Derivation and External Validation of the Ottawa Bloodstream Infection Model for Acutely Ill Adults.

BACKGROUND: Knowing the probability that patients have a bloodstream infection (BSI) could influence the ordering of blood cultures and interpretation of their preliminary results. Many previous BSI probability models have limited applicability and accuracy. This study used currently recommended modeling techniques and a large sample to derive and validate the Ottawa BSI Model. METHODS: At a tertiary care teaching hospital, we retrieved a random sample of 4180 adults having blood cultures in our emergency department or during the initial 48 h of the encounter. Variable selection was based on clinical experience and a systematic review of previous model performance. Model performance was measured in a temporal external validation group of 4680 patients. RESULTS: A total of 327 derivation patients had a BSI (8.0%). BSI risk increased with increased number of culture sets (2 sets: adjusted odds ratio [aOR] 1.52 [1.10-2.11]; 3 sets: 1.99 [0.86-4.58]); with indwelling catheter (aOR 2.07 [1.34-3.20); with increasing temperature, heart rate, and neutrophil-lymphocyte ratio; and with decreasing systolic blood pressure, platelet count, urea-creatinine ratio, and estimated glomerular filtration rate. In the temporal external validation group, model discrimination was good (c-statistic 0.71 [0.69-0.74]) and calibration was very good (integrated calibration index .016 [.010-.024]). Exclusion of validation patients with acute SARS-CoV-2 infection improved discrimination slightly (c-statistic 0.73 [0.69-0.76]). CONCLUSIONS: The Ottawa BSI Model uses commonly available data to return an expected BSI probability for acutely ill patients. However, it cannot exclude BSI and its complexity requires computational assistance to use.

Predictors of Noninvasive Ventilation Failure in the Post-Extubation Period: A Systematic Review and Meta-Analysis.

OBJECTIVES: To identify factors associated with failure of noninvasive ventilation (NIV) in the post-extubation period. DATA SOURCES: We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to February 28, 2022. STUDY SELECTION: We included English language studies that provided predictors of post-extubation NIV failure necessitating reintubation. DATA EXTRACTION: Two authors conducted data abstraction and risk-of-bias assessments independently. We used a random-effects model to pool binary and continuous data and summarized estimates of effect using odds ratios (ORs) mean difference (MD), respectively. We used the Quality in Prognosis Studies tool to assess risk of bias and the Grading of Recommendations, Assessment, Development and Evaluations to assess certainty. DATA SYNTHESIS: We included 25 studies ( n = 2,327). Illness-related factors associated with increased odds of post-extubation NIV failure were higher critical illness severity (OR, 3.56; 95% CI, 1.96-6.45; high certainty) and a diagnosis of pneumonia (OR, 6.16; 95% CI, 2.59-14.66; moderate certainty). Clinical and biochemical factors associated with moderate certainty of increased risk of NIV failure post-extubation include higher respiratory rate (MD, 1.54; 95% CI, 0.61-2.47), higher heart rate (MD, 4.46; 95% CI, 1.67-7.25), lower Pa o2 :F io2 (MD, -30.78; 95% CI, -50.02 to -11.54) 1-hour after NIV initiation, and higher rapid shallow breathing index (MD, 15.21; 95% CI, 12.04-18.38) prior to NIV start. Elevated body mass index was the only patient-related factor that may be associated with a protective effect (OR, 0.21; 95% CI, 0.09-0.52; moderate certainty) on post-extubation NIV failure. CONCLUSIONS: We identified several prognostic factors before and 1 hour after NIV initiation associated with increased risk of NIV failure in the post-extubation period. Well-designed prospective studies are required to confirm the prognostic importance of these factors to help further guide clinical decision-making.

Long-term exercise is needed to enhance synaptic plasticity in the hippocampus.

Exercise can have many benefits for the body, but it also benefits the brain by increasing neurogenesis, synaptic plasticity, and performance on learning and memory tasks. The period of exercise needed to realize the structural and functional benefits for the brain have not been well delineated, and previous studies have used periods of exercise exposure that range from as little as 3 d to up to 6 mo. In this study, we systematically evaluated the effects of differential running periods (3, 7, 14, 28, and 56 d) on both structural (cell proliferation and maturation) and functional (in vivo LTP) changes in the dentate gyrus of adult male Sprague-Dawley rats. We found that voluntary access to a running wheel for both short- and long-term periods can increase cell proliferation in the adult DG; however, increases in neurogenesis required longer term exposure to exercise. Increases in immature neurons were not observed until animals had been running for a minimum of 14 d. Similarly, short-term periods of wheel running did not facilitate LTP in the DG of adult animals, and reliable increases in LTP were only observed with 56 d of running. These results provide us with a greater understanding of the time course of wheel running access needed to enhance DG function. Furthermore, the results indicate that the new neurons produced in response to exercise in rats do not contribute significantly to synaptic plasticity until they mature.

Glycemic Variability As a Prognostic Factor for Mortality in Patients With Critical Illness: A Systematic Review and Meta-Analysis.

OBJECTIVES: To perform a systematic review and meta-analysis to evaluate the association of various measures of glycemic variability, including time-domain and complexity-domain, with short-term mortality in patients with critical illness. DATA SOURCES: We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to November 3, 2023. STUDY SELECTION: We included English language studies that assessed metrics of glycemic variation or complexity and short-term mortality in patients admitted to the ICU. DATA EXTRACTION: Two authors performed independent data abstraction and risk-of-bias assessments. We used a random-effects model to pool binary and continuous data and summarized estimates of effect using odds ratios and mean difference. We used the Quality in Prognosis Studies tool to assess risk of bias and the Grading of Recommendations, Assessment, Development and Evaluations to assess certainty of pooled estimates. DATA SYNTHESIS: We included 41 studies (n = 162,259). We demonstrate that increased sd, coefficient of variance, glycemic lability index, and decreased time in range are probably associated with increased mortality in critically ill patients (moderate certainty) and that increased mean absolute glucose, mean amplitude of glycemic excursion, and detrended fluctuation analysis may be associated with increased mortality (low certainty). CONCLUSIONS: We found a consistent association between increased measures of glycemic variability and higher short-term mortality in patient with critical illness. Further research should focus on standardized measurements of glycemic variation and complexity, along with their utility as therapeutic targets and prognostic markers.

Doctor-patient interactions in the age of AI: navigating innovation and expertise.

The integration of artificial intelligence (AI) in healthcare has the capacity to transform medical practice. Despite its revolutionary potential, the influence of AI may affect the physician-patient interaction and presents ethical challenges that will need to be carefully considered. This article discusses how patients may interact with this technology, considers how emerging technologies may alter the dynamics of the physician-patient relationship, and reviews some of the limitations that continue to exist. We identify potential challenges that may arise with the integration of AI into medical settings and propose solutions to help mitigate these issues.

Guiding principles and proposed classification system for the responsible adoption of artificial intelligence in scientific writing in medicine.

The integration of large language models (LLMs) and artificial intelligence (AI) into scientific writing, especially in medical literature, presents both unprecedented opportunities and inherent challenges. This manuscript evaluates the transformative potential of LLMs for the synthesis of information, linguistic enhancements, and global knowledge dissemination. At the same time, it raises concerns about unintentional plagiarism, the risk of misinformation, data biases, and an over-reliance on AI. To address these, we propose governing principles for AI adoption that ensure integrity, transparency, validity, and accountability. Additionally, guidelines for reporting AI involvement in manuscript development are delineated, and a classification system to specify the level of AI assistance is introduced. This approach uniquely addresses the challenges of AI in scientific writing, emphasizing transparency in authorship, qualification of AI involvement, and ethical considerations. Concerns regarding access equity, potential biases in AI-generated content, authorship dynamics, and accountability are also explored, emphasizing the human author's continued responsibility. Recommendations are made for fostering collaboration between AI developers, researchers, and journal editors and for emphasizing the importance of AI's responsible use in academic writing. Regular evaluations of AI's impact on the quality and biases of medical manuscripts are also advocated. As we navigate the expanding realm of AI in scientific discourse, it is crucial to maintain the human element of creativity, ethics, and oversight, ensuring that the integrity of scientific literature remains uncompromised.

Concurrent external validation of bloodstream infection probability models.

OBJECTIVE: Accurately estimating the likelihood of bloodstream infection (BSI) can help clinicians make diagnostic and therapeutic decisions. Many multivariate models predicting BSI probability have been published. This study measured the performance of BSI probability models within the same patient sample. METHODS: We retrieved validated BSI probability models included in a recently published systematic review that returned a patient-level BSI probability for adults. Model applicability, discrimination, and accuracy was measured in a simple random sample of 4485 admitted adults having blood cultures ordered in the emergency department or the initial 48 hours of hospitalization. RESULTS: Ten models were included (publication years 1991-2015). Common methodological threats to model performance included overfitting and continuous variable categorization. Restrictive inclusion criteria caused seven models to apply to <15% of validation patients. Model discrimination was less than originally reported in derivation groups (median c-statistic 60%, range 48-69). The observed BSI risk frequently deviated from expected (median integrated calibration index 4.0%, range 0.8-12.4). Notable disagreement in expected BSI probabilities was seen between models (median (25th-75th percentile) relative difference between expected risks 68.0% (28.6-113.6%)). DISCUSSION: In a large randomly selected external validation population, many published BSI probability models had restricted applicability, limited discrimination and calibration, and extensive inter-model disagreement. Direct comparison of model performance is hampered by dissimilarities between model-specific validation groups.

YAC128 Huntington's disease transgenic mice show enhanced short-term hippocampal synaptic plasticity early in the course of the disease.

Huntington's disease (HD) is a progressive and fatal neurodegenerative disorder caused by a polyglutamine expansion in the gene encoding the protein huntingtin. The disease progresses over decades, but often patients develop cognitive impairments that precede the onset of the classical motor symptoms. Similar to the disease progression in humans, the yeast artificial chromosome (YAC) 128 HD mouse model also exhibits cognitive dysfunction that precedes the onset of the neuropathological and motor impairments characteristic of HD. Thus, the purpose of this study was to evaluate whether short- and long-term synaptic plasticity in the hippocampus, two related biological models of learning and memory processes, were altered in YAC128 mice in early stages of disease progression. We show that the YAC128 hippocampal dentate gyrus (DG) displays marked reductions in paired-pulse depression both at 3 and 6 months of age. In addition, significantly enhanced post-tetanic and short-term potentiation are apparent in YAC128 mice after high-frequency stimulation at this time. Early and late forms of long-term plasticity were not altered at this stage. Together these findings indicate that there may be elevated neurotransmitter release in response to synaptic stimulation in YAC128 mice during the initial phase of disease progression. These abnormalities in short-term plasticity detected at this stage in YAC128 HD transgenic mice indicate that aberrant information processing at the level of the synapses may contribute, at least in part, to the early onset of cognitive deficits that are characteristic of this devastating neurodegenerative disorder.