering Membership of the Royal College of Paediatrics and Child Health (MRCPCH) written paper-style questions. GPT-4 was subjected to four publicly available sample papers designed for those preparing to sit MRCPCH theory components. The model received no specialised training or reinforcement. The average score across all four papers was 78.1%. The model provided reasoning for its answers despite this not being required by the questions. This performance strengthens the case for incorporating LLMs into supporting roles for practising clinicians and medical education in paediatrics.

Performance of ChatGPT on the Chinese Postgraduate Examination for Clinical Medicine: Survey Study.

BACKGROUND: ChatGPT, an artificial intelligence (AI) based on large-scale language models, has sparked interest in the field of health care. Nonetheless, the capabilities of AI in text comprehension and generation are constrained by the quality and volume of available training data for a specific language, and the performance of AI across different languages requires further investigation. While AI harbors substantial potential in medicine, it is imperative to tackle challenges such as the formulation of clinical care standards; facilitating cultural transitions in medical education and practice; and managing ethical issues including data privacy, consent, and bias. OBJECTIVE: The study aimed to evaluate ChatGPT's performance in processing Chinese Postgraduate Examination for Clinical Medicine questions, assess its clinical reasoning ability, investigate potential limitations with the Chinese language, and explore its potential as a valuable tool for medical professionals in the Chinese context. METHODS: A data set of Chinese Postgraduate Examination for Clinical Medicine questions was used to assess the effectiveness of ChatGPT's (version 3.5) medical knowledge in the Chinese language, which has a data set of 165 medical questions that were divided into three categories: (1) common questions (n=90) assessing basic medical knowledge, (2) case analysis questions (n=45) focusing on clinical decision-making through patient case evaluations, and (3) multichoice questions (n=30) requiring the selection of multiple correct answers. First of all, we assessed whether ChatGPT could meet the stringent cutoff score defined by the government agency, which requires a performance within the top 20% of candidates. Additionally, in our evaluation of ChatGPT's performance on both original and encoded medical questions, 3 primary indicators were used: accuracy, concordance (which validates the answer), and the frequency of insights. RESULTS: Our evaluation revealed that ChatGPT scored 153.5 out of 300 for original questions in Chinese, which signifies the minimum score set to ensure that at least 20% more candidates pass than the enrollment quota. However, ChatGPT had low accuracy in answering open-ended medical questions, with only 31.5% total accuracy. The accuracy for common questions, multichoice questions, and case analysis questions was 42%, 37%, and 17%, respectively. ChatGPT achieved a 90% concordance across all questions. Among correct responses, the concordance was 100%, significantly exceeding that of incorrect responses (n=57, 50%; P<.001). ChatGPT provided innovative insights for 80% (n=132) of all questions, with an average of 2.95 insights per accurate response. CONCLUSIONS: Although ChatGPT surpassed the passing threshold for the Chinese Postgraduate Examination for Clinical Medicine, its performance in answering open-ended medical questions was suboptimal. Nonetheless, ChatGPT exhibited high internal concordance and the ability to generate multiple insights in the Chinese language. Future research should investigate the language-based discrepancies in ChatGPT's performance within the health care context.

Clinical decision support system using a machine learning model to assist simultaneous cardiopulmonary auscultation: Open-label randomized controlled trial.

Background: The utility of a clinical decision support system using a machine learning (ML) model for simultaneous cardiac and pulmonary auscultation is unknown. Objective: This study aimed to develop and evaluate an ML system's utility for cardiopulmonary auscultation. Methods: First, we developed an ML system for cardiopulmonary auscultation, using cardiopulmonary sound files from our previous study. The technique involved pre-processing, feature extraction, and classification through several neural network layers. After integration, the output class was categorized as "normal," "abnormal," or "undetermined." Second, we evaluated the ML system with 24 junior residents in an open-label randomized controlled trial at a university hospital. Participants were randomly assigned to the ML system group (intervention) or conventional auscultation group (control). During training, participants listened to four cardiac and four pulmonary sounds, all of which were correctly classified. Then, participants classified a series of 16 simultaneous cardiopulmonary sounds. The control group auscultated the sounds using noise-cancelling headphones, while the intervention group did so by watching recommendations from the ML system. Results: The total scores for correctly identified normal or abnormal cardiopulmonary sounds in the intervention group were significantly higher than those in the control group (366/384 [95.3%] vs. 343/384 [89.3%], P = 0.003). The cardiac test score in the intervention group was better (111/192 [57.8%] vs. 90/192 [46.9%], P = 0.04); there was no significant difference in pulmonary auscultation. Conclusions: The ML-based system improved the accuracy of cardiopulmonary auscultation for junior residents. This result suggests that the system can assist early-career physicians in accurate screening.

Analysis of the use of antibiotics by AWaRe categories during the COVID-19 pandemic in hospitals across Scotland: a national population-based study.

OBJECTIVE: The Access, Watch and Reserve (AWaRe) list of antibiotics was developed by the WHO to support antibiotic stewardship programmes (ASP). The Access group incorporates first-line options, while Watch antibiotics have higher resistance potential or toxicity, and Reserve drugs should be used only for complex infections. ASP implementation has been challenged during the COVID-19 pandemic. There is a knowledge gap regarding in-hospital prescribing patterns of antibiotics nationally during the COVID-19 pandemic, and on the characteristics of hospitalised patients prescribed antibiotics during this time. We aimed to evaluate quality of antibiotic use according to AWaRe classification in Scottish hospitals, including assessing the impact of COVID-19 on trends. METHODS: Cross-sectional study of antibiotics prescribed to hospitalised patients from 1 January 2019 to 30 June 2022 in a selection of Scottish hospitals, covering approximately 60% (3.6 million people) of the Scottish population. Data were obtained from the Hospital Electronic Prescribing and Medicines Administration system. Prescribing trends were explored over time, by age and by sex. RESULTS: Overall, a total 1 353 003 prescriptions were identified. An increase in Access antibiotics was found from 55.3% (31 901/57 708) to 62.3% (106 449/170 995) over the study period, alongside a decrease in Watch antibiotics from 42.9% (24 772/57 708) to 35.4% (60 632/170 995). Reserve antibiotic use was limited throughout, with minor changes over time. Changes in prescribing were most pronounced in the older age group (>65 years): proportions of Access antibiotics increased from 56.4% (19 353/34 337) to 65.8% (64 387/97 815, p<0.05), while Watch antibiotics decreased from 41.9% (14 376/34 337) to 32.3% (31 568/97 815, p<0.05) between Q1 2019 and Q2 2022. Differences between males and females were insignificant. CONCLUSIONS: Findings showed encouraging trends in Access and Watch use among hospitalised patients, in line with Scottish national standards. There was no noteworthy effect of COVID-19 on prescribing trends despite reports indicating stewardship programmes being negatively impacted by the pandemic.

Job stressors in relation to burnout and compromised sleep among academic physicians in India.

BACKGROUND: Burnout among physicians, especially in the academic setting, is an urgent concern, with adequate sleep one of the key focal points. OBJECTIVE: To identify job stressors contributing to burnout and compromised sleep among academic physicians, using a comprehensive, theory-based instrument, the Occupational Stressor Index (OSI), whose specific form was created 'for physicians by physicians'. METHODS: This parallel mixed-methods cross-sectional investigation was conducted among 109 physicians employed in a public teaching hospital, Jodhpur, India. Work conditions were evaluated by the physician-specific OSI (part I). The Copenhagen Burnout Index and Pittsburgh Sleep Quality Index (PSQI) were the outcome instruments (part II). Seventy-six physicians completed parts I and II. RESULTS: The physicians were from wide-ranging specialties, and 82% of the cohort were residents. Mean total OSI scores were 87.4±8.1, with unit-change yielding adjusted odds-ratios (95% confidence-intervals) for personal (1.10 (1.02-1.18)) and work-related burnout (1.12 (1.04-1.22)), and PSQI (1.09 (1.01-1.17)). Significant multivariable associations with burnout and/or sleep indices included: working 7 days/week, lacking work-free vacation, insufficient rest breaks, interruptions, many patients in intensive-care, no separate time for non-clinical duties, pressure to publish, injury/suicide attempts of colleagues/staff, performing pointless tasks. The latter were described as administrative/clerical. Lacking genuine rest breaks was mainly patient-related, further compromised by emergency work and lacking separate time for non-clinical duties. Long workhours and exhausting schedule were cited as most difficult parts of work, while reducing workhours, improving work schedule, and hiring more staff most frequently recommended. CONCLUSION: Specific working conditions potentially contributory to burnout and compromised sleep among physicians working in academic medicine are identified using a methodologically-rigorous, in-depth approach. These findings inform evidence-based interventions aimed at preserving physician mental health and work capacity.

Ensure the accuracy and consistency of biochemical analyzer test results: Chemometrics for instrument and inter-instrument item comparison in Chinese hospital laboratory.

Biochemical analyzers are vital instruments that utilize the principle of photoelectric colorimetry to quantify a specific chemical composition in body fluids. This analysis provides critical data for the diagnosis, treatment, prognosis, and overall health status of various diseases in clinical practice. However, the performance of a biochemical analyzer can vary significantly between different brands or over time within the same brand. Therefore, it is imperative to regularly assess the performance of the analyzer to ensure consistent results for longitudinal studies and to maintain day-to-day data consistency. Additionally, when multiple analyzers are utilized, it is necessary to evaluate the performance of each instrument to ensure accurate results across multiple platforms. In this study, we developed and verified an experimental evaluation scheme for the analytical performance of the instrument, chemometrics for biochemical analyzers, utilizing national reference materials and patient sera as the experimental subjects. We evaluated the performance of the optical system, temperature control system, sample-adding system, and detection system to confirm the feasibility of this scheme. We also compared the analytical performance of different brands of biochemical analyzers for routine biochemical tests, such as liver function, kidney function, ion, blood lipids, blood glucose, and myocardial enzyme spectrum. Using the AU 5400 as a control and the ADVIA 2400 as the comparison system, the relative variation in inter-instrument comparison data was found to be acceptable at the clinical medicine decision level. In conclusion, the performance of a biochemical analyzer can vary significantly between different brands or over time within the same brand. Regular evaluations are necessary to ensure accurate and consistent results across different analyzers. This study provides a feasible scheme for evaluating the analytical performance of biochemical analyzers that can be used to ensure the accuracy and consistency of the results of different brands of automatic chemical analyzers in the laboratory.

Emerging applications of machine learning in genomic medicine and healthcare.

The integration of artificial intelligence technologies has propelled the progress of clinical and genomic medicine in recent years. The significant increase in computing power has facilitated the ability of artificial intelligence models to analyze and extract features from extensive medical data and images, thereby contributing to the advancement of intelligent diagnostic tools. Artificial intelligence (AI) models have been utilized in the field of personalized medicine to integrate clinical data and genomic information of patients. This integration allows for the identification of customized treatment recommendations, ultimately leading to enhanced patient outcomes. Notwithstanding the notable advancements, the application of artificial intelligence (AI) in the field of medicine is impeded by various obstacles such as the limited availability of clinical and genomic data, the diversity of datasets, ethical implications, and the inconclusive interpretation of AI models' results. In this review, a comprehensive evaluation of multiple machine learning algorithms utilized in the fields of clinical and genomic medicine is conducted. Furthermore, we present an overview of the implementation of artificial intelligence (AI) in the fields of clinical medicine, drug discovery, and genomic medicine. Finally, a number of constraints pertaining to the implementation of artificial intelligence within the healthcare industry are examined.