Frontiers in Medicine最新文献

Introduction: Healthcare workers' well-being is of utmost importance given persistent high rates of burnout, which also affects quality of care. Minority healthcare workers (MHCW) face unique challenges including structural racism and discrimination. There is limited data on interventions addressing the psychological well-being of MHCW. Thus, this systematic review aims to identify interventions specifically designed to support MHCW well-being, and to compare measures of well-being between minority and non-minority healthcare workers.

Methods: We searched multiple electronic databases. Two independent reviewers conducted literature screening and extraction. The Mixed Methods Assessment Tool (MMAT) or Joanna Briggs Institute (JBI) criteria were utilized to assess the methodological quality of studies, based on the study design. Total scores as percentages of criteria met were used to determine overall quality as low (<40%), moderate (40-80%), or high (>80%). For conflicts, consensus was reached through discussion. Meta-analysis was not possible due to heterogeneity of study designs.

Results: A total of 3,816 records were screened and 43 were included in the review. The majority of included studies (76.7%) were of moderate quality. There were no randomized control trials and only one study included a well-being intervention designed specifically for MHCW. Most (67.4%) were quantitative-descriptive studies that compared well-being measures between minority and non-minority identifying healthcare workers. Common themes identified were burnout, job retention, job satisfaction, discrimination, and diversity. There were conflicting results regarding burnout rates in MHCW vs non-minority workers with some studies citing protective resilience and lower burnout while others reported greater burnout due to compounding systemic factors.

Discussion: Our findings illuminate a lack of MHCW-specific well-being programs. The conflicting findings of MHCW well-being do not eliminate the need for supports among this population. Given the distinct experiences of MHCW, the development of policies surrounding diversity and inclusion, mental health services, and cultural competency should be considered. Understanding the barriers faced by MHCW can improve both well-being among the healthcare workforce and patient care.

Background: Abdominal pain is a common clinical symptom, and the role of small bowel capsule endoscopy (SBCE) in the evaluation of abdominal pain remains a subject of ongoing debate. The objective of this study is to investigate the factors influencing the efficacy of SBCE in patients with chronic abdominal pain.

Methods: This study retrospectively analyzed the medical records of patients presenting with chronic abdominal pain as the primary complaint who underwent SBCE at Renji Hospital from January 2014 and January 2023. Data collection included patient demographics and relevant influencing factors, such as hospitalization status, anemia, elevated inflammatory markers, hypertension, and diabetes. Univariate and multivariate analyses were employed to examine the factors associated with SBCE transit status and positive outcomes.

Results: A total of 524 patients were included in the study, of whom 113 presented with DUGT and received conservative observation, pharmacological treatment, or endoscopic intervention as appropriate. The overall completion rate was 97.1%. Hospitalization status, diabetes, and anemia were identified as risk factors for DUGT in multivariate analyses. Positive lesions were detected in 160 cases, yielding an overall lesion detection rate of 30.5%. Furthermore, multivariate regression analysis indicated that anemia (hemoglobin <90 g/L) and elevated inflammatory markers were associated with a higher rate of positivity.

Conclusion: In conclusion, our study found that hospitalization status, diabetes, and anemia as significant risk factors for DUGT in patients with chronic abdominal pain. Furthermore, we found that SBCE is highly effective in detecting lesions in patients with chronic abdominal pain combined with anemia and elevated inflammatory markers.

Chronic atrophic gastritis (CAG) is considered to be closely related to Helicobacter pylori (H. pylori) infection and characterized by the atrophy and/or intestinal metaplasia (IM) of the gastric mucosa in pathology. CAG is often regarded as the precancerous lesion of gastric cancer and H. pylori infection stimulates the development of atrophy and IM and the progression of gastric cancer through the persistent effect acting on the gastric mucosa, including releasing inflammatory factors such as Interleukin-8(IL-8). From the molecular biology perspective, growing evidence shows that H. pylori probably induce the expression of NF-κB, miR-204, miR-27a, hnRNPA2B1, and JARID1B, which play crucial roles in the progression of CAG into gastric cancer. In addition, H. pylori can increase Epstein-Barr virus (EBV) infection, and the co-infection will jointly increase gastric cancer risk. Furthermore, H. pylori induces cellular senescence and promotes atrophy progression and finally increases the gastric cancer risk. This review aims to explore the carcinogenic mechanisms of H. pylori related CAG in order to provide theoretical foundations for the pathogenesis mechanism and early detection and prevention of gastric cancer.

Background: The prognostic prediction of patients with hypercapnic respiratory failure holds significant clinical value. The objective of this study was to develop and validate a predictive model for predicting survival in patients with hypercapnic respiratory failure.

Methods: The study enrolled a total of 697 patients with hypercapnic respiratory failure, including 565 patients from the First People's Hospital of Yancheng in the modeling group and 132 patients from the People's Hospital of Jiangsu Province in the external validation group. The three selected models were random survival forest (RSF), DeepSurv, a deep learning-based survival prediction algorithm, and Cox Proportional Risk (CoxPH). The model's predictive performance was evaluated using the C-index and Brier score. Receiver operating characteristic curve (ROC), area under ROC curve (AUC), and decision curve analysis (DCA) were employed to assess the accuracy of predicting the prognosis for survival at 6, 12, 18, and 24 months.

Results: The RSF model (c-index: 0.792) demonstrated superior predictive ability for the prognosis of patients with hypercapnic respiratory failure compared to both the traditional CoxPH model (c-index: 0.699) and DeepSurv model (c-index: 0.618), which was further validated on external datasets. The Brier Score of the RSF model demonstrated superior performance, consistently measuring below 0.25 at the 6-month, 12-month, 18-month, and 24-month intervals. The ROC curve confirmed the superior discrimination of the RSF model, while DCA demonstrated its optimal clinical net benefit in both the modeling group and the external validation group.

Conclusion: The RSF model offered distinct advantages over the CoxPH and DeepSurv models in terms of clinical evaluation and monitoring of patients with hypercapnic respiratory failure.

Background: The Value Proposition (VP) in diagnostic technology serves as a "positioning statement" outlining the unique benefits, costs, and differentiation an innovation under development offers to healthcare organizations and its ability to effectively deliver these advantages in comparison to current interventions in the market. Despite its significance however, VP lacks a universally accepted definition, which is compounded by the diversity of technologies, their applications, and the varying needs of stakeholders. This paper aims to address this gap by offering a detailed conceptual analysis, revised definition of VP, and actionable recommendations for advancing VP development.

Methodology: We conducted a targeted narrative review, focusing on literature explicitly defining VPs in diagnostic technologies. Using Ovid's Medline and Embase databases, we identified 19 relevant papers, of which only 5 provided explicit VP definitions. Our analysis incorporated principles of team science, encompassing reflective and thematic analyses of (1) interdisciplinary co-author discussions enabling us to weave together diverse insights into a cohesive exploration of the topic, and (2) MTech's publicly available set of anonymised responses from NHS Associates, to capture the perspectives of the decision-makers and further enhance depth and breadth of our discourse.

Results and discussion: Our findings highlight the multifaceted nature of VP and its primary hurdles: inadequate identification of unmet needs and insufficient recognition of key stakeholders. We synthesized the evolution of VP definitions and explored the importance of unmet needs in their development, guided by frameworks, such as the Health Technology Navigation Pathway Tool, to ensure VPs meet both the pragmatic and aspirational goals of the healthcare. Thematic insights revealed opportunities for addressing these barriers through implementation science and collaborative strategies. This multi-perspective approach provided a conceptual examination of VP, enabling integration of varied viewpoints and insights.

Conclusion: By employing team science principles and reflective analysis, we introduced a revised definition of VP and a set of actionable recommendations to guide VP development in diagnostics. These findings highlight the importance of addressing stakeholder diversity, unmet needs, and the intricacies of blending interdisciplinary perspectives to advance the field.

Background: Metabolic dysfunction-associated steatotic liver disease, a prevalent chronic liver condition, can cause severe complications like hepatitis, cirrhosis, and hepatocellular carcinoma. In recent years, glucagon-like peptide-1 receptor agonists (GLP - 1RA) have shown unique therapeutic advantages and may become a preferred treatment for it. This meta-analysis aims to systematically examine GLP-1RA associated adverse events, providing a basis for guiding patient clinical management.

Methods: We conducted a search for randomized controlled trials (RCTs) investigating the therapeutic effects of GLP-1RA in the treatment of metabolic dysfunction-associated steatotic liver disease across four databases: PubMed, Embase, Web of Science, and Cochrane Library. The search period extended from the inception of each database until December 2023. Information pertaining to various adverse events was collected as outcome measures. Statistical analysis of the results and assessment of bias risk were conducted utilizing Review Manager (version 5.4.1) software.

Results: An analysis of 10 studies encompassing 960 participants revealed a significantly higher overall incidence of adverse events in the GLP-1RA group compared to the control group (OR: 2.40 [1.10, 5.26], P = 0.03). Subgroup analysis based on treatment duration demonstrated a higher rate of adverse events in the GLP-1RA group during follow-ups of less than 30 weeks (P = 0.0005, OR: 3.58 [1.75, 7.32]), but no statistical difference was observed between the two groups in follow-ups exceeding 30 weeks. There was no statistically significant difference between the two groups in adverse events leading to discontinuation (P = 0.29, OR: 1.47 [0.72, 2.98]). However, a notable difference was observed in gastrointestinal adverse events (P < 0.00001, OR: 4.83 [3.36, 6.95]).

Conclusion: GLP-1RA exhibits an overall higher incidence of adverse events in the treatment of metabolic dysfunction-associated steatotic liver disease, particularly in the gastrointestinal domain. Short-term use of GLP-1RA may be associated with a greater occurrence of adverse events, underscoring the importance of educating patients on preventive measures and establishing tolerance. However, there was no statistically significant difference between the two groups in severe adverse events and adverse events leading to discontinuation, confirming the safety profile of GLP-1RA application.

Objective: The main purpose of this bibliometric study is to compile the rapidly increasing articles in the field of perinatology in recent years and to shed light on the research areas where studies are concentrated.

Materials and methods: This bibliometric study was conducted using the Thomson ISI Web of Science Core Collection (WOSCC) system on May 4, 2024, with specific keywords. The abstracts of 1,124 articles that met the criteria were reviewed, and 382 articles related to perinatology were evaluated. Keyword co-occurrence, co-citation of authors, and co-citation of references analyses were conducted using VOSviewer (version 1.6.19). Out of these, 121 articles with 10 or more citations were analyzed in terms of their content and categorized under the headings "Purpose of Evaluation," "Medical Methods and Parameters Used," "Output To Be Evaluated," and "Fetal System or Region Being Evaluated."

Results: In this bibliometric study, it was found that the most frequently published journal among the 382 examined articles was Medical Image Analysis, while the journals with the most publications in the field of perinatology were Prenatal Diagnosis and Ultrasound in Obstetrıcs & Gynecology. The most commonly used keyword was "deep learning" (115/382). Among the 121 highly cited articles, the most common purpose of evaluation was "Prenatal Screening." Artificial intelligence was most frequently used in ultrasound (59.8%) imaging, with MRI (20.5%) in second place. Among the evaluated outputs, "organ scanning" (35/121) was in first place, while "biometry" (34/121) was in second place. In terms of evaluated systems and organs, "growth screening" (35/121) was the most common, followed by the "neurological system" (33/121) and then the "cardiovascular system" (18/121).

Conclusion: I has witnessed the increasing influence of artificial intelligence in the field of perinatology in recent years. This impact may mark the historic beginning of the transition to the AI era in perinatology. Milestones are being laid on the path from prenatal screening to prenatal treatment.