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Shun Yamashita,1 Hiroyuki Nagano,2 Taku Harada,3 Taiju Miyagami,4 Kosuke Ishizuka,5 Masatomi Ikusaka5 1Department of General Medicine, Saga University Hospital, Saga, Japan; 2Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Kyoto, Japan; 3Division of General Medicine, Showa University Koto Toyosu Hospital, Tokyo, Japan; 4Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo, Japan; 5Department of General Medicine, Chiba University Hospital, Chiba, JapanCorrespondence: Shun Yamashita, Department of General Medicine, Saga University Hospital, Saga University, 5-1-1 Nabeshima, Saga, 849-8501, Japan, Tel +81952343238, Fax +81952342029, Email sy.hospitalist.japan@gmail.comAbstract: Demand is increasing for general medicine services in Japan, a super-aged society. The new medical specialty system introduced in 2019 obligates physicians to obtain a qualified specialty from among 19 basic specialty fields, including general medicine, before obtaining more advanced qualified subspecialties. The role of the department of general medicine in Japan varies in each hospital. Remuneration for medical services obtained by general medicine departments that mainly provide outpatient care is relatively low, making it difficult to fill positions in this department within a hospital. We conducted a narrative review and discussed ways to increase the status of hospital general medicine departments that mainly provide outpatient care. We consider the following four points to be important: improvement of diagnostic capabilities in the outpatient setting; playing a central role in education for medical students and residents; active involvement with patients who have diagnostic difficulties or social problems; and branding and promotion of the general medicine department. We envision that adopting an active approach to these points will increase the status of general medicine departments that mainly provide outpatient care within the hospital, allowing such newly established departments to start easily in Japanese hospitals in the future.Keywords: general medicine, outpatient, diagnostic capability, education, difficult diagnosis, branding

Daiki Yokokawa,1 Kiyoshi Shikino,1 Yasuhiro Kishi,2 Masatomi Ikusaka1 1Department of General Medicine, Chiba University Hospital, Chiba, Japan; 2Department of Psychiatry, Nippon Medical School Musashikosugi Hospital, Kanagawa, JapanCorrespondence: Daiki Yokokawa, Department of General Medicine, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba City, Chiba, 260-8677, Japan, Tel/Fax +81-43-224-4758, Email dyokokawa6@gmail.comPurpose: This study aims to translate and ensure cross-cultural adaptation of a Japanese version of the INTERMED Self-Assessment Questionnaire (IMSA).Methods: A family medicine physician, a medical education specialist, a psychiatrist who prepared the Japanese version of the INTERMED, and two members of the INTERMED consortium were selected as committee members. We used the standard forward and backward translation method to translate the IMSA into Japanese. After translating the original IMSA into Japanese, all committee members discussed and reached a consensus on the proposed translation. The back-translation was performed by an English native professional translator who did not know the original text. We contacted the INTERMED consortium and asked them to review the conceptual equivalence of the back-translated Japanese version with the original version; after two reviews, the members approved the Japanese version. Thereafter, we conducted cognitive debriefings with four patients and nine healthcare professionals to ensure cross-cultural adaptation.Results: The members of the INTERMED consortium approved the use of the Japanese version. We modified some expressions and words, while retaining the original meaning, to make it easier for Japanese patients to understand.Conclusion: We developed a Japanese version of the IMSA. A future study will investigate the construct criterion-related validity and the reliability of the scale.Keywords: IMSA, Japanese version, translation, patient-case complexity

Kiyoshi Shikino1,2, Shoichi Ito2,3, Yoshiyuki Ohira,1 Kazutaka Noda,1 Mayumi Asahina2,3, Masatomi Ikusaka1,21Department of General Medicine, Chiba University Hospital, Chiba, Japan; 2Health Professional Development Center, Chiba University Hospital, Chiba, Japan; 3Office of Medical Education, Chiba University Graduate School of Medicine, Chiba, JapanObjective: To evaluate a short-time simulation training seminar on how to handle difficult patients using professional simulated patients (SPs) such as actors.Participants: Sixty-three second-year residents at Chiba University Hospital between 2015 and 2017 who only attended the seminar once.Intervention: The participants were divided into small groups, each of which was assigned a supervisory doctor as facilitator. Those who were playing the doctor’s role enacted a medical interview with an SP. After the interview, the facilitator, the SP, and the observing residents participated in a debriefing while watching a recorded video of the interview.Outcome measures: Pre- and post-seminar questionnaires using a 7-point Likert scale (from 1: strongly disagree to 7: strongly agree) were used to examine the differences in “confidence in ability to handle difficult patients” and “learning motivation to handle difficult patients”. The two items examined by both pre- and post-seminar questionnaires, were analyzed by a paired t-test. The residents were also surveyed on their satisfaction with the seminar, acquisition of new knowledge, and impressions and comments (free-text answers).Results: The findings of the questionnaire showed a significant post-seminar increase in confidence (3.1±1.6 to 4.0±1.5 [p

Fumio Shimada, Yoshiyuki Ohira, Yusuke Hirota, Akiko Ikegami, Takeshi Kondo, Kiyoshi Shikino, Shingo Suzuki, Kazutaka Noda, Takanori Uehara, Masatomi Ikusaka Department of General Medicine, Chiba University Hospital, Chiba, Japan Background and objectives: Patients who come for a consultation at a general practice clinic as outpatients often suffer from background anxiety and depression. The psychological state of such patients can alleviate naturally; however, there are cases when these symptoms persist. This study investigated the realities and factors behind anxiety/depression becoming prolonged.Methods: Participants were 678 adult patients, who came to Department of General Medicine at Chiba University Hospital within a 1-year period starting from April 2012 and who completed the Hospital Anxiety and Depression Scale (HADS) during their initial consultation. Participants whose Anxiety or Depression scores in the HADS, or both, were 8 points or higher were defined as being within the anxiety/depression group, with all other participants making up the control group. A telephone interview was also conducted with participants. Furthermore, age, sex, the period from the onset of symptoms to the initial consultation at our department, the period from the initial department consultation to the telephone survey, and the existence of mental illness at the final department diagnosis were investigated.Results: A total of 121 patients (17.8% response rate) agreed to the phone survey. The HADS score during the phone survey showed that the anxiety/depression group had a significantly higher score than the control group. The HADS scores obtained between the initial consultation and telephone survey showed a positive correlation. Logistic regression analysis extracted “age” and the “continuation of the symptoms during the initial consultation” as factors that prolonged anxiety/depression.Conclusion: Anxiety and depression in general practice outpatients have the possibility of becoming prolonged for an extended period of time. Being aged 65 years or over and showing a continuation of symptoms past the initial consultation are the strongest factors associated with these prolonged conditions. When patients with anxiety and depression exhibit these risk factors, they should be further evaluated for treatment. Keywords: anxiety, depression, outpatients, general practice

Shingo Suzuki, Yoshiyuki Ohira, Kazutaka Noda, Masatomi Ikusaka Department of General Medicine, Chiba University Hospital, Chiba, Japan Purpose: To develop a clinical score to discriminate patients with somatic symptom disorder (SSD) from those with medical disease (MD) for complaints of non-acute pain.Methods: We retrospectively examined the clinical records of consecutive patients with pain for a duration of ≥1 month in our department from April 2003 to March 2015. We divided the subjects according to the diagnoses of definite SSD (as diagnosed and tracked by psychiatrists in our hospital), probable SSD (without evaluation by psychiatrists in our hospital), matched MD (randomly matched two patients by age, sex, and pain location for each definite SSD patient), unmatched MD, other mental disease, or functional somatic syndrome (FSS). We investigated eight clinical factors for definite SSD and matched MD, and developed a diagnostic score to ­identify SSD. We subsequently validated the model with cases of probable SSD and unmatched MD.Results: The number of patients with definite SSD, probable SSD, matched MD, unmatched MD, other mental disease, and FSS was 104 (3.5%), 214 (7.3%), 197 (6.7%), 742 (25%), 708 (24%), and 978 (33%), respectively. In a conditional logistic regression analysis, the following five factors were included as independent predictors of SSD: Analgesics ineffective, Mental disorder history, Unclear provocative/palliative factors, Persistence without cessation, and Stress feelings/episodes (A-MUPS). The area under the receiver operating characteristic curve (AUC) of the model was 0.900 (95% CI: 0.864–0.937, p

Hideki Kajiwara,1 Yoshiyuki Ohira,1 Akiko Ikegami,1 Nao Hanazawa,1 Takako Masuyama,1,2 Tomoko Yamashita,1 Takeshi Kondo,1 Kiyoshi Shikino,1 Masatomi Ikusaka1 1Department of General Medicine, Chiba University Hospital, Chiba-shi, 2Department of General Medicine, Kimitsu Chuo Hospital, Kisarazu-shi, Chiba, Japan Introduction: Anxiety and depressive symptoms are seen in patients with anxiety and mood disorders but are also common in those with organic disorders. However, since physical symptoms are predominant complaints from patients who visit nonpsychiatric outpatient clinics, anxiety and depressive symptoms are often unrecognized. It is important for physicians to be aware of these issues concurrent with the physical symptoms. We therefore examined whether a self-administered medical questionnaire could identify anxiety and depressive symptoms.Patients and methods: A total of 453 patients on their first visit to the Department of General Medicine, Chiba University Hospital, Chiba, Japan, participated in this study. They were asked to complete a medical questionnaire and the Hospital Anxiety and Depression Scale questionnaire before examination. Data on age, sex, number of complaints, symptom duration, and number of previous physicians were extracted from the medical questionnaire. These data were used as independent variables in logistic regression analysis to develop a predictive model for the presence of anxiety and depressive symptoms.Results: Data from 358 (79.0%) patients were included in the analyses. Logistic regression analysis identified the following predictors: “three or more complaints” (odds ratio [OR] 2.39; 95% confidence interval [CI] 1.48–3.88) and “four or more previous physicians” (OR 1.72; 95% CI 1.10–2.69). In the predictive model for the presence of symptoms of anxiety and depression, the likelihood ratio was 2.40 (95% CI 1.33–4.34) in patients reporting both conditions and 1.35 (95% CI 1.04–1.77) in those reporting either condition.Conclusion: The presence of anxiety and depressive symptoms can be predicted from the items of a medical questionnaire in outpatients visiting a general medicine department of a university hospital. When patients report three or more complaints or four or more previous physicians on a medical questionnaire, physicians should consider the presence of anxiety or depression or both in differential diagnosis. Keywords: anxiety, depression, Hospital Anxiety and Depression Scale, HADS, complaint numbers, number of previous physicians, medical questionnaire

Kiyoshi Shikino, Masatomi Ikusaka, Yoshiyuki Ohira, Masahito Miyahara, Shingo Suzuki, Misa Hirukawa, Kazutaka Noda, Tomoko Tsukamoto, Takanori Uehara Department of General Medicine, Chiba University Hospital, Chiba, Chiba Prefecture, Japan Background: This study aimed to clarify the influence of predicting a correct diagnosis from the history on physical examination by comparing the diagnostic accuracy of auscultation with and without clinical information. Methods: The participants were 102 medical students from the 2013 clinical clerkship course. Auscultation was performed with a cardiology patient simulator. Participants were randomly assigned to two groups. Each group listened to a different simulated heart murmur and then made a diagnosis without clinical information. Next, a history suggesting a different murmur was provided to each group and they predicted the diagnosis. Finally, the students listened to a murmur corresponding to the history provided and again made a diagnosis. Correct and incorrect diagnosis rates of auscultation were compared between students with and without clinical information, between students predicting a correct or incorrect diagnosis from the history (correct and incorrect prediction groups, respectively), and between students without clinical information and those making an incorrect prediction. Results: For auscultation with or without clinical information, the correct diagnosis rate was 62.7% (128/204 participants) versus 54.4% (111/204 participants), showing no significant difference (P=0.09). After receiving clinical information, a correct diagnosis was made by 102/117 students (87.2%) in the correct prediction group versus 26/87 students (29.9%) in the incorrect prediction group, showing a significant difference (P=0.006). The correct diagnosis rate was also significantly lower in the incorrect prediction group than when the students performed auscultation without clinical information (54.4% versus 29.9%, P

Takanori Uehara,1,2 Masatomi Ikusaka,1 Yoshiyuki Ohira,1 Mitsuyasu Ohta,1,2 Kazutaka Noda,1 Tomoko Tsukamoto,1 Toshihiko Takada,1 Masahito Miyahara11Department of General Medicine, Chiba University Hospital, 2Division of Rotated Collaboration Systems for Local Healthcare, Graduate School of Medicine, Chiba University, Chiba, JapanPurpose: To compare the diagnostic accuracy of diseases predicted from patient responses to a simple questionnaire completed prior to examination by doctors with different levels of ambulatory training in general medicine.Participants and methods: Before patient examination, five trained physicians, four short-term-trained residents, and four untrained residents examined patient responses to a simple questionnaire and then indicated, in rank order according to their subjective confidence level, the diseases they predicted. Final diagnosis was subsequently determined from hospital records by mentor physicians 3 months after the first patient visit. Predicted diseases and final diagnoses were codified using the International Classification of Diseases version 10. A “correct” diagnosis was one where the predicted disease matched the final diagnosis code.Results: A total of 148 patient questionnaires were evaluated. The Herfindahl index was 0.024, indicating a high degree of diversity in final diagnoses. The proportion of correct diagnoses was high in the trained group (96 of 148, 65%; residual analysis, 4.4) and low in the untrained group (56 of 148, 38%; residual analysis, -3.6) (χ2=22.27, P

Kazutaka Noda, Masatomi Ikusaka, Yoshiyuki Ohira, Toshihiko Takada, Tomoko TsukamotoDepartment of General Medicine, Chiba University Hospital, Chiba, JapanObjective: Patient medical history is important for making a diagnosis of causes of dizziness, but there have been no studies on the diagnostic value of individual items in the history. This study was performed to identify and validate useful questions for suspecting a diagnosis of benign paroxysmal positional vertigo (BPPV).Methods: Construction and validation of a disease prediction model was performed at the outpatient clinic in the Department of General Medicine of Chiba University Hospital. Patients with dizziness were enrolled (145 patients for construction of the disease prediction model and 61 patients for its validation). This study targeted BPPV of the posterior semicircular canals only with a positive Dix–Hallpike test (DHT + BPPV) to avoid diagnostic ambiguity. Binomial logistic regression analysis was performed to identify the items that were useful for diagnosis or exclusion of DHT + BPPV.Results: Twelve patients from the derivation set and six patients from the validation set had DHT + BPPV. Binomial logistic regression analysis selected a "duration of dizziness ≤15 seconds" and "onset when turning over in bed" as independent predictors of DHT + BPPV with an odds ratio (95% confidence interval) of 4.36 (1.18–16.19) and 10.17 (2.49–41.63), respectively. Affirmative answers to both questions yielded a likelihood ratio of 6.81 (5.11–9.10) for diagnosis of DHT + BPPV, while negative answers to both had a likelihood ratio of 0.19 (0.08–0.47).Conclusion: A "duration of dizziness ≤15 seconds" and "onset when turning over in bed" were the two most important questions among various historical features of BPPV.Keywords: benign paroxysmal positional vertigo, likelihood ratio, diagnosis, screening, prediction rules

CASE REPORT Hoffmann-Tinelsignandentrapmentneuropathy K.Ishizuka,T.Uehara,D.Yokokawa,K.NodaandM.Ikusaka Department of General Medicine, Chiba University Hospital, 1-8-1 Inohana, Chuo-Ku, Chiba-City 260-8677, ChibaPrefecture,Japan Address correspondence to K. Ishizuka, Department of General Medicine, Chiba University Hospital, 1-8-1 Inohana, Chuo-Ku, Chiba-City 260-8677, Chiba Prefecture,Japan.email:e103007c@yokohama-cu.ac.jp Learning point for clinicians Identification of Hoffmann-Tinel sign at the site of nerve injury is essential in physical examination, and nerve conduction studies can confirm the distribution of nerve injury. Nerve conduction study demonstrated no response by either the common peroneal nerve or tibial nerve. Identification of Hoffmann-Tinel sign at the site of nerve injury is essential in physical examination, and nerve conduction studiescanconfirmthedistributionofnerveinjury. [Extracted from the article]

Background: Creating clinical vignettes requires considerable effort. Recent developments in generative artificial intelligence (AI) for natural language processing have been remarkable and may allow for the easy and immediate creation of diverse clinical vignettes., Objective: In this study, we evaluated the medical accuracy and grammatical correctness of AI-generated clinical vignettes in Japanese and verified their usefulness., Methods: Clinical vignettes were created using the generative AI model GPT-4-0613. The input prompts for the clinical vignettes specified the following seven elements: (1) age, (2) sex, (3) chief complaint and time course since onset, (4) physical findings, (5) examination results, (6) diagnosis, and (7) treatment course. The list of diseases integrated into the vignettes was based on 202 cases considered in the management of diseases and symptoms in Japan's Primary Care Physicians Training Program. The clinical vignettes were evaluated for medical and Japanese-language accuracy by three physicians using a five-point scale. A total score of 13 points or above was defined as "sufficiently beneficial and immediately usable with minor revisions," a score between 10 and 12 points was defined as "partly insufficient and in need of modifications," and a score of 9 points or below was defined as "insufficient.", Results: Regarding medical accuracy, of the 202 clinical vignettes, 118 scored 13 points or above, 78 scored between 10 and 12 points, and 6 scored 9 points or below. Regarding Japanese-language accuracy, 142 vignettes scored 13 points or above, 56 scored between 10 and 12 points, and 4 scored 9 points or below. Overall, 97% (196/202) of vignettes were available with some modifications., Conclusion: Overall, 97% of the clinical vignettes proved practically useful, based on confirmation and revision by Japanese medical physicians. Given the significant effort required by physicians to create vignettes without AI, using GPT is expected to greatly optimize this process., (© 2024. The Author(s).)

This study tests whether comprehensively gathering information from medical records is useful for developing clinical decision support systems using Bayes' theorem. Using a single-center cross-sectional study, we retrospectively extracted medical records of 270 patients aged ≥16 years who visited the emergency room at the Tokyo Metropolitan Tama Medical Center with a chief complaint of experiencing headaches. The medical records of cases were analyzed in this study. We manually extracted diagnoses, unique keywords, and annotated keywords, classifying them as either positive or negative. Cross tables were created, and the proportion of combinations for which the likelihood ratios could be calculated was evaluated. Probability functions for the appearance of new unique keywords were modeled, and theoretical values were calculated. We extracted 623 unique keywords, 26 diagnoses, and 6,904 annotated keywords. Likelihood ratios could be calculated only for 276 combinations (1.70%), of which 24 (0.15%) exhibited significant differences. The power function+constant was the best fit for new unique keywords. The increase in the number of combinations after increasing the number of cases indicated that while it is theoretically possible to comprehensively gather information from medical records in this way, doing so presents difficulties related to human costs. It also does not necessarily solve the fundamental issues with medical informatics or with developing clinical decision support systems. Therefore, we recommend using methods other than comprehensive information gathering with Bayes' theorem as the classifier to develop such systems., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Yokokawa et al.)

Background: An illness script is a specific script format geared to represent patient-oriented clinical knowledge organized around enabling conditions, faults (i.e., pathophysiological process), and consequences. Generative artificial intelligence (AI) stands out as an educational aid in continuing medical education. The effortless creation of a typical illness script by generative AI could help the comprehension of key features of diseases and increase diagnostic accuracy. No systematic summary of specific examples of illness scripts has been reported since illness scripts are unique to each physician., Objective: This study investigated whether generative AI can generate illness scripts., Methods: We utilized ChatGPT-4, a generative AI, to create illness scripts for 184 diseases based on the diseases and conditions integral to the National Model Core Curriculum in Japan for undergraduate medical education (2022 revised edition) and primary care specialist training in Japan. Three physicians applied a three-tier grading scale: "A" denotes that the content of each disease's illness script proves sufficient for training medical students, "B" denotes that it is partially lacking but acceptable, and "C" denotes that it is deficient in multiple respects., Results: By leveraging ChatGPT-4, we successfully generated each component of the illness script for 184 diseases without any omission. The illness scripts received "A," "B," and "C" ratings of 56.0% (103/184), 28.3% (52/184), and 15.8% (29/184), respectively., Conclusion: Useful illness scripts were seamlessly and instantaneously created using ChatGPT-4 by employing prompts appropriate for medical students. The technology-driven illness script is a valuable tool for introducing medical students to key features of diseases., (© 2024. The Author(s).)

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., (© Fumitoshi Fukuzawa, Yasutaka Yanagita, Daiki Yokokawa, Shun Uchida, Shiho Yamashita, Yu Li, Kiyoshi Shikino, Tomoko Tsukamoto, Kazutaka Noda, Takanori Uehara, Masatomi Ikusaka. Originally published in JMIR Medical Education (https://mededu.jmir.org).)

Kikuchi-Fujimoto disease (KFD), also called histiocytic necrotizing lymphadenitis, is more common in young women and typically presents with small, painful, localized cervical lymphadenopathy that resolves spontaneously within a few weeks. Laboratory findings are variable. As many as 40% of KFD cases are reported to be painless, and up to 22% to be generalized lymphadenopathy. Therefore, malignant lymphoma could be a differential diagnosis of KFD. A histopathologic diagnosis is needed when it is difficult to distinguish KFD from lymphoma. KFD typically shows small, highly accumulated cervical lymph nodes on fluorodeoxyglucose positron emission tomography (FDG-PET). This contrasts with malignant lymphoma, which tends to be associated with massive lymphadenopathy. In our case, a 40-year-old Japanese male presented with painless lumps in the right neck, accompanied by fever, night sweats, and loss of appetite. His symptoms and laboratory results worsened over a month. FDG-PET revealed highly accumulated uptake in cervical, mediastinal, and axillary lymph nodes. The PET imaging showed a small, high FDG uptake and contributed to the correct diagnosis of KFD. This case report highlights the importance of FDG-PET, which is a valuable diagnostic tool for KFD as it typically differentiates large clusters of small lymph nodes typical of KFD from normal lymph nodes., Learning Points: Kikuchi-Fujimoto disease (KFD) typically presents with small, painful, localised cervical lymphadenopathy.KFD has atypical patterns showing painless and generalised lymphadenopathy.Fluorodeoxyglucose positron emission tomography (FDG-PET) could be useful for diagnosing not only malignant lymphoma but also KFD., Competing Interests: Conflicts of Interests: The Authors declare that there are no competing interests., (© EFIM 2024.)

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., Competing Interests: None., (© 2023 The Authors. Journal of General and Family Medicine published by John Wiley & Sons Australia, Ltd on behalf of Japan Primary Care Association.)

Background: The gamification of learning increases student enjoyment, and motivation and engagement in learning tasks. This study investigated the effects of gamification using decision-making cards (DMCs) on diagnostic decision-making and cost using case scenarios., Method: Thirty medical students in clinical clerkship participated and were randomly assigned to 14 small groups of 2-3 medical students each. Decision-making was gamified using DMCs with a clinical information heading and medical cost on the front, and clinical information details on the back. First, each team was provided with brief clinical information on case scenarios. Subsequently, DMCs depending on the case were distributed to each team, and team members chose cards one at a time until they reached a diagnosis of the case. The total medical cost was then scored based on the number and contents of cards drawn. Four case scenarios were conducted. The quantitative outcomes including confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical costs were measured before and after our gamification by self-evaluation using a 7-point Likert scale. The qualitative component consisted of a content analysis on the benefits of learning clinical reasoning using DMCs., Result: Confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost were significantly higher after the gamification. Furthermore, comparing the clinical case scenario tackled last with the one tackled first, the average medical cost of all cards drawn by students decreased significantly from 11,921 to 8,895 Japanese yen. In the content analysis, seven advantage categories of DMCs corresponding to clinical reasoning components were extracted (information gathering, hypothesis generation, problem representation, differential diagnosis, leading or working diagnosis, diagnostic justification, and management and treatment)., Conclusion: Teaching medical students clinical reasoning using DMCs can improve clinical decision-making confidence and learning motivation, and reduces medical cost in clinical case scenarios. In addition, it can help students to acquire practical knowledge, deepens their understanding of clinical reasoning, and identifies several important clinical reasoning skills including diagnostic decision-making and awareness of medical costs. Gamification using DMCs can be an effective teaching method for improving medical students' diagnostic decision-making and reducing costs., (© 2023. The Author(s).)

Background: ChatGPT (OpenAI) has gained considerable attention because of its natural and intuitive responses. ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers, as stated by OpenAI as a limitation. However, considering that ChatGPT is an interactive AI that has been trained to reduce the output of unethical sentences, the reliability of the training data is high and the usefulness of the output content is promising. Fortunately, in March 2023, a new version of ChatGPT, GPT-4, was released, which, according to internal evaluations, was expected to increase the likelihood of producing factual responses by 40% compared with its predecessor, GPT-3.5. The usefulness of this version of ChatGPT in English is widely appreciated. It is also increasingly being evaluated as a system for obtaining medical information in languages other than English. Although it does not reach a passing score on the national medical examination in Chinese, its accuracy is expected to gradually improve. Evaluation of ChatGPT with Japanese input is limited, although there have been reports on the accuracy of ChatGPT's answers to clinical questions regarding the Japanese Society of Hypertension guidelines and on the performance of the National Nursing Examination., Objective: The objective of this study is to evaluate whether ChatGPT can provide accurate diagnoses and medical knowledge for Japanese input., Methods: Questions from the National Medical Licensing Examination (NMLE) in Japan, administered by the Japanese Ministry of Health, Labour and Welfare in 2022, were used. All 400 questions were included. Exclusion criteria were figures and tables that ChatGPT could not recognize; only text questions were extracted. We instructed GPT-3.5 and GPT-4 to input the Japanese questions as they were and to output the correct answers for each question. The output of ChatGPT was verified by 2 general practice physicians. In case of discrepancies, they were checked by another physician to make a final decision. The overall performance was evaluated by calculating the percentage of correct answers output by GPT-3.5 and GPT-4., Results: Of the 400 questions, 292 were analyzed. Questions containing charts, which are not supported by ChatGPT, were excluded. The correct response rate for GPT-4 was 81.5% (237/292), which was significantly higher than the rate for GPT-3.5, 42.8% (125/292). Moreover, GPT-4 surpassed the passing standard (>72%) for the NMLE, indicating its potential as a diagnostic and therapeutic decision aid for physicians., Conclusions: GPT-4 reached the passing standard for the NMLE in Japan, entered in Japanese, although it is limited to written questions. As the accelerated progress in the past few months has shown, the performance of the AI will improve as the large language model continues to learn more, and it may well become a decision support system for medical professionals by providing more accurate information., (©Yasutaka Yanagita, Daiki Yokokawa, Shun Uchida, Junsuke Tawara, Masatomi Ikusaka. Originally published in JMIR Formative Research (https://formative.jmir.org), 13.10.2023.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Physicians frequently experience patients as difficult. Our study explores whether more empathetic physicians experience fewer patient encounters as difficult., Objective: To investigate the association between physician empathy and difficult patient encounters (DPEs)., Design: Cross-sectional study., Participants: Participants were 18 generalist physicians with 3-8 years of experience. The investigation was conducted from August-September 2018 and April-May 2019 at six healthcare facilities., Main Measures: Based on the Jefferson Scale of Empathy (JSE) scores, we classified physicians into low and high empathy groups. The physicians completed the Difficult Doctor-Patient Relationship Questionnaire-10 (DDPRQ-10) after each patient visit. Scores ≥ 31 on the DDPRQ-10 indicated DPEs. We implemented multilevel mixed-effects logistic regression models to examine the association between physicians' empathy and DPE, adjusting for patient-level covariates (age, sex, history of mental disorders) and with physician-level clustering., Key Results: The median JSE score was 114 (range: 96-126), and physicians with JSE scores 96-113 and 114-126 were assigned to low and high empathy groups, respectively (n = 8 and 10 each); 240 and 344 patients were examined by physicians in the low and high empathy groups, respectively. Among low empathy physicians, 23% of encounters were considered difficulty, compared to 11% among high empathy groups (OR: 0.37; 95% CI = 0.19-0.72, p = 0.004). JSE scores and DDPRQ-10 scores were negatively correlated (r = -0.22, p < 0.01)., Conclusion: Empathetic physicians were less likely to experience encounters as difficult. Empathy appears to be an important component of physician perception of encounter difficulty., (© 2022. The Author(s), under exclusive licence to Society of General Internal Medicine.)

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)., (© 2023. The Author(s).)

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)., (© 2023. The Author(s).)

Angina bullosa haemorrhagica (ABH) is a disease of unknown cause that occurs most frequently in middle-aged and older adults and is characterized by the destruction of blood vessels in the submucosal layer of the middle pharynx and larynx centred on the soft palate, resulting in the formation of haemorrhagic blisters. It usually resolves within a day and heals without scarring within about a week. No treatment is necessary. However, cases of airway obstruction due to haematemesis have been reported, and this potential risk should be considered when tracheal intubation or upper gastrointestinal endoscopy is being performed. In this report, we describe the case of a 50-year-old man who developed a haematoma in the pharynx following upper endoscopy, which spontaneously ruptured and healed, leading to the diagnosis of ABH. The main purpose of this case report is to remind the reader that ABH improves without treatment, thus eliminating the need for unnecessary examination, and that there is a risk of airway obstruction depending on the site of the lesion., Learning Points: The key to the diagnosis of angina bullosa haemorrhagica (ABH) is a history of acute haemorrhagic vesicles caused by an external stimulus such as food or intubation, which resolve without scarring within a week or so.ABH can occur at any oropharyngeal site, but its occurrence in the pharyngeal region raises the risk of airway obstruction due to haematemesis., Competing Interests: Conflicts of Interests: The Authors declare that there are no competing interests., (© EFIM 2023.)

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.

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ishizuka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., (© 2022. The Author(s).)