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  1. Article ; Online: Anterolateral Papillary Muscle Rupture Predicted by Post-Infarction Inflammatory Markers.

    Takafumi, Koyama / Yamamoto, Hiroyuki / Katayama, Ikuo

    The American journal of case reports

    2023  Volume 24, Page(s) e940406

    Abstract: BACKGROUND The incidence of papillary muscle rupture (PMR), a mechanical complication of acute myocardial infarction, has decreased in the reperfusion era; however, its fatality rate remains high. Timely recognition and prompt initiation of treatment for ...

    Abstract BACKGROUND The incidence of papillary muscle rupture (PMR), a mechanical complication of acute myocardial infarction, has decreased in the reperfusion era; however, its fatality rate remains high. Timely recognition and prompt initiation of treatment for PMR are important to avoid prolonged cardiogenic shock; however, the symptoms of PMR are nonspecific, and early diagnosis is often difficult. CASE REPORT A 72-year-old woman with nausea for 2 days presented with ST-segment elevation myocardial infarction with obstruction of the obtuse marginal branch and 75% stenosis of the first diagonal branch. Percutaneous coronary intervention was performed to revascularize the obtuse marginal lesion, which was over thrombolysis in myocardial infarction grade 2 flow. After percutaneous coronary intervention, the patient developed fever, an elevated C-reactive protein level, and an increased neutrophil-to-lymphocyte ratio (NLR). The patient showed no signs of infection but elevated inflammatory marker levels, with C-reactive protein rising to 39.32 mg/dL and NLR to 15. On postoperative day 4, the patient's clinical condition rapidly deteriorated, resulting in circulatory failure. Transthoracic echocardiography showed anterolateral PMR, and urgent surgical mitral valve replacement was performed. On day 32, the patient was discharged from the hospital, and at the 1-year follow-up, she remained in good health. CONCLUSIONS When there are multiple lesions, including the obtuse marginal and diagonal branches, anterolateral PMR should be suspected as the cause of cardiogenic shock. Performing point-of-care echocardiography and closely monitoring C-reactive protein levels and NLR can be helpful to detect PMR early.
    MeSH term(s) Female ; Humans ; Aged ; Shock, Cardiogenic ; C-Reactive Protein ; Papillary Muscles ; Myocardial Infarction ; Constriction, Pathologic
    Chemical Substances C-Reactive Protein (9007-41-4)
    Language English
    Publishing date 2023-09-09
    Publishing country United States
    Document type Case Reports ; Journal Article
    ZDB-ID 2517183-5
    ISSN 1941-5923 ; 1941-5923
    ISSN (online) 1941-5923
    ISSN 1941-5923
    DOI 10.12659/AJCR.940406
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Prevalence of psychological distress, quality of life, and satisfaction among patients and family members following comprehensive genomic profiling testing

    Makoto Nishino / Maiko Fujimori / Takafumi Koyama / Makoto Hirata / Noriko Tanabe / Toshio Shimizu / Noboru Yamamoto / Yosuke Uchitomi

    PLoS ONE, Vol 18, Iss 5, p e

    Protocol of the Quality of life for Cancer genomics and Advanced Therapeutics (Q-CAT) study.

    2023  Volume 0283968

    Abstract: Precision medicine is rapidly changing the diagnostic and treatment spectrum of oncology. In May 2019, comprehensive genomic profiling (CGP) (somatic and/or germline) was approved for reimbursement in Japan. While the promise of novel and targeted ... ...

    Abstract Precision medicine is rapidly changing the diagnostic and treatment spectrum of oncology. In May 2019, comprehensive genomic profiling (CGP) (somatic and/or germline) was approved for reimbursement in Japan. While the promise of novel and targeted therapies has elevated hopes for the benefits of CGP, the lack of relevant genomic findings and/or limited access to relevant therapies remain important themes in this field. These challenges may also negatively influence the psychology of both cancer patients and their family members. However, few studies have reported longitudinal data on quality of life (QOL) with CGP. Here, we report the protocol of a prospective study, Q-CAT (QOL for Cancer genomics and Advanced Therapeutics among patients and their family members), which aims to explore the mental burden on patients and families arising from the implementation of CGP testing by collecting real-world longitudinal data using outcomes obtained with an electronic patient report, known as ePRO. This study has been registered with the Japan Registry of Clinical Trials (jRCT1030200039).
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2023-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: The Accuracy of a Screening System for Carpal Tunnel Syndrome Using Hand Drawing

    Takuro Watanabe / Takafumi Koyama / Eriku Yamada / Akimoto Nimura / Koji Fujita / Yuta Sugiura

    Journal of Clinical Medicine, Vol 10, Iss 4437, p

    2021  Volume 4437

    Abstract: When carpal tunnel syndrome (CTS), an entrapment neuropathy, becomes severe, thumb motion is reduced, which affects manual dexterity, such as causing difficulties in writing; therefore, early detection of CTS by screening is desirable. To develop a ... ...

    Abstract When carpal tunnel syndrome (CTS), an entrapment neuropathy, becomes severe, thumb motion is reduced, which affects manual dexterity, such as causing difficulties in writing; therefore, early detection of CTS by screening is desirable. To develop a screening method for CTS, we developed a tablet app to measure the stylus trajectory and pressure of the stylus tip when drawing a spiral on a tablet screen using a stylus and, subsequently, used these data as training data to predict the classification of participants as non-CTS or CTS patients using a support vector machine. We recruited 33 patients with CTS and 31 healthy volunteers for this study. From our results, non-CTS and CTS were classified by our screening method with 82% sensitivity and 71% specificity. Our CTS screening method can facilitate the screening for potential patients with CTS and provide a quantitative assessment of CTS.
    Keywords carpal tunnel syndrome ; support vector machine ; machine learning ; tablet app ; screening ; manual dexterity ; Medicine ; R
    Language English
    Publishing date 2021-09-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Screening for degenerative cervical myelopathy with the 10-second grip-and-release test using a smartphone and machine learning

    Takuya Ibara / Ryota Matsui / Takafumi Koyama / Eriku Yamada / Akiko Yamamoto / Kazuya Tsukamoto / Hidetoshi Kaburagi / Akimoto Nimura / Toshitaka Yoshii / Atsushi Okawa / Hideo Saito / Yuta Sugiura / Koji Fujita

    Digital Health, Vol

    A pilot study

    2023  Volume 9

    Abstract: Objective Early detection and intervention are essential for the mitigation of degenerative cervical myelopathy (DCM). However, although several screening methods exist, they are difficult to understand for community-dwelling people, and the equipment ... ...

    Abstract Objective Early detection and intervention are essential for the mitigation of degenerative cervical myelopathy (DCM). However, although several screening methods exist, they are difficult to understand for community-dwelling people, and the equipment required to set up the test environment is expensive. This study investigated the viability of a DCM-screening method based on the 10-second grip-and-release test using a machine learning algorithm and a smartphone equipped with a camera to facilitate a simple screening system. Methods Twenty-two participants comprising a group of DCM patients and 17 comprising a control group participated in this study. A spine surgeon diagnosed the presence of DCM. Patients performing the 10-second grip-and-release test were filmed, and the videos were analyzed. The probability of the presence of DCM was estimated using a support vector machine algorithm, and sensitivity, specificity, and area under the curve (AUC) were calculated. Two assessments of the correlation between estimated scores were conducted. The first used a random forest regression model and the Japanese Orthopaedic Association scores for cervical myelopathy (C-JOA). The second assessment used a different model, random forest regression, and the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire. Results The final classification model had a sensitivity of 90.9%, specificity of 88.2%, and AUC of 0.93. The correlations between each estimated score and the C-JOA and DASH scores were 0.79 and 0.67, respectively. Conclusions The proposed model could be a helpful screening tool for DCM as it showed excellent performance and high usability for community-dwelling people and non-spine surgeons.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7
    Subject code 630
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher SAGE Publishing
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: A screening method for cervical myelopathy using machine learning to analyze a drawing behavior

    Eriku Yamada / Koji Fujita / Takuro Watanabe / Takafumi Koyama / Takuya Ibara / Akiko Yamamoto / Kazuya Tsukamoto / Hidetoshi Kaburagi / Akimoto Nimura / Toshitaka Yoshii / Yuta Sugiura / Atsushi Okawa

    Scientific Reports, Vol 13, Iss 1, Pp 1-

    2023  Volume 8

    Abstract: Abstract Early detection of cervical myelopathy (CM) is important for a favorable outcome, as its prognosis is poor when left untreated. We developed a screening method for CM using machine learning-based analysis of the drawing behavior of 38 patients ... ...

    Abstract Abstract Early detection of cervical myelopathy (CM) is important for a favorable outcome, as its prognosis is poor when left untreated. We developed a screening method for CM using machine learning-based analysis of the drawing behavior of 38 patients with CM and 66 healthy volunteers. Using a stylus pen, the participants traced three different shapes displayed on a tablet device. During the tasks, writing behaviors, such as the coordinates, velocity, and pressure of the stylus tip, along with the drawing time, were recorded. From these data, features related to the drawing pressure, and time to trace each shape and combination of shapes were used as training data for the support vector machine, a machine learning algorithm. To evaluate the accuracy, a receiver operating characteristic curve was generated, and the area under the curve (AUC) was calculated. Models with triangular waveforms tended to be the most accurate. The best triangular wave model identified patients with and without CM with 76% sensitivity and 76% specificity, yielding an AUC of 0.80. Our model was able to classify CM with high accuracy and could be applied to the development of disease screening systems useful outside the hospital setting.
    Keywords Medicine ; R ; Science ; Q
    Subject code 006
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Introducing AI to the molecular tumor board

    Ryuji Hamamoto / Takafumi Koyama / Nobuji Kouno / Tomohiro Yasuda / Shuntaro Yui / Kazuki Sudo / Makoto Hirata / Kuniko Sunami / Takashi Kubo / Ken Takasawa / Satoshi Takahashi / Hidenori Machino / Kazuma Kobayashi / Ken Asada / Masaaki Komatsu / Syuzo Kaneko / Yasushi Yatabe / Noboru Yamamoto

    Experimental Hematology & Oncology, Vol 11, Iss 1, Pp 1-

    one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information

    2022  Volume 23

    Abstract: Abstract Since U.S. President Barack Obama announced the Precision Medicine Initiative in his New Year’s State of the Union address in 2015, the establishment of a precision medicine system has been emphasized worldwide, particularly in the field of ... ...

    Abstract Abstract Since U.S. President Barack Obama announced the Precision Medicine Initiative in his New Year’s State of the Union address in 2015, the establishment of a precision medicine system has been emphasized worldwide, particularly in the field of oncology. With the advent of next-generation sequencers specifically, genome analysis technology has made remarkable progress, and there are active efforts to apply genome information to diagnosis and treatment. Generally, in the process of feeding back the results of next-generation sequencing analysis to patients, a molecular tumor board (MTB), consisting of experts in clinical oncology, genetic medicine, etc., is established to discuss the results. On the other hand, an MTB currently involves a large amount of work, with humans searching through vast databases and literature, selecting the best drug candidates, and manually confirming the status of available clinical trials. In addition, as personalized medicine advances, the burden on MTB members is expected to increase in the future. Under these circumstances, introducing cutting-edge artificial intelligence (AI) technology and information and communication technology to MTBs while reducing the burden on MTB members and building a platform that enables more accurate and personalized medical care would be of great benefit to patients. In this review, we introduced the latest status of elemental technologies that have potential for AI utilization in MTB, and discussed issues that may arise in the future as we progress with AI implementation.
    Keywords Molecular tumor board ; Precision medicine ; Artificial intelligence ; Next-generation sequencing ; Natural language processing ; Diseases of the blood and blood-forming organs ; RC633-647.5 ; Neoplasms. Tumors. Oncology. Including cancer and carcinogens ; RC254-282
    Subject code 610
    Language English
    Publishing date 2022-10-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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