Serological diagnosis of strongyloidiasis: An evaluation of three commercial assays.

BACKGROUND: Strongyloidiasis is caused by a neglected nematode, manifesting as chronic intestinal infection with potentially severe manifestations. The disease is an emerging problem in non-endemic countries affecting travelers and migrants. Diagnosis of strongyloidiasis is hampered by the lack of standardization and absence of a gold standard. Since adequate direct methods to detect the motile larvae in stool samples are not widely available, other techniques such as serology have been developed. METHODS: We evaluated three commercial ELISA kits (DRG Instruments, IVD Research, and Bordier Affinity Products) to detect IgG antibodies against Strongyloides stercoralis assays utilizing serum samples from travelers with microscopically confirmed strongyloidiasis (n = 50) and other imported helminthic infections (n = 159) as well as healthy controls (n = 50). RESULTS: The DRG, IVD, and Bordier assays showed sensitivities of 58.0%, 64.0%, and 56.0%, respectively. Specificity values were 96.0%, 96.0%, and 92.0% in healthy controls, and 67.3%, 62.9%, and 76.7% in cases with other helminth infections, respectively. Cross-reactions were mostly observed in cases with other nematodes (37.5%, 42.5%, and 20.0%, respectively), but also in trematode (33.3%, 38.1%, and 19.0%, respectively) and in cestode infections (25.0%, 30.0%, and 32.5%, respectively). CONCLUSION: The study demonstrates the diagnostic limitations of serological assays to detect or exclude cases of strongyloidiasis in returning travelers, who frequently present with recent or acute infections.

Fulfilling last wishes: improving the compassionate discharge process.

BACKGROUND: Compassionate discharges (ComD), commonly known as rapid discharges, are urgent one-way discharges for critically ill hospitalised patients with death expected within hours or less than 7 days, to die at their place of choice-usually in their own home. Challenges abound in this time-sensitive setting when multiple parties must work together to prepare medically unstable patients for discharge, yet healthcare staff are largely unaware of the process, resulting in delays. METHODS: Process mapping, an Ishikawa diagram and a Pareto chart were used to identify barriers, which included timely acquisition of home equipment and medication and poor communication among stakeholders. In May 2020, the Quality Improvement (QI) team embarked on a pilot project to reduce family caregiver anxiety and delays in the ComD process while maintaining a success rate above 90% over a 12-month period. INTERVENTIONS: Three Plan-Do-Study-Act (PDSA) cycles were used to refine a ComD resource package that was developed; this consisted of a checklist, a kit and caregiver resources. This was to support nurses, doctors and families during this difficult and emotional transition. Items in the ComD resource package were revised iteratively based on user feedback, with further data collected to measure its usefulness. RESULTS: The 12-month ComD success rate over 3 PDSA cycles were 88.9%, 94.2% and 96.7%, respectively, after each cycle. There was a consistent reduction in the level of family anxiety before and after caregiver training and resources. Reasons for failed ComD included acute clinical deterioration or delays in obtaining home oxygen support. CONCLUSION: The ComD resource package allowed collaborative work across different disciplines, strengthening the safety and utility of ComD and allowing patients to die in their place of choice. These are ubiquitous across settings; this QI problem is thus relevant beyond our local institution.

Development and psychometric evaluation of a questionnaire for the assessment of depression in primary care: a cross-sectional study.

OBJECTIVES: To develop a new questionnaire for the diagnostic assessment of depression adapted to the primary care setting by combining psychiatric criteria and heuristics of general practitioners (GPs). Psychometric evaluation of the new questionnaire and first validity evidence. DESIGN: The questionnaire was developed using cognitive interviews with think-aloud technique. Factorial validity was then examined in a cross-sectional study. SETTING: Primary care. Five general practices in Bavaria, Germany. PARTICIPANTS: 15 GPs, 4 psychiatrists/psychotherapists and 13 patients participated in cognitive expert interviews. A primary care sample of N=277 consecutive patients participated in the cross-sectional study. METHODS: After consultation with experts and literature research, the questionnaire contained a self-rating part for patients and an external part for GPs. Items were then iteratively optimised using cognitive interviews. Factorial validity was examined. To estimate internal consistency, Cronbach's α was calculated. Validity was assessed by correlating the new questionnaire and the Patient Health Questionnaire-9 (PHQ-9). RESULTS: The preliminary version of the two-part 'Questionnaire for the assessment of DEpression SYmptoms in Primary Care' (DESY-PC) comprised 52 items for patients (DESY-PAT-1: questions about patient's environment; DESY-PAT-2: questions about depression-specific symptoms) and 21 items for GPs (DESY-GP). The analysis of the DESY-PAT-1 revealed a one-factor solution ('environmental factors') with Cronbach's α of 0.55. The items of the DESY-PAT-2 were assigned to three factors, 'depressive cognitions', 'suicidality' and 'symptoms of fatigue', with Cronbach's α of 0.86, 0.79 and 0.85, respectively. Factorial analysis revealed two factors for the DESY-GP: 'depression symptoms' and 'medical history/external factors'. Cronbach's α was 0.90 and 0.59, respectively. After factorial analysis, the DESY-PAT was reduced to 28 items, and the DESY-GP was reduced to 15 items. Correlations of the DESY-PC with the PHQ-9 were high and significant, indicating convergent validity. CONCLUSIONS: The new questionnaire represents an innovative extension of depression questionnaires and could be particularly suitable for general practices.

Exploring subjective quality-of-life indicators in long-term care facilities: a mixed-methods research protocol.

INTRODUCTION: Improving quality of life has become a priority in the long-term care (LTC) sector internationally. With development and implementation guidance, standardised quality-of-life monitoring tools based on valid, self-report surveys could be used more effectively to benefit LTC residents, families and organisations. This research will explore the potential for subjective quality-of-life indicators in the interRAI Self-Reported Quality of Life Survey for Long-Term Care Facilities (QoL-LTCF). METHODS AND ANALYSIS: Guided by the Medical Research Council Framework, this research will entail a (1) modified Delphi study, (2) feasibility study and (3) realist synthesis. In study 1, we will evaluate the importance of statements and scales in the QoL-LTCF by administering Delphi surveys and focus groups to purposively recruited resident and family advisors, researchers, and LTC clinicians, staff, and leadership from international quality improvement organisations. In study 2, we will critically examine the feasibility and implications of risk-adjusting subjective quality-of-life indicators. Specifically, we will collect expert stakeholder perspectives with interviews and apply a risk-adjustment methodology to QoL-LTCF data. In study 3, we will iteratively review and synthesise literature, and consult with expert stakeholders to explore the implementation of quality-of-life indicators. ETHICS AND DISSEMINATION: This study has received approval through a University of Waterloo Research Ethics Board and the Social and Societal Ethics Committee of KU Leuven. We will disseminate our findings in conferences, journal article publications and presentations for a variety of stakeholders.

[Informing the clinical reasoning of advanced practice students with nursing theories]. / Éclairer le raisonnement clinique des étudiants en pratique avancée par les théories infirmières.

This article examines the integration of a Clinical Nurse Reasoning (CNR) model into advanced nursing practice training to develop the clinical reasoning skills of advanced practice nurses. The article explores the contribution of Callista Roy's conceptual model of adaptation and presents a global analysis of a complex care situation that justifies the introduction of an CNR model paired with nursing knowledge to ensure comprehensive, quality nursing care.

[The story of a joint project to develop professional skills]. / L'histoire d'une coconstruction au service du développement des compétences professionnelles.

In the paramedical training establishments and institutes of Northern Gironde, all stakeholders are mobilizing to enhance the attractiveness of healthcare professions. The human resources department and the general coordination of care activities are implementing a proactive social and managerial policy in connection with training institutes that are working to attract learners to a peri-urban and rural area. Like an invitation to live an epic, a commitment to share an adventure with passion, that of discovering the caring professions.

[Pan American Crohn's and Colitis Organization (PANCCO) and the Interamerican Society of Endoscopy (SIED) consensus on endoscopy in inflammatory bowel disease]. / Consenso de endoscopia en enfermedad inflamatoria intestinal de la Organización Panamericana de Crohn y Colitis (PANCCO) y la Sociedad Interamericana de endoscopia (SIED).

INTRODUCTION: Endoscopy plays a fundamental role in inflammatory bowel disease (IBD), and becomes essential in diagnosis, treatment monitoring, and detection and management of complications. MATERIALS AND METHODS: The Pan American Crohn's and Colitis Organization (PANCCO) and the Inter-American Society of Endoscopy (SIED) appointed 22 Latin American experts in IBD to develop a consensus study using the modified Delphi method, based on the best available evidence. A working group of 22 members from 9 countries identified 15 topics and formulated 98 statements, who participated in 2 rounds of voting. It was defined as agreement of ≥80% of experts for each statement. RESULTS: After the voting of all the statements, 8 statements were obtained that did not reach 80% consensus among the participants, so the questions were reconsidered in the Coordinating Committee of the consensus with the participation of the expert reviewers of these questions and 7 final statements were voted again by all the experts in a second round and 1 was eliminated with consensus. After two rounds of voting, the experts reached consensus with literature review with the best available evidence, the most important issues were developed with scientific evidence supporting each of the statements around the topic of endoscopy in IBD. CONCLUSIONS: Consensus statements were developed and based on the best available evidence about endoscopy in inflammatory bowel disease.

Leveraging AI and Machine Learning in Six-Sigma Documentation for Pharmaceutical Quality Assurance.

The pharmaceutical industry must maintain stringent quality assurance standards to ensure product safety and regulatory compliance. A key component of the well-known Six Sigma methodology for process improvement and quality control is precise and comprehensive documentation. However, there are a number of significant issues with traditional documentation procedures, including as slowness, human error, and difficulties with regulatory standards. This review research looks at innovative ways to employ machine learning (ML) and artificial intelligence (AI) to enhance Six Sigma documentation processes in the pharmaceutical sector. AI and ML provide cutting-edge technologies that have the potential to drastically alter documentation processes by automating data entry, collection, and analysis. Natural language processing (NLP) and computer vision technologies have the potential to significantly reduce human error rates and increase the efficacy of documentation processes. By applying machine learning algorithms to support real-time data analysis, predictive analytics, and proactive quality management, pharmaceutical organizations may be able to identify potential quality issues early on and take proactive efforts to address them. Combining AI and ML improves documentation accuracy and reliability while also strengthening compliance with stringent regulatory criteria. The primary barriers and limitations to the current state of Six Sigma documentation in the pharmaceutical industry are identified in this study. It examines the fundamentals of AI and ML with an emphasis on their specific applications in quality assurance and potential benefits for Six Sigma processes. The report includes extensive case studies that highlight notable developments and explain how AI/ML enhanced documentation is used in the real world.

Improved water supply infrastructure to reduce acute diarrhoeal diseases and cholera in Uvira, Democratic Republic of the Congo: Results and lessons learned from a pragmatic trial.

BACKGROUND: Safely managed drinking water is critical to prevent diarrhoeal diseases, including cholera, but evidence on the effectiveness of piped water supply in reducing these diseases in low-income and complex emergency settings remains scarce. METHODS: We conducted a trial of water supply infrastructure improvements in Uvira (DRC). Our primary objective was to estimate the relationship between a composite index of water service quality and the monthly number of suspected cholera cases admitted to treatment facilities and, as a secondary analysis, the number of cases confirmed by rapid diagnostic tests. Other exposures included the quantity of supplied water and service continuity. We used Poisson generalised linear models with generalised estimating equations to estimate incidence rate ratios. FINDINGS: Associations between suspected cholera incidence and water service quality (RR 0·86, 95% CI 0·73-1·01), quantity (RR 0·80, 95% CI 0·62-1·02) and continuity (RR 0·81, 95% CI 0·77-0·86) were estimated. The magnitudes of the associations were similar between confirmed cholera incidence and water service quality (RR 0·84, 95% CI 0·73-0·97), quantity (RR 0·76, 95% CI 0·61-0·94) and continuity (RR 0·75, 95% CI 0·69-0·81). These results suggest that an additional 5 L/user/day or 1.2 hour per day of water production could reduce confirmed cholera by 24% (95% CI 6-39%) and 25% (95% CI 19-31%), respectively. INTERPRETATION: Ensuring a sufficient and continuous piped water supply may substantially reduce the burden of endemic cholera and diarrhoeal diseases but evaluating this rigorously is challenging. Pragmatic strategies are needed for public health research on complex interventions in protracted emergency settings. TRIAL REGISTRATION: The trial is registered in ClinicalTrials.gov ID NCT02928341. https://classic.clinicaltrials.gov/ct2/show/NCT02928341.

Benchmarking mobile applications for the health of people with Diabetes Mellitus.

OBJECTIVE: to map the content and features of mobile applications on the management of Diabetes Mellitus and their usability on the main operating systems. METHOD: benchmarking research. The mapping of apps, content, and resources on the Play Store and App Store platforms was based on an adaptation of the Joanna Briggs Institute's scoping review framework. For the usability analysis, the apps were tested for two weeks and the System Usability Scale instrument was used, with scores between 50-67 points being considered borderline, between 68-84, products with acceptable usability and above 85, excellent user acceptance and, for the analysis, descriptive statistics. RESULTS: the most prevalent contents were capillary blood glucose management, diet, oral drug therapy, and insulin therapy. As for resources, diaries and graphs were the most common. With regard to usability, two apps were considered to have excellent usability; 34, products with acceptable usability; 29, the resource may have some flaws but still has acceptable usability standards and 6, with flaws and no usability conditions. CONCLUSION: the content and resources of mobile applications address the fundamental points for managing Diabetes Mellitus with user-friendly resources, with usability acceptable to users and have the potential to assist in the management of Diabetes Mellitus in patients' daily lives.

Reuse of N95/PFF2 masks in clinical practice: morphological and structural analysis.

OBJECTIVE: to analyze the integrity of N95/PFF2 masks in relation to fiber morphology, porosity, cracks and micro holes, as well as identify visible damage to their structure and components, after seven- and fifteen-day reuse protocols. METHOD: cross-sectional study. Structural and morphological characteristics of a new N95/PFF2 mask were analyzed in comparison with N95/PFF2 masks (n=10) used in seven- and fifteen-day protocols, through visual inspection and scanning electron microscopy. RESULTS: upon visual inspection, following the seven-day protocol, 40% and 60% of the N95/PFF2 masks showed, respectively, personal identification marks and external and internal dirt. Additionally, 20% exhibited loosening and/or tearing of the straps, while 100% showed some type of damage to the nose clips. In the fifteen-day protocol, all N95/PFF2 masks had dirt, loose straps and damaged nose clips, and 80% had folds. Electronic microscopy revealed an increase in pores and loosening in the weaves from seven days onwards, extending up to fifteen days, with the presence of micro holes and residues. CONCLUSION: the reuse of N95/PFF2 masks affects their structural and morphological integrity. It is crucial to carry out tests to measure the impact of this practice on the safety of health professionals.

Assessing GPT-4's Performance in Delivering Medical Advice: Comparative Analysis With Human Experts.

Background: Accurate medical advice is paramount in ensuring optimal patient care, and misinformation can lead to misguided decisions with potentially detrimental health outcomes. The emergence of large language models (LLMs) such as OpenAI's GPT-4 has spurred interest in their potential health care applications, particularly in automated medical consultation. Yet, rigorous investigations comparing their performance to human experts remain sparse. Objective: This study aims to compare the medical accuracy of GPT-4 with human experts in providing medical advice using real-world user-generated queries, with a specific focus on cardiology. It also sought to analyze the performance of GPT-4 and human experts in specific question categories, including drug or medication information and preliminary diagnoses. Methods: We collected 251 pairs of cardiology-specific questions from general users and answers from human experts via an internet portal. GPT-4 was tasked with generating responses to the same questions. Three independent cardiologists (SL, JHK, and JJC) evaluated the answers provided by both human experts and GPT-4. Using a computer interface, each evaluator compared the pairs and determined which answer was superior, and they quantitatively measured the clarity and complexity of the questions as well as the accuracy and appropriateness of the responses, applying a 3-tiered grading scale (low, medium, and high). Furthermore, a linguistic analysis was conducted to compare the length and vocabulary diversity of the responses using word count and type-token ratio. Results: GPT-4 and human experts displayed comparable efficacy in medical accuracy ("GPT-4 is better" at 132/251, 52.6% vs "Human expert is better" at 119/251, 47.4%). In accuracy level categorization, humans had more high-accuracy responses than GPT-4 (50/237, 21.1% vs 30/238, 12.6%) but also a greater proportion of low-accuracy responses (11/237, 4.6% vs 1/238, 0.4%; P=.001). GPT-4 responses were generally longer and used a less diverse vocabulary than those of human experts, potentially enhancing their comprehensibility for general users (sentence count: mean 10.9, SD 4.2 vs mean 5.9, SD 3.7; P<.001; type-token ratio: mean 0.69, SD 0.07 vs mean 0.79, SD 0.09; P<.001). Nevertheless, human experts outperformed GPT-4 in specific question categories, notably those related to drug or medication information and preliminary diagnoses. These findings highlight the limitations of GPT-4 in providing advice based on clinical experience. Conclusions: GPT-4 has shown promising potential in automated medical consultation, with comparable medical accuracy to human experts. However, challenges remain particularly in the realm of nuanced clinical judgment. Future improvements in LLMs may require the integration of specific clinical reasoning pathways and regulatory oversight for safe use. Further research is needed to understand the full potential of LLMs across various medical specialties and conditions.

Surgeon Skill and Perioperative Outcomes in Robot-Assisted Partial Nephrectomy.

Importance: Technical skill in complex surgical procedures may affect clinical outcomes, and there is growing interest in understanding the clinical implications of surgeon proficiency levels. Objectives: To determine whether surgeon scores representing technical skills of robot-assisted kidney surgery are associated with patient outcomes. Design, Setting, and Participants: This quality improvement study included 10 urological surgeons participating in a surgical collaborative in Michigan from July 2021 to September 2022. Each surgeon submitted up to 7 videos of themselves performing robot-assisted partial nephrectomy. Videos were segmented into 6 key steps, yielding 127 video clips for analysis. Each video clip was deidentified and distributed to at least 3 of the 24 blinded peer surgeons from the collaborative who also perform robot-assisted partial nephrectomy. Reviewers rated technical skill and provided written feedback. Statistical analysis was performed from May 2023 to January 2024. Main Outcomes and Measures: Reviewers scored each video clip using a validated instrument to assess technical skill for partial nephrectomy on a scale of 1 to 5 (higher scores indicating greater skill). For all submitting surgeons, outcomes from a clinical registry were assessed for length of stay (LOS) greater than 3 days, estimated blood loss (EBL) greater than 500 mL, warm ischemia time (WIT) greater than 30 minutes, positive surgical margin (PSM), 30-day emergency department (ED) visits, and 30-day readmission. Results: Among the 27 unique surgeons who participated in this study as reviewers and/or individuals performing the procedures, 3 (11%) were female, and the median age was 47 (IQR, 39-52) years. Risk-adjusted outcomes were associated with scores representing surgeon skills. The overall performance score ranged from 3.5 to 4.7 points with a mean (SD) of 4.1 (0.4) points. Greater skill was correlated with significantly lower rates of LOS greater than 3 days (-6.8% [95% CI, -8.3% to -5.2%]), EBL greater than 500 mL (-2.6% [95% CI, -3.0% to -2.1%]), PSM (-8.2% [95% CI, -9.2% to -7.2%]), ED visits (-3.9% [95% CI, -5.0% to -2.8%]), and readmissions (-5.7% [95% CI, -6.9% to -4.6%]) (P < .001 for all). Higher overall score was also associated with higher partial nephrectomy volume (ß coefficient, 11.4 [95% CI, 10.0-12.7]; P < .001). Conclusions and Relevance: In this quality improvement study on video-based evaluation of robot-assisted partial nephrectomy, higher technical skill was associated with lower rates of adverse clinical outcomes. These findings suggest that video-based evaluation plays a role in assessing surgical skill and can be used in quality improvement initiatives to improve patient care.