European Journal of Internal Medicine最新文献

Ischemia with non-obstructive coronary arteries (INOCA) is an increasingly recognized entity. It encompasses different pathophysiological subtypes (i.e., endotypes), including coronary microvascular dysfunction (CMD), vasospastic angina (VSA) and mixed entities resulting from the variable combination of both. Diagnosing INOCA and precisely characterizing the endotype allows for accurate medical treatment and has proven prognostic implications.

A breadth of diagnostic technique is available, ranging from non-invasive approaches to invasive coronary angiography adjuvated by functional assessment and provocative tests. This review summarizes the strength and limitations of these methodologies and provides the rationale for the routine referral for invasive angiography and functional assessment in this subset of patients.

Background

There is a lack of consensus in evaluating multidimensional sleep health, especially concerning its implication for mortality. A validated multidimensional sleep health score is the foundation of effective interventions.

Methods

We obtained data from 5706 participants in the Sleep Heart Health Study. First, random forest-recursive feature elimination algorithm was used to select potential predictive variables. Second, a sleep composite score was developed based on the regression coefficients from a Cox proportional hazards model evaluating the associations between selected sleep-related variables and mortality. Last, we validated the score by constructing Cox proportional hazards models to assess its association with mortality.

Results

The mean age of participants was 63.2 years old, and 47.6% (2715/5706) were male. Six sleep variables, including average oxygen saturation (%), spindle density (C3), sleep efficiency (%), spindle density (C4), percentage of fast spindles (%) and percentage of rapid eye movement (%) were selected to construct this multidimensional sleep health score. The average sleep composite score in participants was 6.8 of 22 (lower is better). Participants with a one-point increase in sleep composite score had an 10% higher risk of death (hazard ratio = 1.10, 95% confidence interval: 1.08–1.12).

Conclusions

This study constructed and validated a novel multidimensional sleep health score to better predict death based on sleep, with significant associations between sleep composite score and all-cause mortality. Integrating questionnaire information and sleep microstructures, our sleep composite score is more appropriately applied for mortality risk stratification.

Background

The increasing admissions of very elderly patients to intensive care units (ICUs) over recent decades highlight a growing need for understanding acute kidney injury (AKI) in this population. Although these individuals are potentially at high risk for AKI and adverse outcomes, data on AKI in this population is scarce. This study investigates the AKI incidence and outcomes of critically-ill patients aging at least 90 years.

Methods

This retrospective cohort study conducted at the Department of Intensive Care Medicine, University Medical Centre Hamburg-Eppendorf, Germany (2008–2020), investigates AKI incidence and outcomes between 2008 and 2020 in critically-ill patients aged ≥ 90 years. AKI was defined according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria using creatinine dynamics and/or urine output. Primary endpoint was overall mortality after 1 year. Secondary endpoints were in-hospital mortality, length of ICU and hospital stay.

Results

During the study period 92,958 critically-ill patients were treated and 1108 were ≥ 90 years. Of these, 1054 patients had available creatinine values and were included in the present study. AKI occurred in 24.4%, mostly classified as mild (17.5%). AKI was independently associated with a significant increase in overall mortality (HR 1.21, 95 %-CI: 1.01–1.46), in-hospital mortality (OR 2, 1.41–2.85), length of ICU (+2.8 days, 2.3–3.3) and hospital stay (+2.3 days, 0.9–3.7). Severity escalated these effects, but even mild AKI showed significance. Introducing urine-based criteria increased incidence but compromised mortality prediction.

Conclusions

AKI is a frequent complication in very elderly critically-ill patients. Occurrence of AKI at any stage was associated with increased mortality. Predictive ability applied to AKI defined by creatinine but not urine output. Careful attention of creatinine dynamics is essential in very elderly ICU-patients.

Background

The increasing prevalence of alcohol use disorder (AUD) and the parallel surge in alcohol-associated liver disease (ALD) emphasize the urgent need for comprehensive alcohol management strategies. Low-dose ondansetron (AD04, a 5-HT3 antagonist) was shown recently to be a promising treatment for AUD with a specific genotypic profile (5-marker). The liver safety of AD04 has never been evaluated in subjects with AUD. The aim of the present study was to assess the liver safety profile of AD04 compared with placebo in subjects with AUD.

Methods

Liver biochemical parameters were assessed in subjects with AUD with a 5-marker genetic profile who participated in a Phase 3 randomized controlled trial and received either twice-daily, low-dose AD04 (ondansetron 0.33 mg twice daily) or matching placebo, combined with brief psychosocial counseling. ALT, AST, GGT, Serum Bilirubin, MCV, and Prothrombin were evaluated at weeks 0, 12, and 24. Adverse cardiac events, general well-being, and study completion were also assessed.

Results

Low-dose AD04 did not significantly change biochemical markers of liver injury, such as ALT, AST, and Serum Bilirubin. While patients with AUD displayed elevated GGT levels, typically associated with increased alcohol consumption, this parameter remained unaffected by low-dose AD04. Notably, no significant adverse effects were observed due to oral low-dose AD04 treatment.

Conclusions

Low-dose AD04 has the potential to be a safe treatment option for subjects with AUD and ALD, indicating the need for an RCT for this specific cohort. Such a trial would pave the way for the design of a precision treatment for combined AUD with ALD.

The debate surrounding the integration of artificial intelligence (AI) into scientific writing has already attracted significant interest in medical and life sciences. While AI can undoubtedly expedite the process of manuscript creation and correction, it raises several criticisms. The crossover between AI and health sciences is relatively recent, but the use of AI tools among physicians and other scientists who work in the life sciences is growing very fast. Within this whirlwind, it is becoming essential to realize where we are heading and what the limits are, including an ethical perspective.

Modern conversational AIs exhibit a context awareness that enables them to understand and remember any conversation beyond any predefined script. Even more impressively, they can learn and adapt as they engage with a growing volume of human language input. They all share neural networks as background mathematical models and differ from old chatbots for their use of a specific network architecture called transformer model [1]. Some of them exceed 100 terabytes (TB) (e.g., Bloom, LaMDA) or even 500 TB (e.g., Megatron-Turing NLG) of text data, the 4.0 version of ChatGPT (GPT-4) was trained with nearly 45 TB, but stays updated by the internet connection and may integrate with different plugins that enhance its functionality, making it multimodal.