Importance of Patient History in Artificial Intelligence-Assisted Medical Diagnosis: Comparison Study.

Background: Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first proposed more than 70 years ago. Recently, its role in various fields of medicine has grown remarkably. However, no studies have evaluated the importance of patient history in AI-assisted medical diagnosis. Objective: This study explored the contribution of patient history to AI-assisted medical diagnoses and assessed the accuracy of ChatGPT in reaching a clinical diagnosis based on the medical history provided. Methods: Using clinical vignettes of 30 cases identified in The BMJ, we evaluated the accuracy of diagnoses generated by ChatGPT. We compared the diagnoses made by ChatGPT based solely on medical history with the correct diagnoses. We also compared the diagnoses made by ChatGPT after incorporating additional physical examination findings and laboratory data alongside history with the correct diagnoses. Results: ChatGPT accurately diagnosed 76.6% (23/30) of the cases with only the medical history, consistent with previous research targeting physicians. We also found that this rate was 93.3% (28/30) when additional information was included. Conclusions: Although adding additional information improves diagnostic accuracy, patient history remains a significant factor in AI-assisted medical diagnosis. Thus, when using AI in medical diagnosis, it is crucial to include pertinent and correct patient histories for an accurate diagnosis. Our findings emphasize the continued significance of patient history in clinical diagnoses in this age and highlight the need for its integration into AI-assisted medical diagnosis systems.

The differential diagnosis of medical and psychogenic disease in primary care.

Diagnosis and management of psychogenic diseases such as conversion disorder, somatic symptom disorder (SSD), illness anxiety disorder, falsehood disorder, and psychotic disorder require an elaborate biopsychosocial approach and are often challenging. Herein, we propose the following points to differentiate medical diseases from these psychogenic diseases: correspondence between symptoms and objective findings or activities of daily living (ADL) impairment; placebo effect; clear provocative or palliative factors; progressive time course; paroxysmal or intermittent symptoms; unfamiliar but not strange expressions; symptoms worsen during sleep or rest.

Do Japanese word-embedded representations obtained in the academic corpus retain the medical concepts of "infarction"?

OBJECTIVE: The pathophysiological concepts of diseases are encapsulated in patients' medical histories. Whether information on the pathophysiology or anatomy of "infarction" can be preserved and objectively expressed in the distributed representation obtained from a corpus of scientific Japanese medical texts in the "infarction" domain is currently unknown. Word2Vec was used to obtain distributed representations, meanings, and word analogies of word vectors, and this process was verified mathematically. MATERIALS & METHODS: The texts were abstracts that were obtained by searching for "infarction," "abstract," and "case report" in the Japan Medical Journal Association's Ichushi Data Base. The abstracted text was morphologically analyzed to produce word sequences converted into their standard form. MeCab was used for morphological analysis and mecab-ipadic-NEologd and ComeJisyo were used as dictionaries. The accuracy of the known tasks for medical terms was evaluated using a word analogy task specific to the "infarction" domain. RESULTS: Only 33 % of the word analogy tasks for medical terminology were correct. However, 52 % of the new original tasks, which were specific to the "infarction" domain, were correct, especially those regarding anatomical differences. DISCUSSION: Documents related to "infarction" were collected from a corpus of Japanese medical documents and word-embedded expressions were obtained using Word2Vec. Terminology that had similar meanings to "infarction" included words such as "cavity" and "ischemia," which suggest the pathology of an infarction. CONCLUSION: The pathophysiological and anatomical features of an "infarction" may be retained in a distributed representation.

Improving decision accuracy using a clinical decision support system for medical students during history-taking: a randomized clinical trial.

BACKGROUND: A clinical diagnostic support system (CDSS) can support medical students and physicians in providing evidence-based care. In this study, we investigate diagnostic accuracy based on the history of present illness between groups of medical students using a CDSS, Google, and neither (control). Further, the degree of diagnostic accuracy of medical students using a CDSS is compared with that of residents using neither a CDSS nor Google. METHODS: This study is a randomized educational trial. The participants comprised 64 medical students and 13 residents who rotated in the Department of General Medicine at Chiba University Hospital from May to December 2020. The medical students were randomly divided into the CDSS group (n = 22), Google group (n = 22), and control group (n = 20). Participants were asked to provide the three most likely diagnoses for 20 cases, mainly a history of a present illness (10 common and 10 emergent diseases). Each correct diagnosis was awarded 1 point (maximum 20 points). The mean scores of the three medical student groups were compared using a one-way analysis of variance. Furthermore, the mean scores of the CDSS, Google, and residents' (without CDSS or Google) groups were compared. RESULTS: The mean scores of the CDSS (12.0 ± 1.3) and Google (11.9 ± 1.1) groups were significantly higher than those of the control group (9.5 ± 1.7; p = 0.02 and p = 0.03, respectively). The residents' group's mean score (14.7 ± 1.4) was higher than the mean scores of the CDSS and Google groups (p = 0.01). Regarding common disease cases, the mean scores were 7.4 ± 0.7, 7.1 ± 0.7, and 8.2 ± 0.7 for the CDSS, Google, and residents' groups, respectively. There were no significant differences in mean scores (p = 0.1). CONCLUSIONS: Medical students who used the CDSS and Google were able to list differential diagnoses more accurately than those using neither. Furthermore, they could make the same level of differential diagnoses as residents in the context of common diseases. TRIAL REGISTRATION: This study was retrospectively registered with the University Hospital Medical Information Network Clinical Trials Registry on 24/12/2020 (unique trial number: UMIN000042831).

Do clinical interview transcripts generated by speech recognition software improve clinical reasoning performance in mock patient encounters? A prospective observational study.

BACKGROUND: To investigate whether speech recognition software for generating interview transcripts can provide more specific and precise feedback for evaluating medical interviews. METHODS: The effects of the two feedback methods on student performance in medical interviews were compared using a prospective observational trial. Seventy-nine medical students in a clinical clerkship were assigned to receive either speech-recognition feedback (n = 39; SRS feedback group) or voice-recording feedback (n = 40; IC recorder feedback group). All students' medical interviewing skills during mock patient encounters were assessed twice, first using a mini-clinical evaluation exercise (mini-CEX) and then a checklist. Medical students then made the most appropriate diagnoses based on medical interviews. The diagnostic accuracy, mini-CEX, and checklist scores of the two groups were compared. RESULTS: According to the study results, the mean diagnostic accuracy rate (SRS feedback group:1st mock 51.3%, 2nd mock 89.7%; IC recorder feedback group, 57.5%-67.5%; F(1, 77) = 4.0; p = 0.049), mini-CEX scores for overall clinical competence (SRS feedback group: 1st mock 5.2 ± 1.1, 2nd mock 7.4 ± 0.9; IC recorder feedback group: 1st mock 5.6 ± 1.4, 2nd mock 6.1 ± 1.2; F(1, 77) = 35.7; p < 0.001), and checklist scores for clinical performance (SRS feedback group: 1st mock 12.2 ± 2.4, 2nd mock 16.1 ± 1.7; IC recorder feedback group: 1st mock 13.1 ± 2.5, 2nd mock 13.8 ± 2.6; F(1, 77) = 26.1; p < 0.001) were higher with speech recognition-based feedback. CONCLUSIONS: Speech-recognition-based feedback leads to higher diagnostic accuracy rates and higher mini-CEX and checklist scores. TRIAL REGISTRATION: This study was registered in the Japan Registry of Clinical Trials on June 14, 2022. Due to our misunderstanding of the trial registration requirements, we registered the trial retrospectively. This study was registered in the Japan Registry of Clinical Trials on 7/7/2022 (Clinical trial registration number: jRCT1030220188).

Pubic Osteomyelitis in a Young Athlete.

We describe a case of pubic osteomyelitis in a 17-year-old Japanese male. The patient presented with acute left groin pain and left lower quadrant pain. He was evaluated at another hospital where pelvic X-ray/computed tomography was normal, and laboratory testing revealed only high C-reactive protein. Pelvic magnetic resonance imaging (MRI) on day three showed inflammation of the pubic attachment of the rectus abdominis muscle. Furthermore, a pelvic MRI performed 10 days after onset revealed a high signal on T2 short-TI inversion recovery in the left pubic bone, which was not found in the previous MRI, leading to a diagnosis of left pubic osteomyelitis. Symptoms improved rapidly after antibiotic therapy, and treatment was completed after six weeks. When a young athlete presents with fever and acute inguinal pain, osteomyelitis of the pubic bone should be considered as a differential diagnosis. This case report emphasizes the importance of taking a sports history during the interview and performing a repeat MRI for the early diagnosis of osteomyelitis of the pubic bone.

Hybrid PBL and Pure PBL: Which one is more effective in developing clinical reasoning skills for general medicine clerkship?-A mixed-method study.

This study aims to compare the effectiveness of Hybrid and Pure problem-based learning (PBL) in teaching clinical reasoning skills to medical students. The study sample consisted of 99 medical students participating in a clerkship rotation at the Department of General Medicine, Chiba University Hospital. They were randomly assigned to Hybrid PBL (intervention group, n = 52) or Pure PBL group (control group, n = 47). The quantitative outcomes were measured with the students' perceived competence in PBL, satisfaction with sessions, and self-evaluation of competency in clinical reasoning. The qualitative component consisted of a content analysis on the benefits of learning clinical reasoning using Hybrid PBL. There was no significant difference between intervention and control groups in the five students' perceived competence and satisfaction with sessions. In two-way repeated measure analysis of variance, self-evaluation of competency in clinical reasoning was significantly improved in the intervention group in "recalling appropriate differential diagnosis from patient's chief complaint" (F(1,97) = 5.295, p = 0.024) and "practicing the appropriate clinical reasoning process" (F(1,97) = 4.016, p = 0.038). According to multiple comparisons, the scores of "recalling appropriate history, physical examination, and tests on clinical hypothesis generation" (F(1,97) = 6.796, p = 0.011), "verbalizing and reflecting appropriately on own mistakes," (F(1,97) = 4.352, p = 0.040) "selecting keywords from the whole aspect of the patient," (F(1,97) = 5.607, p = 0.020) and "examining the patient while visualizing his/her daily life" (F(1,97) = 7.120, p = 0.009) were significantly higher in the control group. In the content analysis, 13 advantage categories of Hybrid PBL were extracted. In the subcategories, "acquisition of knowledge" was the most frequent subcategory, followed by "leading the discussion," "smooth discussion," "getting feedback," "timely feedback," and "supporting the clinical reasoning process." Hybrid PBL can help acquire practical knowledge and deepen understanding of clinical reasoning, whereas Pure PBL can improve several important skills such as verbalizing and reflecting on one's own errors and selecting appropriate keywords from the whole aspect of the patient.

Frequency of Difficult Patient Encounters in a Japanese University Hospital and Community Hospitals: A Cross-sectional Study.

Objective Difficult patient encounters (DPEs) are defined as encounters with patients causing strong negative feelings in physicians. In primary care settings, DPEs account for approximately 15% of visits among outpatients. To our knowledge, this is the first epidemiological study of DPEs in Japan. Methods We conducted a survey of 8 physicians (5.0±2 years of clinical experience) who examined first-visit patients ≥15 years old with clinical symptoms at the Department of General Medicine in Chiba University Hospital and 4 community hospitals over a 2-month period since December 2015. Materials We evaluated 10-Item Difficult Doctor-Patient Relationship Questionnaire (DDPRQ-10) scores (DPE ≥31 points; non-DPE ≤30 points) and patient age, sex, and presence of psychological or social problems. Results The valid response rate was 98.9% (94/95) and 98.4% (189/192) in the university and community hospitals, respectively. The percentage of DPEs was 39.8% (37/93) and 15.0% (26/173) in the university and community hospitals, respectively; the percentage of DPEs was significantly higher at the university hospital than at the community hospitals (p<0.001). The proportion of patients with psychosocial problems was significantly higher in the DPE group than in the non-DPE group (93.7% vs. 40.4%, p<0.001). Conclusion Our findings were similar to those reported in primary care settings in other countries in community hospital outpatient and general internal medicine departments, where patients are mostly non-referrals, although the values were higher in university hospital general medicine departments, where patients were mostly referrals. Patients involved in DPEs have a high rate of psychological and social problems.

Validating the representation of distance between infarct diseases using word embedding.

BACKGROUND: The pivot and cluster strategy (PCS) is a diagnostic reasoning strategy that automatically elicits disease clusters similar to a differential diagnosis in a batch. Although physicians know empirically which disease clusters are similar, there has been no quantitative evaluation. This study aimed to determine whether inter-disease distances between word embedding vectors using the PCS are a valid quantitative representation of similar disease groups in a limited domain. METHODS: Abstracts were extracted from the Ichushi Web database and subjected to morphological analysis and training using Word2Vec, FastText, and GloVe. Consequently, word embedding vectors were obtained. For words including "infarction," we calculated the cophenetic correlation coefficient (CCC) as an internal validity measure and the adjusted rand index (ARI), normalized mutual information (NMI), and adjusted mutual information (AMI) with ICD-10 codes as the external validity measures. This was performed for each combination of metric and hierarchical clustering method. RESULTS: Seventy-one words included "infarction," of which 38 diseases matched the ICD-10 standard with the appearance of 21 unique ICD-10 codes. When using Word2Vec, the CCC was most significant at 0.8690 (metric and method: euclidean and centroid), whereas the AMI was maximal at 0.4109 (metric and method: cosine and correlation, and average and weighted). The NMI and ARI were maximal at 0.8463 and 0.3593, respectively (metric and method: cosine and complete). FastText and GloVe generally resulted in the same trend as Word2Vec, and the metric and method that maximized CCC differed from the ones that maximized the external validity measures. CONCLUSIONS: The metric and method that maximized the internal validity measure differed from those that maximized the external validity measures; both produced different results. The cosine distance should be used when considering ICD-10, and the Euclidean distance when considering the frequency of word occurrence. The distributed representation, when trained by Word2Vec on the "infarction" domain from a Japanese academic corpus, provides an objective inter-disease distance used in PCS.

The relationship between CPAP and health literacy: A prospective observational study.

Background: We aimed to assess differences in health literacy between those who improved CPAP non-adherent and those who remained non-adherent. Methods: We included patients newly diagnosed with sleep apnea syndrome who had started CPAP therapy between February 2019 and October 2020 with ≥6 follow-up months or who self-interrupted CPAP therapy <6 months. We recorded the CPAP wearing time after 3 and 6 months. Patients were divided into the CPAP adherent (using CPAP for ≥4 h per night) and non-adherent (self-interrupted CPAP therapy/using CPAP for <4 h per night) groups. We compared the European Health Literacy Survey Questionnaire 47 (HLS-EU-Q47) score between those who were CPAP non-adherent after 3 months and become CPAP adherent after 6 months, and those who remained non-adherent after 6 months. Results: At 3 months, 34 patients were CPAP non-adherent. After 6 months, there were 7 and 27 patients in the CPAP adherent and non-adherent groups, respectively. There was a significant difference in the HLS-EU-Q47 score between the patients who became adherent to CPAP and who remained non-adherent after 6 months. Conclusion: Previously non-adherent patients who subsequently became adherent tended to have higher health literacy.

Behavior-based medical diagnosis-Applying perspectives of behavioral science to clinical reasoning.

Behavioral science, the scientific study of human behavior and the elucidation of its laws, is also applied to medicine, and is included in pre-graduate education.Understanding patient behaviors that correspond to behavior-based medical diagnosis and interpreting the clinical information suggested by these patient behaviors can be useful in avoiding diagnostic errors in clinical practice.

The flipped classroom is effective for medical students to improve deep tendon reflex examination skills: A mixed-method study.

Deep tendon reflexes (DTR) are a prerequisite skill in clinical clerkships. However, many medical students are not confident in their technique and need to be effectively trained. We evaluated the effectiveness of a flipped classroom for teaching DTR skills. We recruited 83 fifth-year medical students who participated in a clinical clerkship at the Department of General Medicine, Chiba University Hospital, from November 2018 to July 2019. They were allocated to the flipped classroom technique (intervention group, n = 39) or the traditional technique instruction group (control group, n = 44). Before procedural teaching, while the intervention group learned about DTR by e-learning, the control group did so face-to-face. A 5-point Likert scale was used to evaluate self-confidence in DTR examination before and after the procedural teaching (1 = no confidence, 5 = confidence). We evaluated the mastery of techniques after procedural teaching using the Direct Observation of Procedural Skills (DOPS). Unpaired t-test was used to analyze the difference between the two groups on the 5-point Likert scale and DOPS. We assessed self-confidence in DTR examination before and after procedural teaching using a free description questionnaire in the two groups. Additionally, in the intervention group, focus group interviews (FGI) (7 groups, n = 39) were conducted to assess the effectiveness of the flipped classroom after procedural teaching. Pre-test self-confidence in the DTR examination was significantly higher in the intervention group than in the control group (2.8 vs. 2.3, P = 0.005). Post-test self-confidence in the DTR examination was not significantly different between the two groups (3.9 vs. 4.1, P = 0.31), and so was mastery (4.3 vs. 4.1, P = 0.68). The questionnaires before the procedural teaching revealed themes common to the two groups, including "lack of knowledge" and "lack of self-confidence." Themes about prior learning, including "acquisition of knowledge" and "promoting understanding," were specific in the intervention group. The FGI revealed themes including "application of knowledge," "improvement in DTR technique," and "increased self-confidence." Based on these results, teaching DTR skills to medical students in flipped classrooms improves readiness for learning and increases self-confidence in performing the procedure at a point before procedural teaching.

Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case-control study in Japan.

OBJECTIVE: To clarify the factors associated with prolonged hospital stays, focusing on the COMplexity PRediction Instrument (COMPRI) score's accuracy in predicting the length of stay of newly hospitalised patients in general internal medicine wards. DESIGN: A case-control study. SETTING: Three general internal medicine wards in Chiba Prefecture, Japan. PARTICIPANTS: Thirty-four newly hospitalised patients were recruited between November 2017 and December 2019, with a final analytic sample of 33 patients. We included hospitals in different cities with general medicine outpatient and ward facilities, who agreed to participate. We excluded any patients who were re-hospitalised within 2 weeks of a prior discharge. PRIMARY AND SECONDARY OUTCOME MEASURES: Patients' COMPRI scores and their consequent lengths of hospital stay. RESULTS: The 17 patients (52%) allocated to the long-term hospitalisation group (those hospitalised ≥14 days) had a significantly higher average age, COMPRI score and percentage of participants with comorbid chronic illnesses than the short-term hospitalisation group (<14 days). A logistic regression model (model A, comprising only the COMPRI score as the explanatory variable) and a multiple logistic regression model (model B, comprising variables other than the COMPRI score as explanatory variables) were created as prediction models for the long-term hospitalisation group. When age ≥75 years, a COMPRI score ≥6 and a physician with 10 years' experience were set as explanatory variables, model A showed better predictive accuracy compared with model B (fivefold cross-validation, area under curve of 0.87 vs 0.78). The OR of a patient with a COMPRI score of ≥6 joining the long-term hospitalisation group was 4.25 (95% CI=1.43 to 12.63). CONCLUSIONS: Clinicians can use the COMPRI score when screening for complexity assessment to identify hospitalised patients at high risk of prolonged hospitalisation. Providing such patients with multifaceted and intensive care may shorten hospital stays.

Mortality risk in older Japanese people based on self-reported dyslipidemia treatment and socioeconomic status: The JAGES cohort study.

Few studies consider socioeconomic status when assessing mortality risk in dyslipidemia cases. This study used cohort data from the 2010 Japan Gerontological Evaluation Study (JAGES), which contains data on older Japanese people, to associate socioeconomic status with mortality risk in patients treated for dyslipidemia. In this 6-year longitudinal study, we examined 47,275 older Japanese people aged ≥ 65 years who could independently perform activities of daily living. Patients' background characteristics were classified based on their dyslipidemia treatment status and were assessed using the chi-squared test. The mortality risk was assessed using the Cox proportional hazards model, wherein the objective and explanatory variables were total mortality and self-report of dyslipidemia treatment, respectively. The participants were stratified by sex and age into younger (aged 65-74 years) and older (aged ≥ 75 years) groups of men and women. The results were adjusted, with health condition, health behavior, and socioeconomic status as confounding factors. The adjusted hazard ratios of 5514 people who died during the follow-up who had self-reported dyslipidemia treatment were 0.49 [95% confidence interval (CI) 0.35-0.69] for younger men; 0.57 (95% CI 0.42-0.76) for older men; 0.52 (95% CI 0.34-0.80) for younger women; and 0.47 (95% CI 0.33-0.67) for older women. Older people undergoing treatment for dyslipidemia had factors beneficial for health, such as good socioeconomic status. Despite considering these factors, individuals undergoing dyslipidemia treatment had a negative association with mortality risk.