Publications by authors named "M Makino"

In the field of cancer care, it is still difficult to say that advance care planning(ACP)has been fully integrated, and the perceptions of ACP vary depending on the individual's role. Since oncologists have a deeper understanding of the patient's condition and prognosis than the patients themselves, they are often the first to recognize the future need for ACP. It is important to gather and incorporate patients' preferences and relevant information regarding ACP early in the course of daily cancer treatment.

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Owing to the extensive use of antibiotics in hospitals, animal husbandry, and various human activities, antibiotic contamination is becoming an increasing global concern, including in Bangladesh. In Bangladesh, the Buriganga River is heavily polluted with multiple antibiotics, which can lead to antibiotic resistance in bacteria. In this study, we performed the first investigation of seasonal variations in the occurrence and spatial distribution of 29 antibiotics in the Buriganga River, Bangladesh, from wet season (August 2019) and dry season (February 2020).

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  • Hypertension is a known risk factor for atrial fibrillation (AF) and strokes, but there is limited research on AF screening in hypertensive patients and its link to blood pressure levels.
  • A study involving over 4,000 hypertensive patients aged 60 and older in Japan measured their electrocardiograms (ECG) and blood pressure (BP) at home for three months.
  • The study found that 5.8% of participants had undiagnosed AF, with no significant differences in AF detection rates based on different baseline BP categories or the use of antihypertensive medication.
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  • Atrial fibrillation (AF) is categorized by duration into paroxysmal, persistent, and long-standing persistent types, with longer durations increasing the risk of recurrence during catheter ablation treatment.
  • The study aims to enhance the diagnosis accuracy of AF duration through a predictive model, utilizing data from 272 patients to train a machine learning algorithm.
  • Results showed the model achieved 81.8% accuracy in predicting AF duration, significantly improving cardiologists' diagnostic performance from 63.9% to 71.6% after using the model's insights.
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  • The study looked at how javelin throwers perform short run-up throws compared to full run-up throws, to see if there are differences in their throwing techniques.
  • Twelve male athletes participated and their movements were recorded using special cameras to analyze how they throw.
  • The results showed that the way their bodies moved, like their knee, trunk, and shoulder angles, was different between the two types of throws.
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