BACKGROUND: During the Covid-19 pandemic, family visitation to intensive care was severely restricted. In response, family communication moved to remote-only options. The effect on patients and families of this communication change is poorly understood.
OBJECTIVE: The aim of this review was to synthesise the available research on remote-only communication interventions and their effect on patient and family outcomes within the intensive care environment.
METHODS: A systematic review of relevant studies was undertaken.
METHODS: Databases included CINAHL, APA PsychINFO, MEDLINE, and Ovid Embase.
METHODS: Databases were searched with a date restriction of June 1st, 2011, to June 1st, 2023. Two independent reviewers assessed each study using the Mixed Methods Appraisal Tool, version 2 of the Cochrane risk-of-bias tool for randomised controlled trials, and the Risk Of Bias In Nonrandomised Studies of Interventions tool for methodological quality and risk of bias. Of the 2292 articles screened, 10 studies met the inclusion criteria.
RESULTS: Ten studies were included (n = 3861). Methodological quality was mostly poor, with one study evaluated as high on Mixed Methods Appraisal Tool quality criteria. Two themes were derived from the literature: (i) patient and family satisfaction; and (ii) patient and family psychological distress symptoms. Five studies reported patient and family satisfaction, with four studies finding statistically significant improvement following the communication intervention. However, only one of the five studies specifically evaluated the satisfaction with the communication intervention. Nine studies reported patient and family psychological distress symptoms, using 12 measurement tools. A variable effect of interventions was found within this theme.
CONCLUSIONS: This review identified important gaps in the research examining remote-only family communication interventions in intensive care. Inconsistent delivery of remote-only communication interventions, biased research methods, and variable outcome measurement tools impacted the reliability and validity of current evidence. Further research on remote-only communication interventions and the effect on families is recommended.

OBJECTIVE: The US Agency for Healthcare Research and Quality (AHRQ), through the Evidence-based Practice Center (EPC) Program, aims to provide health system decision makers with the highest-quality evidence to inform clinical decisions. However, limitations in the literature may lead to inconclusive findings in EPC systematic reviews (SRs). The EPC Program conducted pilot projects to understand the feasibility, benefits, and challenges of utilizing health system data to augment SR findings to support confidence in healthcare decision-making based on real-world experiences.
METHODS: Three contractors (each an EPC located at a different health system) selected a recently completed systematic review conducted by their center and identified an evidence gap that electronic health record (EHR) data might address. All pilot project topics addressed clinical questions as opposed to care delivery, care organization, or care disparities topics that are common in EPC reports. Topic areas addressed by each EPC included infantile epilepsy, migraine, and hip fracture. EPCs also tracked additional resources needed to conduct supplemental analyses. The workgroup met monthly in 2022-2023 to discuss challenges and lessons learned from the pilot projects.
RESULTS: Two supplemental data analyses filled an evidence gap identified in the systematic reviews (raised certainty of evidence, improved applicability) and the third filled a health system knowledge gap. Project challenges fell under three themes: regulatory and logistical issues, data collection and analysis, and interpretation and presentation of findings. Limited ability to capture key clinical variables given inconsistent or missing data within the EHR was a major limitation. The workgroup found that conducting supplemental data analysis alongside an SR was feasible but adds considerable time and resources to the review process (estimated total hours to complete pilot projects ranged from 283-595 across EPCs), and that the increased effort and resources added limited incremental value.
CONCLUSIONS: Supplementing existing systematic reviews with analyses of EHR data is resource intensive and requires specialized skillsets throughout the process. While using EHR data for research has immense potential to generate real-world evidence and fill knowledge gaps, these data may not yet be ready for routine use alongside systematic reviews.

OBJECTIVE: To synthesise qualitative evidence on clinicians\' views and experiences of defensive practice.
METHODS: Systematic review of qualitative data.
METHODS: MEDLINE, Embase, PsycINFO, AMED, Maternity and Infant Care, CINAHL, ASSIA, Sociological Abstracts, Proquest Dissertations & Theses and PROSPERO were searched from 2000 to October 2023.
METHODS: We included English-language studies of clinicians which reported qualitative data on the impact of litigation or complaints on clinical practice.
METHODS: We coded findings data line by line using a grounded theory approach. We assessed quality using Hawker et al\'s tool and synthesised data thematically.
RESULTS: 17 studies were included. Participants identify a range of clinical decisions which may be defensively motivated, relating to diagnosis and documentation as well as to treatment. Defensive practice often relates to a diffuse sense of risk rather than the direct threat of litigation and may overlap with other motivations, such as perceived pressure from patients or the desire to avoid harm. Defensive practice is seen to be harmful in many ways, but again, these perceptions may gain force from broader narratives of mistrust and disempowerment, as much as from the risk of litigation.
CONCLUSIONS: The idea of defensive practice, as enacted, is more complex than some theoretical accounts suggest and may often function to express broader concerns about the work of clinical care. The qualitative evidence calls into question the view of defensive practice as a key mediator linking litigation risk to inappropriate treatment and excess costs.

BACKGROUND: This systematic review aims to assist clinical decision-making in selecting appropriate preoperative prediction methods for difficult tracheal intubation by identifying and synthesizing literature on these methods in adult patients undergoing all types of surgery.
METHODS: A systematic review and meta-analysis were conducted following PRISMA guidelines. Comprehensive electronic searches across multiple databases were completed on March 28, 2023. Two researchers independently screened, selected studies, and extracted data. A total of 227 articles representing 526 studies were included and evaluated for bias using the QUADAS-2 tool. Meta-Disc software computed pooled sensitivity (SEN), specificity (SPC), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). Heterogeneity was assessed using the Spearman correlation coefficient, Cochran\'s-Q, and I2 index, with meta-regression exploring sources of heterogeneity. Publication bias was evaluated using Deeks\' funnel plot.
RESULTS: Out of 2906 articles retrieved, 227 met the inclusion criteria, encompassing a total of 686,089 patients. The review examined 11 methods for predicting difficult tracheal intubation, categorized into physical examination, multivariate scoring system, and imaging test. The modified Mallampati test (MMT) showed a SEN of 0.39 and SPC of 0.86, while the thyromental distance (TMD) had a SEN of 0.38 and SPC of 0.83. The upper lip bite test (ULBT) presented a SEN of 0.52 and SPC of 0.84. Multivariate scoring systems like LEMON and Wilson\'s risk score demonstrated moderate sensitivity and specificity. Imaging tests, particularly ultrasound-based methods such as the distance from the skin to the epiglottis (US-DSE), exhibited higher sensitivity (0.80) and specificity (0.77). Significant heterogeneity was identified across studies, influenced by factors such as sample size and study design.
CONCLUSIONS: No single preoperative prediction method shows clear superiority for predicting difficult tracheal intubation. The evidence supports a combined approach using multiple methods tailored to specific patient demographics and clinical contexts. Future research should focus on integrating advanced technologies like artificial intelligence and deep learning to improve predictive models. Standardizing testing procedures and establishing clear cut-off values are essential for enhancing prediction reliability and accuracy. Implementing a multi-modal predictive approach may reduce unanticipated difficult intubations, improving patient safety and outcomes.

OBJECTIVE: Billions of vascular access devices (VADs) are inserted annually for intravenous therapy worldwide. However, their use is not without challenges. Facilitating the process and enhancing results, hospital authorities have created vascular access specialist teams (VASTs) with advanced competencies in the evaluation, insertion, care and management of VADs. The objective is to compare the effectiveness of VASTs versus standard practice regarding cannulation success and vascular access maintenance in hospitalised adults.
METHODS: Systematic review, using the Mixed Methods Appraisal Tool.
METHODS: We conducted a structured data search on Cochrane Library, MEDLINE, Web of Science, Scopus and EBSCOhost up to 31 May 2023. We did not impose a time limit regarding the date of publication.
METHODS: Studies were eligible for inclusion in the review if they were randomised and non-randomised trials and observational studies.
METHODS: We included studies that described or evaluated the activity of VASTs compared with clinical practitioners. The outcomes analysed were the success of the cannulation and the incidence of associated adverse effects.
RESULTS: The search strategy produced 3053 papers published between 1984 and 2020, from which 12 were selected for analysis. VASTs are heterogeneously described among these studies, which mainly focus on insertions, frequently for patients with difficult intravenous access. Some patients presented with specific needs or requirement for specific insertion technique or catheter type. Compared with usual practice, these studies indicate that the involvement of a VAST is associated with a higher effectiveness in terms of first attempt insertions and insertion success rates, and a reduction in catheter-associated adverse events. However, meta-analyses confirming this trend are not currently possible.
CONCLUSIONS: It seems apparent that VASTS contribute to improving the health of patients during the administration of intravenous. VASTs seem to increase the effectiveness of VAD insertion and care and reduce complications.
UNASSIGNED: CRD42021231259.

OBJECTIVE: Research indicates that people with lower socioeconomic status (SES) receive inferior healthcare and experience poorer health outcomes compared with those with higher SES, in part due to health professional (HP) bias. We conducted a scoping review of the impact of HP bias about SES on clinical decision-making and its effect on the care of adults with lower SES.
METHODS: JBI scoping review methods were used to perform a systematic comprehensive search for literature. The scoping review protocol has been published in BMJ Open.
METHODS: Medline, Embase, ASSIA, Scopus and CINAHL were searched, from the first available start date of the individual database to March 2023. Two independent reviewers filtered and screened papers.
METHODS: Studies of all designs were included in this review to provide a comprehensive map of the existing evidence of the impact of HP bias of SES on clinical decision-making and its effect on the care for people with lower SES.
METHODS: Data were gathered using an adapted JBI data extraction tool for systematic scoping reviews.
RESULTS: Sixty-seven papers were included from 1975 to 2023. 35 (73%) of the included primary research studies reported an association between HP SES bias and decision-making. Thirteen (27%) of the included primary research studies did not find an association between HP SES bias and decision-making. Stereotyping and bias can adversely affect decision-making when the HP is fatigued or has a high cognitive load. There is evidence of intersectionality which can have a powerful cumulative effect on HP assessment and subsequent decision-making. HP implicit bias may be mitigated through the assertiveness of the patient with low SES.
CONCLUSIONS: HP decision-making is at times influenced by non-medical factors for people of low SES, and assumptions are made based on implicit bias and stereotyping, which compound or exacerbate health inequalities. Research that focuses on decision-making when the HP has a high cognitive load, would help the health community to better understand this potential influence.

Artificial intelligence (AI) is transforming spinal imaging and patient care through automated analysis and enhanced decision-making. This review presents a clinical task-based evaluation, highlighting the specific impact of AI techniques on different aspects of spinal imaging and patient care. We first discuss how AI can potentially improve image quality through techniques like denoising or artifact reduction. We then explore how AI enables efficient quantification of anatomical measurements, spinal curvature parameters, vertebral segmentation, and disc grading. This facilitates objective, accurate interpretation and diagnosis. AI models now reliably detect key spinal pathologies, achieving expert-level performance in tasks like identifying fractures, stenosis, infections, and tumors. Beyond diagnosis, AI also assists surgical planning via synthetic computed tomography generation, augmented reality systems, and robotic guidance. Furthermore, AI image analysis combined with clinical data enables personalized predictions to guide treatment decisions, such as forecasting spine surgery outcomes. However, challenges still need to be addressed in implementing AI clinically, including model interpretability, generalizability, and data limitations. Multicenter collaboration using large, diverse datasets is critical to advance the field further. While adoption barriers persist, AI presents a transformative opportunity to revolutionize spinal imaging workflows, empowering clinicians to translate data into actionable insights for improved patient care.

Positron emission tomography (PET) imaging has moved forward the development of medical diagnostics and research across various domains, including cardiology, neurology, infection detection, and oncology. The integration of machine learning (ML) algorithms into PET data analysis has further enhanced their capabilities of including disease diagnosis and classification, image segmentation, and quantitative analysis. ML algorithms empower researchers and clinicians to extract valuable insights from complex big PET datasets, which enabling automated pattern recognition, predictive health outcome modeling, and more efficient data analysis. This review explains the basic knowledge of PET imaging, statistical methods for PET image analysis, and challenges of PET data analysis. We also discussed the improvement of analysis capabilities by combining PET data with machine learning algorithms and the application of this combination in various aspects of PET image research. This review also highlights current trends and future directions in PET imaging, emphasizing the driving and critical role of machine learning and big PET image data analytics in improving diagnostic accuracy and personalized medical approaches. Integration between PET imaging will shape the future of medical diagnosis and research.

Lower extremity peripheral artery disease (PAD) often results from atherosclerosis, and is highly prevalent in patients with type 2 diabetes mellitus (T2DM). Individuals with T2DM exhibit a more severe manifestation and a more distal distribution of PAD compared to those without diabetes, adding complexity to the therapeutic management of PAD in this particular patient population. Indeed, the management of PAD in patients with T2DM requires a multidisciplinary and individualized approach that addresses both the systemic effects of diabetes and the specific vascular complications of PAD. Hence, cardiovascular prevention is of the utmost importance in patients with T2DM and PAD, and encompasses smoking cessation, a healthy diet, structured exercise, careful foot monitoring, and adherence to routine preventive treatments such as statins, antiplatelet agents, and angiotensin-converting enzyme inhibitors or angiotensin receptor blockers. It is also recommended to incorporate glucagon-like peptide-1 receptor agonists (GLP-1RA) and sodium-glucose cotransporter-2 inhibitors (SGLT2i) in the medical management of patients with T2DM and PAD, due to their demonstrated cardiovascular benefits. However, the specific impact of these novel glucose-lowering agents for individuals with PAD remains obscured within the background of cardiovascular outcome trials (CVOTs). In this review article, we distil evidence, through a comprehensive literature search of CVOTs and clinical guidelines, to offer key directions for the optimal medical management of individuals with T2DM and lower extremity PAD in the era of GLP-1RA and SGLT2i.

Simulation-based education methods improve nursing students\' clinical decision-making skills. It allows students to experience situations they may not encounter in a real clinical environment.
The aim of this systematic review was to better understand the effectiveness of simulation-based education on clinical decision-making skills in undergraduate nursing students.
Meta-analysis of randomized controlled trials and quasi-experimental studies.
The review included fourteen studies obtained by scanning the PubMed, EBSCO (Medline, CINAHL), OVID, Web of Science, and Cochrane databases.
Three authors independently screened the literature, extracted data, and assessed the quality of the included studies. The methodological quality of the studies was assessed with the Critical Appraisal Checklists for experimental and quasi-experimental studies developed by the Joanna Briggs Institute. Standardized mean difference with 95 % confidence interval was used to facilitate direct comparisons between studies. All statistical tests were performed with Review Manager 5.4 software.
In this study, 1614 records were reached as a result of the first screening. After examining the titles and removing duplicate articles and other articles that did not meet the research criteria according to the abstracts, 48 articles were included in the full-text analysis. Three researchers read the studies (n = 48) eligible for evaluation, and 14 (n = 14) studies suitable for full-text review met all of the listed inclusion criteria and were included in the meta-analysis.
The analysis revealed that simulation-based educational practices appeared to improve undergraduate nursing students\' clinical decision-making skills.