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1.
Interv Cardiol Clin ; 13(2): 191-205, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38432762

RESUMO

Mitral regurgitation complicated by cardiogenic shock creates a unique and devastating risk profile for patients and poses significant difficulties for physicians who lack a comprehensive range of effective management strategies. Supportive measures such as intravenous vasodilators, intra-aortic balloon pumps, and percutaneous ventricular assist devices are often necessary to stabilize patients prior to definitive treatment with surgical mitral valve replacement or trans-catheter edge-to-edge repair. This review evaluates the evidence for the available supportive and definitive management strategies in patients with mitral regurgitation complicated by cardiogenic shock and presents a framework to aid clinicians in navigating the complex clinical decision-making process. Additionally, the authors review emerging transcatheter mitral valve replacement technologies that hold promise for expanding the therapeutic armamentarium and improving patient outcomes.


Assuntos
Coração Auxiliar , Insuficiência da Valva Mitral , Humanos , Insuficiência da Valva Mitral/complicações , Insuficiência da Valva Mitral/cirurgia , Choque Cardiogênico/etiologia , Choque Cardiogênico/terapia , Tomada de Decisão Clínica , Medição de Risco
2.
J Cancer Res Clin Oncol ; 150(3): 119, 2024 Mar 11.
Artigo em Inglês | MEDLINE | ID: mdl-38466449

RESUMO

PURPOSE: Gene mutations drive tumor immune microenvironment (TIME) heterogeneity, in turn affecting prognosis and immunotherapy efficacy. PIK3CA is the most frequently mutated gene in breast cancer (BC), yet its relevance to BC prognosis remains controversial. Herein, we sought to determine the impact of PIK3CA mutation-driven immune genes (PDIGs) on BC prognosis in relation to TIME heterogeneity. METHODS: PIK3CA mutation characteristics were compared and verified between the TCGA-BRCA dataset and a patient cohort from our hospital. PIK3CA mutation-driven differentially expressed genes were identified for consensus clustering and weighted gene co-expression network analysis to select the modules most relevant to the immune subtype. Thereafter, the two were intersected to obtain PDIGs. Univariate Cox, LASSO, and multivariate Cox regression analyses were sequentially performed on PDIGs to obtain a PIK3CA mutation-driven immune signature (PDIS), which was then validated using the Gene Expression Omnibus (GEO) database. Differences in functional enrichment, mutation landscape, immune infiltration, checkpoint gene expression, and drug response were compared between different risk groups. RESULTS: PIK3CA mutation frequencies in the TCGA and validation cohorts were 34.49% and 40.83%, respectively. PIK3CA mutants were significantly associated with ER, PR, and molecular BC subtypes in our hospital cohort. The PDIS allowed for effective risk stratification and exhibited prognostic power in TCGA and GEO sets. The low-risk patients exhibited greater immune infiltration, higher expression of common immune checkpoint factors, and lower scores for tumor immune dysfunction and exclusion. CONCLUSION: The PDIS can be used as an effective prognostic model for predicting immunotherapy response to guide clinical decision-making.


Assuntos
Neoplasias da Mama , Humanos , Feminino , Neoplasias da Mama/genética , Neoplasias da Mama/terapia , Prognóstico , Classe I de Fosfatidilinositol 3-Quinases/genética , Tomada de Decisão Clínica , Análise por Conglomerados , Microambiente Tumoral/genética
3.
Health Expect ; 27(2): e14001, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38433012

RESUMO

BACKGROUND: There is a growing momentum around the world to foster greater opportunities for the involvement of mental health service users in their care and treatment planning. In-principle support for this aim is widespread across mental healthcare professionals. Yet, progress in mental health services towards this objective has lagged in practice. OBJECTIVES: We conducted a systematic review of quantitative, qualitative and mixed-method research on interventions to improve opportunities for the involvement of mental healthcare service users in treatment planning, to understand the current research evidence and the barriers to implementation. METHODS: Seven databases were searched and 5137 articles were screened. Articles were included if they reported on an intervention for adult service users, were published between 2008 and October 2023 and were in English. Evidence in the 140 included articles was synthesised according to the JBI guidance on Mixed Methods Systematic Reviews. RESULTS: Research in this field remains exploratory in nature, with a wide range of interventions investigated to date but little experimental replication. Overarching barriers to shared and supported decision-making in mental health treatment planning were (1) Organisational (resource limitations, culture barriers, risk management priorities and structure); (2) Process (lack of knowledge, time constraints, health-related concerns, problems completing and using plans); and (3) Relationship barriers (fear and distrust for both service users and clinicians). CONCLUSIONS: On the basis of the barriers identified, recommendations are made to enable the implementation of new policies and programs, the designing of new tools and for clinicians seeking to practice shared and supported decision-making in the healthcare they offer. PATIENT OR PUBLIC CONTRIBUTION: This systematic review has been guided at all stages by a researcher with experience of mental health service use, who does not wish to be identified at this point in time. The findings may inform organisations, researchers and practitioners on implementing supported decision-making, for the greater involvement of people with mental ill health in their healthcare.


Assuntos
Tomada de Decisão Clínica , Serviços de Saúde Mental , Humanos , Atenção à Saúde , Instalações de Saúde , Pessoal de Saúde , Saúde Mental
4.
J Cancer Res Clin Oncol ; 150(3): 112, 2024 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-38436779

RESUMO

PURPOSE: CIC-rearranged sarcomas represent a type of undifferentiated small round cell sarcoma (USRCS) characterized by poor survival, rapid development of chemotherapy resistance, and high rates of metastasis. We aim to contribute to the growing body of knowledge regarding diagnosis, treatment, clinical course, and outcomes for these patients. METHODS: This case series investigates the clinical courses of ten patients with CIC-rearranged sarcoma treated at the Johns Hopkins Hospital from July 2014 through January 2024. Clinical data were retrospectively extracted from electronic medical records. RESULTS: Patients ranged from 10 to 67 years of age at diagnosis, with seven patients presenting with localized disease and three with metastatic disease. Tumors originated from soft tissues of various anatomic locations. Mean overall survival (OS) was 22.1 months (10.6-52.2), and mean progression-free survival (PFS) was 16.7 months (5.3-52.2). Seven patients received intensive systemic therapy with an Ewing sarcoma-directed regimen or a soft tissue sarcoma-directed regimen. Three patients experienced prolonged disease-free survival without systemic treatment. CONCLUSION: Most patients in this case series demonstrated aggressive clinical courses consistent with those previously described in the literature, although we note a spectrum of clinical outcomes not previously reported. The diversity of clinical courses underscores the need for an improved understanding of individual tumor biology to enhance clinical decision-making and patient prognosis. Despite its limitations, this article broadens the spectrum of reported clinical outcomes, providing a valuable addition to the published literature on this rare cancer.


Assuntos
Sarcoma de Ewing , Sarcoma , Humanos , Estudos Retrospectivos , Sarcoma/genética , Sarcoma/terapia , Hospitais , Sarcoma de Ewing/genética , Sarcoma de Ewing/terapia , Tomada de Decisão Clínica
5.
J Nurs Educ ; 63(3): 182-185, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38442403

RESUMO

BACKGROUND: The complexity of health care requires entry-level nurses to have competent clinical judgment skills. In response, a nursing program created Reflective Clinical Judgment Questions (RCJQ) to guide students in the development of clinical judgment. METHOD: The RCJQ incorporates the Clinical Judgment Measurement Model, the National Council of State Boards of Nursing's action questions, and the American Association of Colleges of Nursing's core competencies for professional nursing education. The RCJQ includes cognitive process questions and self-reflection questions aligned to the prelicensure subcompetencies to direct student thinking and build a routine for clinical decision making. RESULTS: The RCJQ provides faculty with a framework to teach clinical judgment and incorporates self-reflective questions to guide decision making for safe and effective client care. CONCLUSION: The RCJQ streamlines the clinical judgment process and guides students to achieve essential outcomes in classroom, clinical, and simulation settings to prepare for clinical practice. [J Nurs Educ. 2024;63(3):182-185.].


Assuntos
Julgamento , Estudantes , Humanos , Raciocínio Clínico , Tomada de Decisão Clínica , Competência Clínica
6.
J Med Internet Res ; 26: e50369, 2024 Mar 18.
Artigo em Inglês | MEDLINE | ID: mdl-38498038

RESUMO

BACKGROUND: Early and reliable identification of patients with sepsis who are at high risk of mortality is important to improve clinical outcomes. However, 3 major barriers to artificial intelligence (AI) models, including the lack of interpretability, the difficulty in generalizability, and the risk of automation bias, hinder the widespread adoption of AI models for use in clinical practice. OBJECTIVE: This study aimed to develop and validate (internally and externally) a conformal predictor of sepsis mortality risk in patients who are critically ill, leveraging AI-assisted prediction modeling. The proposed approach enables explaining the model output and assessing its confidence level. METHODS: We retrospectively extracted data on adult patients with sepsis from a database collected in a teaching hospital at Beth Israel Deaconess Medical Center for model training and internal validation. A large multicenter critical care database from the Philips eICU Research Institute was used for external validation. A total of 103 clinical features were extracted from the first day after admission. We developed an AI model using gradient-boosting machines to predict the mortality risk of sepsis and used Mondrian conformal prediction to estimate the prediction uncertainty. The Shapley additive explanation method was used to explain the model. RESULTS: A total of 16,746 (80%) patients from Beth Israel Deaconess Medical Center were used to train the model. When tested on the internal validation population of 4187 (20%) patients, the model achieved an area under the receiver operating characteristic curve of 0.858 (95% CI 0.845-0.871), which was reduced to 0.800 (95% CI 0.789-0.811) when externally validated on 10,362 patients from the Philips eICU database. At a specified confidence level of 90% for the internal validation cohort the percentage of error predictions (n=438) out of all predictions (n=4187) was 10.5%, with 1229 (29.4%) predictions requiring clinician review. In contrast, the AI model without conformal prediction made 1449 (34.6%) errors. When externally validated, more predictions (n=4004, 38.6%) were flagged for clinician review due to interdatabase heterogeneity. Nevertheless, the model still produced significantly lower error rates compared to the point predictions by AI (n=1221, 11.8% vs n=4540, 43.8%). The most important predictors identified in this predictive model were Acute Physiology Score III, age, urine output, vasopressors, and pulmonary infection. Clinically relevant risk factors contributing to a single patient were also examined to show how the risk arose. CONCLUSIONS: By combining model explanation and conformal prediction, AI-based systems can be better translated into medical practice for clinical decision-making.


Assuntos
Inteligência Artificial , Sepse , Adulto , Humanos , Estudos Retrospectivos , Sepse/diagnóstico , Tomada de Decisão Clínica , Hospitais de Ensino
7.
Clin Transplant ; 38(3): e15281, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38504577

RESUMO

BACKGROUND: We aimed to assess outcomes in patients with and without donor specific antibodies (DSA) and to evaluate the relationship between DSA presence and graft function, cardiac allograft vasculopathy (CAV), and mortality. METHODS: The study population comprises 193 consecutive long-term heart transplanted (HTx) patients who underwent DSA surveillance between 2016 and 2022. The patients were prospectively screened for CAV through serial coronary angiograms, graft function impairment through serial echocardiograms, and cardiac biomarkers. The patients were followed from the first DSA measurement until death, 5 years follow-up or right censuring on the 30th of June 2023. RESULTS: DSAs were detected in 50 patients using a cut-off at MFI ≥1000 and 45 patients using a cut-off at ≥2000 MFI. The median time since HTx was 9.0 years [3.0-14.4]. DSA positive patients had poorer graft function and higher values of NT-proBNP and troponin T, and more prevalent CAV than DSA negative patients. In total, 25 patients underwent endomyocardial biopsies due to DSA presence while another eight patients underwent endomyocardial biopsies for other reasons. Histological antibody mediated rejection (AMR) signs were seen in three biopsies. During a median follow-up of five years [4.7-5], a total of 41 patients died. Mortality rates did not differ between DSA positive and DSA negative patients (HR 1.2, 95% CI .6-2.4). DSA positive patients were more likely to experience CAV progression than DSA negative patients (HR 2.7, 95% CI 1.5-4.8) CONCLUSIONS: Routine screening reveals DSA in approximately 25% of long-term HTx patients but is rarely related to histopathological AMR signs. DSA presence was associated with poorer graft function and more prevalent and progressive CAV. However, DSA positive patients had similar survival rates to DSA negative patients.


Assuntos
Rejeição de Enxerto , Transplante de Coração , Humanos , Rejeição de Enxerto/diagnóstico , Rejeição de Enxerto/etiologia , Anticorpos , Transplante de Coração/efeitos adversos , Doadores de Tecidos , Tomada de Decisão Clínica , Antígenos HLA , Isoanticorpos , Estudos Retrospectivos
8.
J Med Internet Res ; 26: e53951, 2024 Mar 19.
Artigo em Inglês | MEDLINE | ID: mdl-38502157

RESUMO

BACKGROUND: Spinal disorders are highly prevalent worldwide with high socioeconomic costs. This cost is associated with the demand for treatment and productivity loss, prompting the exploration of technologies to improve patient outcomes. Clinical decision support systems (CDSSs) are computerized systems that are increasingly used to facilitate safe and efficient health care. Their applications range in depth and can be found across health care specialties. OBJECTIVE: This scoping review aims to explore the use of CDSSs in patients with spinal disorders. METHODS: We used the Joanna Briggs Institute methodological guidance for this scoping review and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) statement. Databases, including PubMed, Embase, Cochrane, CINAHL, Web of Science, Scopus, ProQuest, and PsycINFO, were searched from inception until October 11, 2022. The included studies examined the use of digitalized CDSSs in patients with spinal disorders. RESULTS: A total of 4 major CDSS functions were identified from 31 studies: preventing unnecessary imaging (n=8, 26%), aiding diagnosis (n=6, 19%), aiding prognosis (n=11, 35%), and recommending treatment options (n=6, 20%). Most studies used the knowledge-based system. Logistic regression was the most commonly used method, followed by decision tree algorithms. The use of CDSSs to aid in the management of spinal disorders was generally accepted over the threat to physicians' clinical decision-making autonomy. CONCLUSIONS: Although the effectiveness was frequently evaluated by examining the agreement between the decisions made by the CDSSs and the health care providers, comparing the CDSS recommendations with actual clinical outcomes would be preferable. In addition, future studies on CDSS development should focus on system integration, considering end user's needs and preferences, and external validation and impact studies to assess effectiveness and generalizability. TRIAL REGISTRATION: OSF Registries osf.io/dyz3f; https://osf.io/dyz3f.


Assuntos
Sistemas de Apoio a Decisões Clínicas , Eritrodermia Ictiosiforme Congênita , Erros Inatos do Metabolismo Lipídico , Doenças Musculares , Humanos , Tomada de Decisão Clínica , Algoritmos , Bases de Dados Factuais
9.
Implement Sci ; 19(1): 27, 2024 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-38491544

RESUMO

BACKGROUND: Artificial intelligence (AI), particularly generative AI, has emerged as a transformative tool in healthcare, with the potential to revolutionize clinical decision-making and improve health outcomes. Generative AI, capable of generating new data such as text and images, holds promise in enhancing patient care, revolutionizing disease diagnosis and expanding treatment options. However, the utility and impact of generative AI in healthcare remain poorly understood, with concerns around ethical and medico-legal implications, integration into healthcare service delivery and workforce utilisation. Also, there is not a clear pathway to implement and integrate generative AI in healthcare delivery. METHODS: This article aims to provide a comprehensive overview of the use of generative AI in healthcare, focusing on the utility of the technology in healthcare and its translational application highlighting the need for careful planning, execution and management of expectations in adopting generative AI in clinical medicine. Key considerations include factors such as data privacy, security and the irreplaceable role of clinicians' expertise. Frameworks like the technology acceptance model (TAM) and the Non-Adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) model are considered to promote responsible integration. These frameworks allow anticipating and proactively addressing barriers to adoption, facilitating stakeholder participation and responsibly transitioning care systems to harness generative AI's potential. RESULTS: Generative AI has the potential to transform healthcare through automated systems, enhanced clinical decision-making and democratization of expertise with diagnostic support tools providing timely, personalized suggestions. Generative AI applications across billing, diagnosis, treatment and research can also make healthcare delivery more efficient, equitable and effective. However, integration of generative AI necessitates meticulous change management and risk mitigation strategies. Technological capabilities alone cannot shift complex care ecosystems overnight; rather, structured adoption programs grounded in implementation science are imperative. CONCLUSIONS: It is strongly argued in this article that generative AI can usher in tremendous healthcare progress, if introduced responsibly. Strategic adoption based on implementation science, incremental deployment and balanced messaging around opportunities versus limitations helps promote safe, ethical generative AI integration. Extensive real-world piloting and iteration aligned to clinical priorities should drive development. With conscientious governance centred on human wellbeing over technological novelty, generative AI can enhance accessibility, affordability and quality of care. As these models continue advancing rapidly, ongoing reassessment and transparent communication around their strengths and weaknesses remain vital to restoring trust, realizing positive potential and, most importantly, improving patient outcomes.


Assuntos
Inteligência Artificial , Ciência da Implementação , Humanos , Ecossistema , Tomada de Decisão Clínica , Atenção à Saúde
10.
Cancer Med ; 13(5): e6971, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38491804

RESUMO

BACKGROUND: More accurate prediction of distant metastases (DM) in patients with colorectal cancer (CRC) would optimize individualized treatment and follow-up strategies. Multiple prediction models based on machine learning have been developed to assess the likelihood of developing DM. METHODS: Clinicopathological features of patients with CRC were obtained from the National Cancer Center (NCC, China) and the Surveillance, Epidemiology, and End Results (SEER) database. The algorithms used to create the prediction models included random forest (RF), logistic regression, extreme gradient boosting, deep neural networks, and the K-Nearest Neighbor machine. The prediction models' performances were evaluated using receiver operating characteristic (ROC) curves. RESULTS: In total, 200,958 patients, 3241 from NCC and 197,717 CRC from SEER were identified, of whom 21,736 (10.8%) developed DM. The machine-learning-based prediction models for DM were constructed with 12 features remaining after iterative filtering. The RF model performed the best, with areas under the ROC curve of 0.843, 0.793, and 0.806, respectively, on the training, test, and external validation sets. For the risk stratification analysis, the patients were separated into high-, middle-, and low-risk groups according to their risk scores. Patients in the high-risk group had the highest incidence of DM and the worst prognosis. Surgery, chemotherapy, and radiotherapy could significantly improve the prognosis of the high-risk and middle-risk groups, whereas the low-risk group only benefited from surgery and chemotherapy. CONCLUSION: The RF-based model accurately predicted the likelihood of DM and identified patients with CRC in the high-risk group, providing guidance for personalized clinical decision-making.


Assuntos
Tomada de Decisão Clínica , Neoplasias Colorretais , Humanos , Estudos de Coortes , Fatores de Risco , Aprendizado de Máquina , Neoplasias Colorretais/diagnóstico , Neoplasias Colorretais/epidemiologia , Neoplasias Colorretais/terapia
11.
BMJ Open ; 14(3): e080558, 2024 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-38490655

RESUMO

OBJECTIVE: Large language models (LLMs) such as ChatGPT are being developed for use in research, medical education and clinical decision systems. However, as their usage increases, LLMs face ongoing regulatory concerns. This study aims to analyse ChatGPT's performance on a postgraduate examination to identify areas of strength and weakness, which may provide further insight into their role in healthcare. DESIGN: We evaluated the performance of ChatGPT 4 (24 May 2023 version) on official MRCP (Membership of the Royal College of Physicians) parts 1 and 2 written examination practice questions. Statistical analysis was performed using Python. Spearman rank correlation assessed the relationship between the probability of correctly answering a question and two variables: question difficulty and question length. Incorrectly answered questions were analysed further using a clinical reasoning framework to assess the errors made. SETTING: Online using ChatGPT web interface. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome was the score (percentage questions correct) in the MRCP postgraduate written examinations. Secondary outcomes were qualitative categorisation of errors using a clinical decision-making framework. RESULTS: ChatGPT achieved accuracy rates of 86.3% (part 1) and 70.3% (part 2). Weak but significant correlations were found between ChatGPT's accuracy and both just-passing rates in part 2 (r=0.34, p=0.0001) and question length in part 1 (r=-0.19, p=0.008). Eight types of error were identified, with the most frequent being factual errors, context errors and omission errors. CONCLUSION: ChatGPT performance greatly exceeded the passing mark for both exams. Multiple choice examinations provide a benchmark for LLM performance which is comparable to human demonstrations of knowledge, while also highlighting the errors LLMs make. Understanding the reasons behind ChatGPT's errors allows us to develop strategies to prevent them in medical devices that incorporate LLM technology.


Assuntos
Colangiopancreatografia por Ressonância Magnética , Raciocínio Clínico , Humanos , Tomada de Decisão Clínica , Benchmarking , Reino Unido
12.
J Med Case Rep ; 18(1): 118, 2024 Mar 18.
Artigo em Inglês | MEDLINE | ID: mdl-38494473

RESUMO

BACKGROUND: In the current treatment landscape for non-small cell lung cancers, epidermal growth factor receptor-tyrosine kinase inhibitors have emerged as a well-established treatment option for patients with advanced or metastatic disease. This is particularly true for those with commonly occurring epidermal growth factor receptor mutations. However, the therapeutic efficacy of these agents for so-called rare epidermal growth factor receptor mutations, and in particular those characterized by a high degree of complexity, such as double mutations, remains a subject of clinical uncertainty. CASE PRESENTATION: In this context, we present the case of a 64-year-old man of Moroccan descent, a lifelong non-smoker, diagnosed with metastatic non-small cell lung cancer characterized by a complex epidermal growth factor receptor mutation encompassing L858R and S768I. The patient subsequently underwent afatinib-based treatment, showing notable clinical results. These included a remarkable overall survival of 51 months, with a median progression-free survival of more than 39 months. CONCLUSIONS: This case report is a compelling testimony to the evolving therapeutic landscape of non-small cell lung cancers, providing valuable insight into the potential therapeutic efficacy of epidermal growth factor receptor-tyrosine kinase inhibitors in the realm of rare and complex epidermal growth factor receptor mutations.


Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Humanos , Pessoa de Meia-Idade , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/patologia , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Tomada de Decisão Clínica , Inibidores de Proteínas Quinases/uso terapêutico , Receptores ErbB/genética , Receptores ErbB/uso terapêutico , Incerteza , Mutação
13.
Reumatol Clin (Engl Ed) ; 20(3): 147-149, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38431489

RESUMO

OBJECTIVE: The purpose of the present study is to identify the extent to which it affects clinical decisions in a single-centre observational retrospective study. METHOD: The results of 801 requests and 1174 consecutive individual ultrasound examinations performed over 10 months were analysed. RESULTS: The most frequent indication was diagnostic assistance (39%) followed by assessment of inflammatory activity (34%). By topography, the hand was the most frequently studied region (51%), followed by the foot (18.1%). Of all requests, 67% had an impact on decision-making. The impact on clinical decision-making was associated with a shorter waiting time for the evaluation of the results, being the greatest in those ultrasound scans performed on demand on the same day of the request. In 73% of bilateral ultrasound studies, findings in one of the joints exemplified the overall result reported. CONCLUSIONS: Rheumatological musculoskeletal ultrasound has proven to be a useful decision-making technique, the greater the impact of which is seen the shorter the waiting time before it is performed.


Assuntos
Reumatologia , Humanos , Estudos Longitudinais , Estudos Retrospectivos , Tomada de Decisão Clínica , Ultrassonografia
14.
Can J Surg ; 67(2): E118-E127, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38503461

RESUMO

BACKGROUND: The rapid evolution of genetic technologies and utilization of genetic information for clinical decision-making has necessitated increased surgeon participation in genetic counselling, testing, and appropriate referral of patients for genetic services, without formal training in genetics. We performed a scoping review to describe surgeons' knowledge, perceptions, attitudes, and barriers pertaining to genetic literacy in the management of patients who had confirmed cancer or who were potentially genetically at risk. METHODS: We conducted a scoping review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews checklist. We performed a comprehensive literature search, and 2 reviewers independently screened studies for inclusion. These studies included surgeons involved in the care of patients with confirmed gastrointestinal, breast, and endocrine and neuroendocrine cancers, or patients who were potentially genetically at risk for these cancers. RESULTS: We analyzed 17 studies, all of which used survey or interview-based formats. Many surgeons engaged in genetic counselling, testing, and referral, but reported low confidence and comfort in doing so. Knowledge assessments showed lower confidence in identifying genetic inheritance patterns and hereditary cancer syndromes, but awareness was higher among surgeons with greater clinical volume or subspecialty training in oncology. Surgeons felt responsible for facilitating these services and explicitly requested educational support in genetics. Barriers to genetic literacy were identified and catalogued at patient, surgeon, and system levels. CONCLUSION: Surgeons frequently engage in genetics-related tasks despite a lack of formal genetics training, and often report low knowledge, comfort, and confidence in providing such services. We have identified several barriers to genetic literacy that can be used to develop interventions to enhance genetic literacy among surgeons.


Assuntos
Neoplasias , Cirurgiões , Humanos , Alfabetização , Atitude do Pessoal de Saúde , Tomada de Decisão Clínica
15.
Ital J Pediatr ; 50(1): 37, 2024 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-38433210

RESUMO

BACKGROUND: Home phototherapy (HPT) remains a contentious alternative to inpatient phototherapy (IPT) for neonatal hyperbilirubinemia. To guide evidence-based clinical decision-making, we conducted a meta-analysis of randomized clinical trials (RCTs) and cohort studies and assessed the comparative risks and benefits of HPT and IPT. METHODS: PubMed, Embase, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure Database, Wanfang Database, Chinese Science and Technique Journals Database, ClinicalTrials.gov, and International Clinical Trial Registry Platform trial were searched from inception until June 2, 2023. We included RCTs and cohort studies and adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Study quality was assessed with the Cochrane Collaboration Risk of Bias tool and the Newcastle-Ottawa scale. The outcome measures were phototherapy duration, daily bilirubin level reduction, exchange transfusion, hospital readmission, parental stress scale, and complications. We used fixed- or random-effects meta-analysis models, assessed heterogeneity (I2), conducted subgroup analyses, evaluated publication bias, and graded evidence quality. RESULTS: Nine studies (998 patients) were included (four RCTs, five cohort studies). HPT was associated with longer phototherapy duration (SMD = 0.55, 95% CI: 0.06-1.04, P = 0.03). Cohort study subgroup analysis yielded consistent results (SMD = 0.90; 95% CI: 0.69 to 1.11, P < 0.001, I2 = 39%); the RCTs were not significantly different (SMD = -0.04; 95% CI: -0.15 to 0.08, P = 0.54, I2 = 0%). Hospital readmission was higher with HPT (RR = 4.61; 95% CI: 1.43-14.86, P = 0.01). Daily bilirubin reduction (WMD = -0.12, 95% CI: -0.68 to 0.44, P = 0.68) or complications were not significantly different (RR = 2.29; 95% CI: 0.31-16.60, P = 0.41). The evidence quality was very low. HPT was associated with lower parental stress (SMD = -0.44, 95% CI: -0.71 to -0.16, P = 0.002). None of three included studies reported exchange transfusion. CONCLUSIONS: The current evidence does not strongly support HPT efficacy for neonatal hyperbilirubinemia, as high-quality data on long-term outcomes are scarce. Future research should prioritize well-designed, large-scale, high-quality RCTs to comprehensively assess HPT risks and benefits.


Assuntos
Hiperbilirrubinemia Neonatal , Pacientes Internados , Recém-Nascido , Humanos , Hiperbilirrubinemia Neonatal/terapia , Povo Asiático , Bilirrubina , Tomada de Decisão Clínica
16.
BMC Med Inform Decis Mak ; 24(1): 72, 2024 Mar 12.
Artigo em Inglês | MEDLINE | ID: mdl-38475802

RESUMO

IMPORTANCE: Large language models (LLMs) like OpenAI's ChatGPT are powerful generative systems that rapidly synthesize natural language responses. Research on LLMs has revealed their potential and pitfalls, especially in clinical settings. However, the evolving landscape of LLM research in medicine has left several gaps regarding their evaluation, application, and evidence base. OBJECTIVE: This scoping review aims to (1) summarize current research evidence on the accuracy and efficacy of LLMs in medical applications, (2) discuss the ethical, legal, logistical, and socioeconomic implications of LLM use in clinical settings, (3) explore barriers and facilitators to LLM implementation in healthcare, (4) propose a standardized evaluation framework for assessing LLMs' clinical utility, and (5) identify evidence gaps and propose future research directions for LLMs in clinical applications. EVIDENCE REVIEW: We screened 4,036 records from MEDLINE, EMBASE, CINAHL, medRxiv, bioRxiv, and arXiv from January 2023 (inception of the search) to June 26, 2023 for English-language papers and analyzed findings from 55 worldwide studies. Quality of evidence was reported based on the Oxford Centre for Evidence-based Medicine recommendations. FINDINGS: Our results demonstrate that LLMs show promise in compiling patient notes, assisting patients in navigating the healthcare system, and to some extent, supporting clinical decision-making when combined with human oversight. However, their utilization is limited by biases in training data that may harm patients, the generation of inaccurate but convincing information, and ethical, legal, socioeconomic, and privacy concerns. We also identified a lack of standardized methods for evaluating LLMs' effectiveness and feasibility. CONCLUSIONS AND RELEVANCE: This review thus highlights potential future directions and questions to address these limitations and to further explore LLMs' potential in enhancing healthcare delivery.


Assuntos
Tomada de Decisão Clínica , Medicina Baseada em Evidências , Humanos , Instalações de Saúde , Idioma , MEDLINE
17.
Pediatr Surg Int ; 40(1): 77, 2024 Mar 12.
Artigo em Inglês | MEDLINE | ID: mdl-38472473

RESUMO

Accurate measurement of pneumothorax (PTX) size is necessary to guide clinical decision making; however, there is no consensus as to which method should be used in pediatric patients. This systematic review seeks to identify and evaluate the methods used to measure PTX size with CXR in pediatric patients. A systematic review of the literature through 2021 following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was conducted using the following databases: Ovid/MEDLINE, Scopus, Cochrane Database of Controlled Trials, Cochrane Database of Systematic Reviews, and Google Scholar. Original research articles that included pediatric patients (< 18 years old) and outlined the PTX measurement method were included. 45 studies were identified and grouped by method (Kircher and Swartzel, Rhea, Light, Collins, Other) and societal guideline used. The most used method was Collins (n = 16; 35.6%). Only four (8.9%) studies compared validated methods. All found the Collins method to be accurate. Seven (15.6%) studies used a standard classification guideline and 3 (6.7%) compared guidelines and found significant disagreement between them. Pediatric-specific measurement guidelines for PTX are needed to establish consistency and uniformity in both research and clinical practice. Until there is a better method, the Collins method is preferred.


Assuntos
Pneumotórax , Adolescente , Criança , Humanos , Tomada de Decisão Clínica , Pneumotórax/terapia
18.
Front Immunol ; 15: 1282521, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38455037

RESUMO

Background: The routine use of donor-derived cell-free DNA (dd-cfDNA) assays to monitor graft damage in patients after kidney transplantation is being implemented in many transplant centers worldwide. The interpretation of the results can be complicated in the setting of multiple sequential kidney transplantations where accurate donor assignment of the detected dd-cfDNA can be methodologically challenging. Methods: We investigated the ability of a new next-generation sequencing (NGS)-based dd-cfDNA assay to accurately identify the source of the detected dd-cfDNA in artificially generated samples as well as clinical samples from 31 patients who had undergone two sequential kidney transplantations. Results: The assay showed a high accuracy in quantifying and correctly assigning dd-cfDNA in our artificially generated chimeric sample experiments over a clinically meaningful quantitative range. In our clinical samples, we were able to detect dd-cfDNA from the first transplanted (nonfunctioning) graft in 20% of the analyzed patients. The amount of dd-cfDNA detected from the first graft was consistently in the range of 0.1%-0.6% and showed a fluctuation over time in patients where we analyzed sequential samples. Conclusion: This is the first report on the use of a dd-cfDNA assay to detect dd-cfDNA from multiple kidney transplants. Our data show that a clinically relevant fraction of the transplanted patients have detectable dd-cfDNA from the first donor graft and that the amount of detected dd-cfDNA is in a range where it could influence clinical decision-making.


Assuntos
Ácidos Nucleicos Livres , Transplante de Rim , Humanos , Transplante de Rim/efeitos adversos , Doadores de Tecidos , Bioensaio , Ácidos Nucleicos Livres/genética , Tomada de Decisão Clínica
19.
Clin Toxicol (Phila) ; 62(1): 1-9, 2024 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-38421362

RESUMO

INTRODUCTION: The evaluation of acute poisoning is challenging due to varied toxic substances and clinical presentations. The new-Poisoning Mortality Score was recently developed to assess patients with acute poisoning and showed good performance in predicting in-hospital mortality. The objective of this study is to externally validate the performance of the new-Poisoning Mortality Score and to compare it with the Modified Early Warning Score. METHODS: This retrospective analysis used data from the 2019-2020 Injury Surveillance Cohort, established by the Korea Center for Disease Control and Prevention, to perform external validation of the new-Poisoning Mortality Score. The statistical performances of the new-Poisoning Mortality and Modified Early Warning Scores were assessed and compared in terms of discrimination and calibration. Discrimination analysis involved metrics such as sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve. For calibration analysis, the Hosmer-Lemeshow goodness-of-fit test was utilized and calibration curves for each score were generated to elucidate the relationship between observed and predicted mortalities. RESULTS: This study analysed 16,570 patients with acute poisoning. Significant differences were observed between survivors and those who died in-hospital, including age, sex, and vital signs. The new-Poisoning Mortality Score showed better performance over the Modified Early Warning Score in predicting in-hospital mortality, in terms of the area under the receiver operating characteristic curve (0.947 versus 0.800), sensitivity (0.863 versus 0.667), specificity (0.912 versus 0.817), and accuracy (0.911 versus 0.814). When evaluated through calibration curves, the new-Poisoning Mortality Score showed better concordance between predicted and observed mortalities. In subgroup analyses, the score system consistently showed strong performance, excelling particularly in substances with high mortality indices and remaining superior in all substances as a group. CONCLUSIONS: Our study has helped to validate the new-Poisoning Mortality Score as an effective tool for predicting in-hospital mortality in patients with acute poisoning in the emergency department. The score system demonstrated superior performance over the Modified Early Warning Score in various metrics. Our findings suggest that the new-Poisoning Mortality Score can contribute to the enhancement of clinical decision-making and patient management.


Assuntos
Escore de Alerta Precoce , Humanos , Mortalidade Hospitalar , Estudos Retrospectivos , Benchmarking , Tomada de Decisão Clínica
20.
Neurosurg Clin N Am ; 35(2): 235-241, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38423739

RESUMO

There is a significant need for robust and objective outcome assessments in spine surgery. Constant monitoring via smartphones and wearable devices has the potential to fill this role by providing an in-depth picture of human well-being, creating an unprecedented amount of objective data to augment clinical decision-making. The metrics obtained from continuous patient monitoring increase the amount and ecological validity of data relevant to spine surgery. This can provide physicians with patient and disease-specific medical information, facilitating personalized patient care.


Assuntos
Tomada de Decisão Clínica , Dispositivos Eletrônicos Vestíveis , Humanos
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