生坂 政臣

BACKGROUND: Discrepancies existed between the medical knowledge sections of the Model Core Curriculum for Medical Education (MCC) and the Guidelines for the National Examination for Medical Practitioners (GNEMP) in Japan. These discrepancies have been one of the underlying factors hindering the development of learner-centered medical education in the country. The project team responsible for the 'Problem-Solving' section of the MCC aimed to address discrepancies between the disease lists in the MCC and the GNEMP. METHOD: We refined the disease list for the 2022 revision of the MCC using a three-phase process: (a) procedure development, (b) selection, and (c) adjudication. First, we developed a scoring system for sifting and prioritizing diseases in the GNEMP, selecting those that met our scoring criteria. An expert adjudication panel then finalized the list of diseases through discussion. RESULTS: Among the 1,456 diseases identified in the GNEMP, 781 met the selection criteria. The adjudication panel selected 56 of these diseases to be newly added to the 2022 MCC, resulting in a total of 691 diseases. CONCLUSIONS: The list of diseases defined as required medical knowledge in the MCC was finalized through dialogue among medical education stakeholders, effectively minimizing discrepancies between the MCC and GNEMP.

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.

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.

UNLABELLED: 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.

Abstract Background Illness scripts, which are structured summaries of clinical knowledge concerning diseases, are crucial in disease prediction and problem representation during clinical reasoning. Clinicians iteratively enhance their illness scripts through their clinical practice. Because illness scripts are unique to each physician, no systematic summary of specific examples of illness scripts has been reported. Objective 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 enhance the comprehension of disease concepts and increase diagnostic accuracy. This study investigated whether generative AI possesses the capability to generate illness scripts. Methods We used ChatGPT, a generative AI, to create illness scripts for 184 diseases based on the diseases and conditions integral to the National Model Core Curriculum for undergraduate medical education (2022 revised edition) and primary care specialist training in Japan. Three physicians applied a three-tier grading scale: “A” if the content of each disease’s illness script proves sufficient for training medical students, “B” if it is partially lacking but acceptable, and “C” if it is deficient in multiple respects. Moreover, any identified deficiencies in the illness scripts were discussed during the evaluation process. Results Leveraging ChatGPT, 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 by ChatGPT using prompts appropriate for medical students. The technology-driven illness script is a valuable tool for introducing medical students to disease conceptualization.

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.

Acute visual loss in an immunocompromised patient may be caused by acute invasive fungal sinusitis (AIFS), even if symptoms include only mild headache and computed tomography (CT) shows only mild sinusitis, especially of the Onodi cell. Herein, we report a case of a 71-year-old man with a medical history of dermatomyositis and type 2 diabetes mellitus who presented with a stepwise progression of acute bilateral visual loss, mild headache, and altered consciousness. Initially, as the plain cranial CT showed only mild fluid retention in the posterior ethmoid sinus without bone destruction, the sinusitis was considered unrelated to the visual loss. Afterward, however, contrast-enhanced cranial magnetic resonance imaging (MRI) showed mucosal thickening, fluid retention in the posterior ethmoid sinus, and spread of the contrast medium over the dura around the right posterior ethmoid sinus and bilateral optic nerve tracts. Aspergillus fumigatus was identified from endoscopic drainage of the sinus. The patient was diagnosed with AIFS and treated with amphotericin B 350 mg/day. The altered sensorium and headache rapidly improved, and his left visual acuity improved to counting fingers. Although AIFS is rare, it can cause severe sequela or death due to vascular or direct intracranial invasion. Therefore, immediate drainage of the sinus and intravenous antifungal therapy are essential for AIFS. Our findings will help physicians make accurate and rapid diagnoses of AIFS in future cases.

BACKGROUND<p>Medical history contributes approximately 80% to the 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.</p> OBJECTIVE<p>This study explored the contribution of patient history to AI-assisted medical diagnoses.</p> METHODS<p>Using 30 cases from clinical vignettes from the British Medical Journal, we evaluated the accuracy of diagnoses generated by the AI model ChatGPT. We compared the diagnoses made by ChatGPT based solely on the medical history with the correct diagnoses. We also compared the diagnoses made by ChatGPT after incorporating additional physical examination findings and laboratory data alongside the history with correct diagnoses.</p> RESULTS<p>ChatGPT accurately diagnosed 76.6% of the cases with the medical history alone, consistent with previous research targeting physicians. We also found that this rate was 93.3% when additional information was included.</p> CONCLUSIONS<p>Although adding additional information improves diagnostic accuracy, patient history remains a significant factor in AI-assisted medical diagnosis. Thus, when utilizing 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.</p>

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.

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.

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).

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).

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.

UNSTRUCTURED<p>ChatGPT (Open AI, San Francisco, California, USA) has gained considerable attention because of its natural and intuitive responses. One limitation of OpenAI is its failure to perform reinforcement learning based on reliable information, thereby providing inaccurate or meaningless answers. Fortunately, on March 2023 update introduced GPT-4, which, according to internal evaluations, is expected to increase the likelihood of producing factual responses by 40% compared with its predecessor, GPT-3.5. We verified the accuracy of ChatGPT based on GPT-4 (ChatGPT4) and based on GPT-3.5 (ChatGPT3.5) by solving the Japanese National Medical Examination. We excluded questions containing figures and tables unsupported by ChatGPT. Of the 400 questions, 292 were analyzed. The correct response rate for ChatGPT4 was 81.5%, which was significantly higher than 42.8%, the rate for ChatGPT3.5. Moreover, ChatGPT4 surpassed the passing standard (&gt;72%) for the Japanese National Medical Examination, indicating its potential as a diagnostic and therapeutic decision aid for physicians. We anticipate that future updates of ChatGPT will further enhance its accuracy, making it an invaluable resource in the field of medicine.</p>

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.

UNLABELLED: 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.

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.

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.

Group B Streptococcus (GBS) causes septic arthritis in healthy adults, and a significant number of GBS septic arthritis cases involve multiple joints. Nevertheless, septic arthritis is commonly monoarticular. Here, we report a case of a 45-year-old man who complained of subacute fever and right shoulder and right buttock pain for three weeks despite undergoing garenoxacin treatment for one week. Although synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome could be a possible differential diagnosis for this patient, the fever and subacute clinical course could not be explained. Blood cultures revealed the presence of GBS; therefore, he was diagnosed with septic arthritis. After antibiotic treatment for six weeks, his symptoms resolved.

The clinical manifestations of Takayasu arteritis (TA) greatly vary, and this ultimately leads to a delay in diagnosis. We describe a case of TA presenting with two coexisting rare symptoms of linear neck pain and prolonged cough. A 28-year-old Japanese female with a six-month history of ulcerative colitis presented with recurrent left neck pain, cough, and fever. The neck pain and fever started five months ago. Her symptoms briefly improved with nonsteroidal anti-inflammatory drug therapy, but eventually recurred one month prior to her latest presentation to the hospital, which was accompanied by a dry cough. Physical examination revealed a blood pressure discrepancy, with systolic blood pressure being >10 mmHg lower in her left arm than in her right arm, a bilateral carotid bruit, a weak left radial pulse and radio-radial delay without coolness in the upper extremities, and linear pulsatile tenderness in her left neck along the common carotid artery. No supraclavicular or infraclavicular bruit was noted. The erythrocyte sedimentation rate was elevated at 66 mm/hour. After obtaining the images from a contrast-enhanced computed tomography, she was diagnosed with TA. All her symptoms improved with prednisone therapy. Notably, neck pain and cough are both late-stage symptoms of TA, which are seen in 9.7% and 1.5% of patients, respectively. Although her unspecific symptoms could have been easily misdiagnosed, the recurring exacerbation of symptoms warranted careful attention to a focused physical examination. In conclusion, neck pain and cough are both uncommon presentations of TA, which may lead to physicians underdiagnosing it. It is important to recognize neck pain and cough as presenting complaints in patients with TA.

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.

Objective: To determine if inter-disease distances between word embedding vectors using the picot-and-cluster strategy (PCS) are a valid quantitative representation of similar disease groups in a limited domain.Materials and Methods: Abstracts were extracted from the Ichushi-Web database and subjected to morphological analysis and training using the Word2Vec. From this, 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. The CCC was most significant at 0.8690 (metric and method: euclidean and centroid), while 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).Discussion: The metric and method that maximized the internal validity measure were different 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.Conclusion: 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.

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.

BACKGROUND: Interprofessional collaborative practice competency (ICPC) is key to providing safe, high-quality, accessible, patient-centred care. Effective delirium management, particularly, requires a multi-component intervention, including the use of interprofessional teams at care point. This research aims to investigate the effectiveness of the flipped classroom approach for improving ICPC in simulation-based delirium case management. METHOD: An embedded mixed-methods study was designed to investigate the effects of the flipped classroom approach on health professionals' performance in delirium management. The study population comprised nine health professionals (three physicians, nurses, and pharmacists each). They used pre-class study materials about delirium management via a digital learning platform before a simulation case training session. A readiness assurance process test was conducted on key concepts, covered in the pre-class study material. Participants were randomly assigned to three teams, each of which included health professionals. Each team participated in a simulation case scenario. For the quantitative outcome measures, the Chiba Interprofessional Competency Scale (CICS29), a validated scale for measuring competencies of interprofessional practice, was used before, after, and three months after the educational intervention. The qualitative component consisted of a post-training questionnaire and semi-structured focused group interviews about the impact of the flipped classroom approach. RESULT: The CICS29 measured after the intervention and three months after was noted to be significantly higher than before the intervention. Three semi-structured focused group interviews were conducted (n=9), which, upon analysis revealed that the flipped classroom approach effected on four stages of Bloom's taxonomy level. A total of nine categories and 17 subcategories were identified corresponding to four levels of the revised Bloom's taxonomy: remember (1), understand (12), apply (23), and analyse (3). CONCLUSION: The simulation-based skill training using flipped classroom approach can be an effective method for improving ICPC for health professionals. In this approach, an elevated level of cognitive activity is practiced in the Bloom's taxonomy, and the participants worked on an application-based case simulation that promoted higher level learning and engagement in interprofessional collaborative practice. This approach also established a basic common language of delirium assessment and management, thus facilitating communication among health professionals and improving ICPC.

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.

In malignant mesotheliomas, cases involving the peritoneum as the primary site are rare, accounting for approximately 10% of all mesothelioma cases. We report a case of medical-type peritoneal mesothelioma leading to death 2 months after the onset of fever of unknown origin, along with a review of the literature. A 76-year-old man presented with a fever of unknown origin over 4 weeks. Thoracoabdominal computed tomography (CT) scan showed increased mesenteric adipose tissue density. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) scan showed diffuse hyperaccumulation in the mesentery and hyperaccumulation in the intraperitoneal and parasternal lymph nodes. A thoracoscopic biopsy of the parasternal lymph nodes revealed metastatic peritoneal mesothelioma. The treatment plan was discussed with him and his family, and the best supportive care was provided. 2 months later, he died from multiple organ failure. Underlying malignant tumors cause 38% of mesenteric panniculitis cases. Symptoms accompanied by lymphadenopathy within the area of mesenteric panniculitis are highly suggestive of malignancy. Peritoneal mesothelioma can be classified as (1) classical, which is accompanied by abdominal pain, ascites, and abdominal masses; (2) surgical, which is accompanied by hernia incarceration and intestinal occlusion; and (3) medical, wherein systemic symptoms, such as fever and weight loss, are primarily observed. The medical-type peritoneal mesothelioma, wherein systemic symptoms are primarily observed, has a poorer prognosis than the other types. FDG-PET/CT is an effective diagnostic modality for peritoneal mesothelioma and typically shows diffuse hyperaccumulation along the peritoneal surface.

Background: The supply of primary care physicians is associated with better health outcomes and a lower total cost of health services. However, the effect of the presence or absence of primary care physicians on health-related quality of life (QOL) is unknown. We comparatively investigated the health-related QOL of ordinary citizens according to the presence or absence of a primary care physician. Methods: We conducted an observational cross-sectional study using a propensity score analysis. A questionnaire on health-related QOL (SF-36v2, age, gender, presence or absence of a primary care physician, and chronic disease status) was mailed to 2200 individuals identified through stratified random sampling. We used propensity scores to compensate for covariates and analyzed three component SF-36 summary scores and subscale scores of the “primary care physician” and “no primary care physician” groups. Results: Valid responses were received from 1095 individuals (49.8%). The “primary care physician group” comprised 653 individuals (59.6%). The physical health component scores of the “primary care physician group” were significantly lower than those of the “no primary care physician group,” and the “mental health component” scores were significantly higher (p = 0.032, p = 0.009). For the subscales, scores for “vitality” and “mental health” were significantly higher in the “primary care physician group” (p = 0.014, p = 0.018). Conclusions: Patients who had a primary care physician with whom they could comfortably consult at any time had a high mental health component score, and low physical health component score in the health-related QOL.

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.

Purpose: 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.

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.

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.

Although patients with scrub typhus develop a maculopapular rash all over the body, patients with COVID-19 may also show a similar rash. At the first visit, we did not fully inspect his trunk and extremities under his clothes. Although scrub typhus and COVID-19 have some similar symptoms, an eschar is a characteristic symptom of the former, and careful inspection is important to distinguish between the diseases.