Background: Primary headaches are widespread and costly public health problems. However, there are insufficient medical resources for their treatment in Japan due to two reasons. First, the numbers of headache specialists and clinics remain insufficient. Second, neurologists and neurosurgeons mainly treat headaches in Japan. However, they mainly work as general stroke neurologists, so they cannot focus on primary headache treatment. To solve these problems, we preliminarily developed a deep learning (DL)-based automated diagnosis model from patients’ Japanese unstructured sentences in the medical questionnaire using a DL framework. We hypothesized that the model would reduce the time and burden on both doctors and patients and improve their quality of life. Methods: We retrospectively investigated our primary headache database and developed a diagnosis model using the DL framework (Prediction One, Sony Network Communications Inc., Japan). We used age, sex, date, and embedding layer made by the medical questionnaire’s natural language processing (NLP). Results: Eight hundred and forty-eight primary headache patients (495 women and 353 men) are included. The median (interquartile range) age was 59 (40–74). Migraine accounted for 46%, tension-type headache for 47%, trigeminal autonomic cephalalgias for 5%, and other primary headache disorders for 2%. The accuracy, mean precision, mean recall, and mean F value of the developed diagnosis model were 0.7759, 0.8537, 0.6086, and 0.6353, which were satisfactory. Conclusion: The DL-based diagnosis model for primary headaches using the raw medical questionnaire’s Japanese NLP would be useful in performing efficient medical practice after ruling out the secondary headaches.
Background: Chronologically meteorological and calendar factors were risks of stroke occurrence. However, the prediction of stroke occurrences is difficult depending on only meteorological and calendar factors. We tried to make prediction models for stroke occurrences using deep learning (DL) software, Prediction One (Sony Network Communications Inc., Tokyo, Japan), with those variables. Methods: We retrospectively investigated the daily stroke occurrences between 2017 and 2019. We used Prediction One software to make the prediction models for daily stroke occurrences (present or absent) using 221 chronologically meteorological and calendar factors. We made a prediction models from the 3-year dataset and evaluated their accuracies using the internal cross-validation. Areas under the curves (AUCs) of receiver operating characteristic curves were used as accuracies. Results: The 371 cerebral infarction (CI), 184 intracerebral hemorrhage (ICH), and 53 subarachnoid hemorrhage patients were included in the study. The AUCs of the several DL-based prediction models for all stroke occurrences were 0.532–0.757. Those for CI were 0.600–0.782. Those for ICH were 0.714–0.988. Conclusion: Our preliminary results suggested a probability of the DL-based prediction models for stroke occurrence only by meteorological and calendar factors. In the future, by synchronizing a variety of medical information among the electronic medical records and personal smartphones as well as integrating the physical activities or meteorological conditions in real time, the prediction of stroke occurrence could be performed with high accuracy, to save medical resources, to have patients care for themselves, and to perform efficient medicine.
It is important to assess the cerebral arteries near the clip after cerebral aneurysm clipping. Contrast-enhanced computed tomography angiography has side effects of contrast medium and radiation exposure. Time-of-flight magnetic resonance angiography (TOF-MRA) is a fast and non-invasive method, but clip-induced artifact limits the assessment around the clip. Recently, 3 tesla MRA with ultrashort echo time called SILENT MRA (GE Healthcare Life Sciences, UK) has been reported to have the potential to overcome these disadvantages. We herein present consecutive 19 cerebral aneurysm patients treated by clipping and evaluated using SILENT MRA. The 19 patients (15 women and 4 men) underwent TOF-MRA and SILENT MRA during the same scan session. Two neurosurgeons independently assessed the visibility of the mother vessel at the clipping site in TOF-MRA and SILENT MRA. We also investigated the factors related to visibility in SILENT MRA. All patients' mother vessels were not described in TOF-MRA, and that of 16 patients (84%) were described in SILENT MRA. Overall agreement was 100% in the two neurosurgeons, and the fixed marginal kappa = 1.00 (95% CI: 0.36-1.00). Univariate analysis revealed that larger aneurysm dome and long clip blade length contributed to the visibility of the mother vessel in SILENT MRA. (p = 0.023, 0.007, each). In conclusion, SILENT MRA can be applied for the assessment of the arteries and aneurysm neck remnants near the clip. Using clips with long blade and ligation with its tip would be related to the visibility of the mother vessels in SILENT MRA.
Purpose With the aging population in Japan, the prediction of ambulance transports is needed to save the limited medical resources. Some meteorological factors were risks of ambulance transports, but it is difficult to predict in a classically statistical way because Japan has 4 seasons. We tried to make prediction models for ambulance transports using the deep learning (DL) framework, Prediction One (Sony Network Communications Inc., Tokyo, Japan), with the meteorological and calendarial variables. Materials and Methods We retrospectively investigated the daily ambulance transports and meteorological data between 2017 and 2019. First, to confirm their association, we performed classically statistical analysis. Second, to test the DL framework’s utility for ambulance transports prediction, we made 3 prediction models for daily ambulance transports (total daily ambulance transports more than 5 or not, cardiopulmonary arrest (CPA), and trauma) using meteorological and calendarial factors and evaluated their accuracies by internal cross-validation. Results During the 1095 days of 3 years, the total ambulance transports were 5948, including 240 CPAs and 337 traumas. Cardiogenic CPA accounted for 72.3%, according to the Utstein classification. The relation between ambulance transports and meteorological parameters by polynomial curves were statistically obtained, but their r 2 s were small. On the other hand, all DL-based prediction models obtained satisfactory accuracies in the internal cross-validation. The areas under the curves obtained from each model were all over 0.947. Conclusion We could statistically make polynomial curves between the meteorological variables and the number of ambulance transport. We also preliminarily made DL-based prediction models. The DL-based prediction for daily ambulance transports would be used in the future, leading to solving the lack of medical resources in Japan.
Kampo (Japanese herbal) medicine for primary headaches as an acute treatment has been empirically prescribed, but the evidence is insufficient. Therefore, we retrospectively investigated kampo medicine’s efficacy for primary headaches at 1 week and discussed how kampo medicine works for headaches, referring to previous articles. We prescribed, as needed, kakkonto (TJ-1) for 223 tension-type headaches, goshuyuto (TJ-31) for 93 migraines with or without aura and those with the menopausal disorder, goreisan (TJ-17) for 71 migraines with edema, dehydration (Sui-doku), or associated with weather conditions, and non-steroidal anti-inflammatory drugs (NSAIDs) for 162 primary headaches between 2015 and 2019 in Kesennuma City Hospital. As a total, 92.0% of the patients’ subjective symptoms improved after 1 week. The ratio of improvement was not significantly different between each kampo medicine and NSAIDs. The follow-up period is short as 1 week, and it is difficult to judge whether the improvement is due to medication, the placebo effect, or spontaneous remission. However, our results suggested that kampo medicine could be an alternative medication as an acute treatment for primary headaches, and our strategy would be applicable to the clinical practice of primary headaches. (187/250 words)
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