Diagnosis最新文献

Diagnostic errors comprise the leading threat to patient safety in healthcare today. Learning how to extract the lessons from cases where diagnosis succeeds or fails is a promising approach to improve diagnostic safety going forward. We present up-to-date and authoritative guidance on how the existing approaches to conducting root cause analyses (RCA's) can be modified to study cases involving diagnosis. There are several diffierences: In cases involving diagnosis, the investigation should begin immediately after the incident, and clinicians involved in the case should be members of the RCA team. The review must include consideration of how the clinical reasoning process went astray (or succeeded), and use a human-factors perspective to consider the system-related contextual factors in the diagnostic process. We present detailed instructions for conducting RCA's of cases involving diagnosis, with advice on how to identify root causes and contributing factors and select appropriate interventions.

Objectives: Diagnostic excellence underscores the patient-centered diagnosis and patient engagement in the diagnostic process. In contrast to a patient-centered diagnosis, a doctor-centered diagnosis with a lack of patient engagement may inhibit the diagnostic process due to the lack of responsibility, disrupted information, and increased effect of cognitive biases, particularly in a situation where multiple physicians are involved. In this paper, we suggest a promising idea to enhance patient engagement in the diagnostic process by using written information by a patient about their perspective and experience, which can fill the gaps needed for diagnosis that doctors cannot find alone.

Case presentation: A 38-year-old woman developed chest pain, which gradually worsened during the following two years. For two years, she was evaluated in multiple departments; however, no definitive diagnosis was made, and her condition did not improve. During this evaluation, she searched her symptoms and image findings online. She reached a possible diagnosis of 'esophageal achalasia.' Still, she could not tell her concerns to any physicians because she felt that her concerns were not correctly recognized, although she showed her notes that her symptoms were recorded. She finally consulted the department of internal medicine, where her notes and previous test results were thoroughly reviewed. The final diagnosis of esophageal achalasia was confirmed.

Conclusions: Doctors must organize an environment where patients can freely express their thoughts, emotions, and ideas regarding their diagnosis. Cogenerating visit notes using patient input through written communication can be a promising idea to facilitate patient engagement in the diagnostic process.

Objectives: To present and discuss an uncommon clinical presentation of hyperthyroidism in a female patient with Chiari type 1 malformation. We explore how her medical history influenced the diagnostic process and ultimately contributed to the delayed diagnosis.

Case presentation: In this case study, we discuss an unusual presentation of hyperthyroidism in a 35-year-old female with Chiari type 1 malformation. Initially experiencing headaches, tremors, and dizziness, the patient consulted multiple specialists without a clear diagnosis. Later, she developed recurrent vomiting unrelated to food intake, significant weight loss (12 kg), and muscle weakness, leading to her hospitalization. After six months of clinical evaluation with several specialists (neurologists, neurosurgeons, and gastroenterologists), she was, finally, diagnosed with hyperthyroidism by an Internal Medicine physician in another private clinic. Treatment with thiamazole and propranolol led to the improvement of symptoms progressively. This case emphasizes the vital role of clinical reasoning, crucial problem-solving, and decision-making processes while addressing cognitive biases in medical specialization. Besides, it highlights the need for internist evaluation in outpatient care to ensure comprehensive assessment and prompt specialist referrals if needed.

Conclusions: This case accentuates the importance of internist evaluation for comprehensive care and timely specialist referrals. Recognizing unusual presentations, like thyrotoxic vomiting, and addressing cognitive biases, such as confirmation and anchor biases, are crucial for accurate and prompt diagnosis. This approach enhances diagnostic accuracy, minimizing unnecessary tests and costs, and alleviates patient suffering.

Introduction: Neurotrauma is the leading cause of death in individuals <45 years old. Many of the published articles on UCHL1 and GFAP lack rigorous methods and reporting.

Content: Due to the high heterogeneity between studies, we evaluated blood GFAP and UCHL1 levels in the same subjects. We determined the biomarker congruence among areas under the ROC curves (AUCs), sensitivities, specificities, and laboratory values in ng/L to avoid spurious results. The definitive meta-analysis included 1,880 subjects in eight studies. The items with the highest risk of bias were as follows: cut-off not prespecified and case-control design not avoided. The AUC of GFAP was greater than the AUC of UCHL1, with a lower prediction interval (PI) limit of 50.1 % for GFAP and 37.3 % for UCHL1, and a significantly greater percentage of GFAP Sp. The PI of laboratory results for GFAP and UCHL1 were 0.517-7,518 ng/L (diseased), 1.2-255 ng/L (nondiseased), and 3-4,180 vs. 3.2-1,297 ng/L, respectively.

Summary: Only the GFAP positive cut-off (255 ng/L) appears to be reliable. The negative COs appear unreliable.

Outlook: GFAP needs better standardization. However, the AUCs of the phospho-Tau and phospho-Tau/Tau proteins resulted not significantly lower than AUC of GFAP, but this result needs further verifications.

Objectives: This paper aims to identify and address gaps in cancer treatment and diagnosis within European health services, focusing specifically on discrepancies between clinical guidelines and policy guidelines. It seeks to highlight how the underutilization of advanced diagnostic techniques recommended by medical societies contributes to missed opportunities for improving patient outcomes.

Methods: A comprehensive analysis was conducted across multiple European countries to assess the compliance and integration of clinical guidelines with the availability of advanced diagnostic technologies. Secondary data related to clinical and policy guidelines in cancer care were collected and analyzed. Key indicators of adoption and utilization of next-generation sequencing and liquid biopsy were examined to evaluate their impact on health service efficiency and patient care.

Results: The analysis revealed significant discrepancies between the recommendations of medical societies regarding advanced diagnostic techniques and their adoption in health policy decisions across Europe. Country-specific assessments indicated varying levels of alignment between clinical guidelines and the availability of advanced diagnostics. These findings underscored missed opportunities for optimizing patient care and health service efficiency through better alignment and integration of clinical guidelines with policy decisions.

Conclusions: This study concludes that there is a critical need for health policy decision-makers to prioritize the adoption of clinical guidelines in resource allocation and health service organization. Greater attention to the recommendations of medical societies regarding advanced diagnostic techniques could significantly enhance diagnostic accuracy, treatment efficacy, and overall patient outcomes in cancer care. The paper advocates for policy reforms that acknowledge and leverage the potential benefits of advanced diagnostics in improving health service performance and patient-centered care across Europe.

Objectives: This short communication explores the potential, limitations, and future directions of generative artificial intelligence (GAI) in enhancing diagnostics.

Methods: This commentary reviews current applications and advancements in GAI, particularly focusing on its integration into medical diagnostics. It examines the role of GAI in supporting medical interviews, assisting in differential diagnosis, and aiding clinical reasoning through the lens of dual-process theory. The discussion is supported by recent examples and theoretical frameworks to illustrate the practical and potential uses of GAI in medicine.

Results: GAI shows significant promise in enhancing diagnostic processes by supporting the translation of patient descriptions into visual formats, providing differential diagnoses, and facilitating complex clinical reasoning. However, limitations such as the potential for generating medical misinformation, known as hallucinations, exist. Furthermore, the commentary highlights the integration of GAI with both intuitive and analytical decision-making processes in clinical diagnostics, demonstrating potential improvements in both the speed and accuracy of diagnoses.

Conclusions: While GAI presents transformative potential for medical diagnostics, it also introduces risks that must be carefully managed. Future advancements should focus on refining GAI technologies to better align with human diagnostic reasoning, ensuring GAI enhances rather than replaces the medical professionals' expertise.

Objectives: Patients referred to general internal medicine (GIM) outpatient clinics may face a higher risk of diagnostic errors than non-referred patients. This difference in risk is assumed to be due to the differences in diseases and clinical presentations between referred and non-referred patients; however, clinical data regarding this issue are scarce. This study aimed to determine the frequency of diagnostic errors and compare the characteristics of referred and non-referred patients visit GIM outpatient clinics.

Methods: This study included consecutive outpatients who visited the GIM outpatient clinic at a university hospital, with or without referral. Data on age, sex, chief complaints, referral origin, and final diagnosis were collected from medical records. The Revised Safer Dx Instrument was used to detect diagnostic errors.

Results: Data from 534 referred and 599 non-referred patients were analyzed. The diagnostic error rate was higher in the referral group than that in the non-referral group (2.2 % vs. 0.5 %, p=0.01). The prevalence of abnormal test results and sensory disturbances was higher in the chief complaints, and the prevalence of musculoskeletal system disorders, connective tissue diseases, and neoplasms was higher in the final diagnoses of referred patients compared with non-referred patients. Among referred patients with diagnostic errors, abnormal test results and sensory disturbances were the two most common chief complaints, whereas neoplasia was the most common final diagnosis. Problems with data integration and interpretation were found to be the most common factors contributing to diagnostic errors.

Conclusions: Paying more attention to patients with abnormal test results and sensory disturbances and considering a higher pre-test probability for neoplasms may prevent diagnostic errors in patients referred to GIM outpatient clinics.

Clinical reasoning is considered one of the most important competencies but is not included in most healthcare curricula. The number and diversity of patient encounters are the decisive factors in the development of clinical reasoning competence. Physical real patient encounters are considered optimal, but virtual patient cases also promote clinical reasoning. A high-volume, low-fidelity virtual patient library thus can support clinical reasoning training in a safe environment and can be tailored to the needs of learners from different health care professions. It may also stimulate interprofessional understanding and team shared decisions. Implementation will be challenged by tradition, the lack of educator competence and prior experience as well as the high-density curricula at medical and veterinary schools and will need explicit address from curriculum managers and education leads.

Objectives: Diagnostic disparities are preventable differences in diagnostic errors or opportunities to achieve diagnostic excellence. There is a need to summarize solutions with explicit considerations for addressing diagnostic disparities. We aimed to describe potential solutions to diagnostic disparities, organize them into an action-oriented typology with illustrative examples, and characterize these solutions to identify gaps for their further development.

Methods: During four human-centered design workshops composed of diverse expertise, participants ideated and clarified potential solutions to diagnostic disparities and were supported by environmental literature scan inputs. Nineteen individual semi-structured interviews with workshop participants validated identified solution examples and solution type characterizations, refining the typology.

Results: Our typology organizes 21 various types of potential diagnostic disparities solutions into four primary expertise categories needed for implementation: healthcare systems' internal expertise, educator-, multidisciplinary patient safety researcher-, and health IT-expertise. We provide descriptions of potential solution types ideated as focused on disparities and compare those to existing examples. Six types were characterized as having diagnostic-disparity-focused examples, five as having diagnostic-focused examples, and 10 as only having general healthcare examples. Only three solution types had widespread implementation. Twelve had implementation on limited scope, and six were mostly hypothetical. We describe gaps that inform the progress needed for each of the suggested solution types to specifically address diagnostic disparities and be suitable for the implementation in routine practice.

Conclusions: Numerous opportunities exist to tailor existing solutions and promote their implementation. Likely enablers include new perspectives, more evidence, multidisciplinary collaborations, system redesign, meaningful patient engagement, and action-oriented coalitions.