Communications medicine最新文献

Background: In this study, we implemented an indoor positioning system to track the activities of healthcare professionals during their shifts in an emergency department, aiming to gain a better understanding of the emergency care production process.

Methods: An ultrawideband-based tracking system was used in an experiment at the emergency department of Le Corbusier Hospital in Firminy, France. Over a 46-day period, healthcare professionals, including assistant nurses, nurses, doctors, and managers, wore a sensor to record their location within the emergency department. We analyzed a substantial amount of quasi-real-time data to objectively assess physicians' time allocation and movement patterns and their correlation with the emergency department's occupancy. Additionally, we developed a user recognition algorithm (i.e., random forest classifier) capable of detecting the job category of the participant wearing the sensor.

Results: The proportion of time spent on care-related activities ranges from 26% to 39% for doctors. In contrast, this share reaches approximately half of the time for triage nurses and intensive care unit nurses. The burden of non-care-related activities appears to be largely induced by the time spent on administrative duties and transit. For doctors, the share of non-care-related activities is found to be correlated with the occupancy level. The hourly distance walked by nurses (except triage nurses) is found to increase with occupancy, while for doctors, the walking distance remains invariant to patient load. The random forest classifier predicts job categories with 96% accuracy.

Conclusions: Indoor tracking systems offer additional perspectives for enhancing the understanding of emergency department systems. The technology tested in this study demonstrates its potential to quantify physicians' time allocation and movements.

Background: Development of polymyxin resistance in carbapenem-resistant Klebsiella pneumoniae (CRKP) poses a severe challenge to public health. Here we aimed to perform a retrospective study of prevalence and molecular characteristics of polymyxin-resistant CRKP strains.

Methods: 4455 clinical CRKP strains from 18 provinces in China during 2000 to 2023 were collected. Polymyxin-resistant CRKP strains were subjected to antimicrobial susceptibility testing, whole genome sequencing and bioinformatic analysis. Molecular mechanisms underlying the polymyxin resistance in CRKP were analyzed.

Results: Here we show that polymyxin-resistant CRKP emerge initially in 2014, prevalence of such strains then increase steadily over the years, reaching a rate of 9.86% in 2023. In total, 112 polymyxin-resistant CRKP isolates are identified. Antimicrobial susceptibility tests show that all polymyxin-resistant CRKP are resistant to commonly used antibiotics, yet most isolates remain susceptible only to ceftazidime-avibactam and tigecycline. Predominant polymyxin resistance mechanism in CRKP is mutations in mgrB (59/112), which commonly involves disruption of mgrB by insertion of elements such as ISKpn26 (20/59), IS903B (14/59), and ISKpn14 (9/59). Phylogenetic analysis reveals frequent clonal dissemination of polymyxin-resistant CRKP within the same hospital and even among different hospitals in neighboring provinces. pLVPK-like virulence plasmids are detected in 46 isolates, such strains are therefore categorized as polymyxin and carbapenem-resistant hypervirulent K. pneumoniae which may cause infections with high mortality.

Conclusions: Our results highlight frequent clonal transmission of polymyxin-resistant CRKP within hospitals. Continuous surveillance of polymyxin resistance among CRKP should be implemented to prevent further dissemination of such strains in clinical settings in China.

Background: Flooding has emerged as the most prevalent natural disaster, impacting billions of individuals worldwide. However, the long-term effects of flooding exposure on dementia remain unclear.

Methods: With a nested case-control design, a risk-set sampling method was used to match cases and controls. Annual cumulative flooding exposure was calculated for each participant. The associations between flooding exposure and incident dementia were assessed using conditional logistic regression models.

Results: Here we show that the risk of flood-related incident dementia is the strongest in the current year and diminished over a span of 6 years. In the fully adjusted model, the cumulative odds ratios (OR) are 1.28 (95% confidence interval [CI]: 1.25-1.31) for any dementia, 1.44 (95% CI: 1.36-1.53) for Alzheimer's disease and 1.65 (95% CI: 1.48-1.83) for vascular dementia, associated with per unit increase in annual cumulative flooding exposure over lag 0-6 years. Participants under the age of 65 years (OR: 1.39, 95% CI: 1.33-1.46) and female participants (OR: 1.41, 95% CI: 1.33-1.49) exhibit a higher risk of incident dementia compared to those aged 65 years and older (OR: 1.25, 95% CI: 1.21-1.28) and male participants (OR: 1.26, 95% CI: 1.23-1.30), respectively. Similar effect estimates are observed in the stratified analyses of Alzheimer's disease according to genetic factors.

Conclusions: This study provides robust epidemiological evidence supporting the link between floods and an increased risk of dementia. These findings enhance the understanding of the long-term consequences of flood exposure.

Background: Young, healthy women carrying a pathogenic or likely pathogenic variant (P/LPV) in genes configuring the hereditary breast and/or ovarian cancer (HBOC) syndrome face several non-oncological issues. Among these, the implications on fertility are not yet entirely understood.

Methods: Aiming to explore the ovarian reserve in young, healthy women with HBOC syndrome, we conducted a monocentric, prospective, observational cohort trial between January 2020 and September 2023. Eighty-seven healthy women aged less than 42 years with a P/LPV in HBOC predisposition genes were enrolled: 32 BRCA1 P/LPV carriers, 47 BRCA2 P/LPV carriers, and 8 carriers of P/LPV in other genes (TP53, RAD50, CHECK2, RAD51D, PALB2, ATM). AMH levels and antral follicular count (AFC) were evaluated as fertility biomarkers.

Results: No significant differences in demographic characteristics or mean levels of AMH or in AFC are observed between BRCA1 and BRCA2 P/LPV carriers. The distribution of AMH values is significantly lower compared to the general population (p = 0.019). The significant decrease in AMH levels is mostly ascribable to BRCA1 P/LPV carriers (p = 0.03). Both in the overall population and in BRCA1/2 P/LPV carriers, AFC decreases faster compared to those reported in the nomogram.

Conclusions: A consistent trend for reduced reproductive potential in young, healthy women with HBOC syndrome is observed, particularly in BRCA1 P/LPV carriers. These findings need to be confirmed by larger studies including also women carrying P/LPV in other HBOC syndrome-related genes.

Background: While the value of Des-γ-carboxy prothrombin in hepatocellular carcinoma diagnosis has been widely acknowledged, whether or how Des-γ-carboxy prothrombin could be used in recurrence evaluation remains largely unexplored.

Methods: We performed a multicenter retrospective analysis including an Exploration Cohort (1074 patients, 5133 Des-γ-carboxy prothrombin measurements) and a Validation Cohort (263 patients, 612 Des-γ-carboxy prothrombin measurements) to investigate whether Des-γ-carboxy prothrombin could evaluate patients' prognosis. We introduced the Des-γ-carboxy prothrombin dynamic rate as a normalized quantitative measurement of Des-γ-carboxy prothrombin dynamic change. Des-γ-carboxy prothrombin dynamic rates were further applied in a high-risk liver cirrhosis patient cohort (PreCar Cohort, 542 liver cirrhosis patients, 2023 Des-γ-carboxy prothrombin measurements).

Results: Here, we show a post-operative decrease of Des-γ-carboxy prothrombin in the Exploration Cohort, making the Des-γ-carboxy prothrombin threshold in diagnosis unsuitable for prognosis, while Des-γ-carboxy prothrombin dynamic rates significantly associate with recurrence risk. Categorizing patients based on Des-γ-carboxy prothrombin dynamic rates and final concentrations shows that patients negative for both exhibit the best median recurrence-free survival and patients positive for both show the worst median recurrence-free survival. Patients with consistently positive status have a significantly lower median recurrence-free survival compared to those whose status reverted to negative. These findings are validated in the Validation Cohort. Furthermore, the Des-γ-carboxy prothrombin dynamic rates in the PreCar Cohort can identify an additional 28% of cirrhosis patients progressing to hepatocellular carcinoma.

Conclusions: These results expand on the clinical utilization of the hepatocellular carcinoma diagnosis biomarker, Des-γ-carboxy prothrombin, by proposing a quantification measurement of Des-γ-carboxy prothrombin dynamics to monitor hepatocellular carcinoma recurrence. This measurement is not limited in prognosis but can also improve the sensitivity of early hepatocellular carcinoma screening.

Background: Although there have been significant advancements in reducing the burden of cardiovascular disease (CVD) by modifying traditional CVD risk factors, substantial risks persist, particularly among male subjects who exhibit heightened susceptibility to atherosclerosis. In this context, we aim to study the link between oral microbiome and carotid intima media thickness (cIMT).

Methods: The Northern Finland Birth Cohort of 1966 (mean age 46 years, n = 869) underwent an extensive health examination, including the measurement of cIMT. The oral microbiome was also investigated using high-throughput 16S rRNA gene sequencing.

Results: Here we show that oral microbiome diversity links with atherosclerosis risk factors, namely smoking, glycemic balance, low-grade inflammation, and periodontitis. After excluding CVD-influencing factors (n = 339), oral microbiome genera (p = 0.030), Shannon index (p = 0.001), β-diversity Bray-Curtis (p < 0.001), and Jaccard (p < 0.001) are associated with cIMT in males, but not in the female sub-cohort. Furthermore, in the male sub-cohort (n = 131), the genera Prevotella, Megasphaera, and Veillonella associate positively with cIMT, while Absconditabacteria, Capnocytophaga, Gemella, Fusobacterium, Neisseria, Aggregatibacter, Tannerella, Treponema, Cardiobacterium, and Bacteroidales associate inversely with cIMT. We examine the involvement of serum total immunoglobulins and antibodies to phosphorylcholine (PCho) and malondialdehyde-acetaldehyde LDL (MAA-LDL) with cIMT. Subjects with high cIMT have lower levels of serum total IgA (p = 0.009), IgA to PCho (p = 0.017), and IgG to PCho (p = 0.008). The relative abundance of cIMT-associated genera correlates with serum IgA antibodies.

Conclusions: This middle-aged birth cohort study shows that male oral microbiome diversity links to cIMT, suggesting a potential sex-specific interaction between the oral microbiome and atherosclerosis.

Background: Artificial intelligence (AI), specifically Deep learning (DL), has revolutionized biomedical image analysis, but its efficacy is limited by the need for representative, high-quality large datasets with manual annotations. While latest research on synthetic data using AI-based generative models has shown promising results to tackle this problem, several challenges such as lack of interpretability and need for vast amounts of real data remain. This study aims to introduce a new approach-SYNTA-for the generation of photo-realistic synthetic biomedical image data to address the challenges associated with state-of-the art generative models and DL-based image analysis.

Methods: The SYNTA method employs a fully parametric approach to create photo-realistic synthetic training datasets tailored to specific biomedical tasks. Its applicability is tested in the context of muscle histopathology and skeletal muscle analysis. This new approach is evaluated for two real-world datasets to validate its applicability to solve complex image analysis tasks on real data.

Results: Here we show that SYNTA enables expert-level segmentation of unseen real-world biomedical data using only synthetic training data. By addressing the lack of representative and high-quality real-world training data, SYNTA achieves robust performance in muscle histopathology image analysis, offering a scalable, controllable and interpretable alternative to generative models such as Generative Adversarial Networks (GANs) or Diffusion Models.

Conclusions: SYNTA demonstrates great potential to accelerate and improve biomedical image analysis. Its ability to generate high-quality photo-realistic synthetic data reduces reliance on extensive collection of data and manual annotations, paving the way for advancements in histopathology and medical research.

Background: Appropriate management of patients with Persistent Spinal Pain Syndrome Type 2 (PSPS-T2) remains challenging. The need for robust evidence for treatment modalities is urgently pressing. The aim of this systematic review and network meta-analysis (NMA) is to compare different treatment modalities for patients with PSPS-T2 on pain intensity.

Methods: The study protocol was prospectively registered (PROSPERO;CRD42022360160). Four different databases were consulted from database inception to December 18th, 2023. Randomised controlled trials of interventions for PSPS-T2 were included. The revised Cochrane Risk of Bias Tool was used to assess risk of bias. A NMA with standardized mean differences was calculated with pairwise comparisons between all treatment modalities.

Results: Here we include 49 studies in the systematic review and 13 in NMA. A high risk of bias is indicated for 65.3% of the studies. Half of the studies investigate neuromodulation (mainly Spinal Cord Stimulation), 16 explore minimal invasive treatment options (predominantly epidural injections), 6 studies focus on conservative treatments (physiotherapy/cognitive training and medication) and 2 on reoperation. Comparison of neuromodulation versus a combination of conservative and minimal invasive options results in an effect size of 0.45 (95% CI: 0.14-0.76), clearly favouring neuromodulation (z = 2.88; p = 0.004). Additionally, neuromodulation results in a standardised mean difference of 0.36 (95% CI: 0.18-0.53) compared to placebo/sham (z = 4.03; p < 0.0001). No statistically significant difference is found between conservative options and neuromodulation.

Conclusions: Neuromodulation, followed by conservative treatment options, seems to be the most effective treatment option to obtain pain relief in patients with PSPS-T2. Nevertheless, a personalized approach tailored to individual patient needs is essential for optimizing outcomes, since interventions should be adjusted based on the failure or success of prior therapies.

Background: Artificial intelligence assistance in clinical decision making shows promise, but concerns exist about potential exacerbation of demographic biases in healthcare. This study aims to evaluate how physician clinical decisions and biases are influenced by AI assistance in a chest pain triage scenario.

Methods: A randomized, pre post-intervention study was conducted with 50 US-licensed physicians who reviewed standardized chest pain video vignettes featuring either a white male or Black female patient. Participants answered clinical questions about triage, risk assessment, and treatment before and after receiving GPT-4 generated recommendations. Clinical decision accuracy was evaluated against evidence-based guidelines.

Results: Here we show that physicians are willing to modify their clinical decisions based on GPT-4 assistance, leading to improved accuracy scores from 47% to 65% in the white male patient group and 63% to 80% in the Black female patient group. The accuracy improvement occurs without introducing or exacerbating demographic biases, with both groups showing similar magnitudes of improvement (18%). A post-study survey indicates that 90% of physicians expect AI tools to play a significant role in future clinical decision making.

Conclusions: Physician clinical decision making can be augmented by AI assistance while maintaining equitable care across patient demographics. These findings suggest a path forward for AI clinical decision support that improves medical care without amplifying healthcare disparities.