前田 佳孝

Abstract Back ground In hemodialysis, hypotension occurs due to dehydration and solute removal. Conventional blood pressure monitoring during dialysis is intermittent and relies on staff experience and intuition to predict patient blood pressure trends based on the amount of water removed on the day and previous trends, which requires hemodialysis operations that do not lead to hypotension. Our research group has attempted to estimate blood pressure based on the spatial features of facial visible images, including information on facial color, and facial infrared images, including information on skin temperature. It is expected to realize early detection of blood pressure decrease during treatment if the blood pressure of dialysis patients can be estimated from their facial visible and infrared images measured continuously and remotely. In this study, we verified the applicability of deep learning algorithms in blood pressure estimation based on facial visible and infrared images of hemodialysis patients. Methods Measured facial visible and infrared images and mean blood pressure (MBP) of hemodialysis patients were applied to a convolutional neural network to construct an MBP estimation model based on the spatial features of the facial images. Results Average blood pressure could be estimated with an error of less than 20 mmHg based on the spatial features of the facial images, and the blood pressure estimation accuracy based on the spatial features of the facial infrared images was higher than that of the facial visible images. Conclusion We found the possibility of applying the deep learning algorithm to blood pressure estimation based on the spatial features of facial images. Trial registration This study is not subject to enrollment in a clinical trial due to the absence of both intervention and invasion. The Ethics Review Committee of Jichi Medical University has approved the same interpretation.

We assessed whether training on writing readable and accurate medical incident reports (IRs) improves the quality of fact description. In this training, 124 residents created fictional IRs. We provided tips, including using When, Where, Who, What, Why, How. We compared the fictional IRs with and without tips, and the trainees' and non-trainees’ IRs submitted in the first five months after training. Results indicated that the subject words in IRs were more clarified and the readability was improved. The fictional IRs using tips were more accurate, with increased descriptions of the patient's background, reporter's actions, team members' actions and conversations, safety check procedures, result of the error, and post-incident response. The reporter's actions, work procedures, and environment were more clarified in the trainees' IRs than in the non-trainees’ IRs. This training may help analysts comprehend the sequence of and underlying factors for reporter's actions based on IRs.

In this study, the relationship between gaze patterns, task duration, and years of experience, which are commonly used to define and evaluate expert surgeons in laparoscopic surgery, was identified. Ten surgeons with 1-28 years of experience and six inexperienced students were included. Subjects used forceps to repeat the task of suturing a suture pad. Each subject wore an eye-marking recorder, and gaze points were recorded and analyzed. No significant relationship between task duration and gaze pattern was observed. However, there was a significant relationship between a surgeon's years of experience and the percentage of time spent gazing at the forceps. Subjects with more years of experience operated without looking at the forceps and fixed their gaze on the operational target. Therefore, when analyzing laparoscopic gazing patterns, it may be more appropriate to define an "expert" based on the years of experience rather than task duration.

血液透析では，体外循環に伴う出血などの事故の防止や，患者の容態に応じた透析条件設定・調整を確実に行うため，装置の透析条件設定は適切か等の判断を適切・迅速に行うことが医療安全上重要となる．一方，同じ透析状態でも，それが不具合に相当するか否かの判断基準は様々な要因により異なり，臨床工学技士の経験度により判断が異なる場合も多い．また，判断基準の多くは各技士が経験により獲得した内在化された知識から構成されているため，新人教育上の課題も多い．本稿では透析中の判断に関して，新人技士が難度を高く感じる判断箇所に着目し，技士が困難さを感じている理由を抽出することで，新人技士の訓練項目を明確化した．