{"created":"2023-05-15T12:29:39.257215+00:00","id":2131,"links":{},"metadata":{"_buckets":{"deposit":"61b9def2-8ee4-4606-ae80-9a4cebc0a657"},"_deposit":{"created_by":4,"id":"2131","owners":[4],"pid":{"revision_id":0,"type":"depid","value":"2131"},"status":"published"},"_oai":{"id":"oai:luke.repo.nii.ac.jp:00002131","sets":["1","1:30","1:30:17","1:30:17:217"]},"author_link":["4966","6620"],"item_10006_alternative_title_1":{"attribute_name":"その他（別言語等）のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"重症外傷患者の予後予測モデル: 日本の外傷レジストリを用いた研究"}]},"item_10006_date_granted_11":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2020-03-10"}]},"item_10006_degree_grantor_9":{"attribute_name":"学位授与機関","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_name":"聖路加国際大学"}]}]},"item_10006_degree_name_8":{"attribute_name":"学位名","attribute_value_mlt":[{"subitem_degreename":"修士(公衆衛生学)"}]},"item_10006_description_10":{"attribute_name":"学位授与年度","attribute_value_mlt":[{"subitem_description":"2019","subitem_description_type":"Other"}]},"item_10006_description_7":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Objective: We aimed to create a new prognostic prediction score model for severe trauma patients: by using the Japanese nationwide trauma registry, which is focused on patient transportation time,: the treatment provided by emergency medical services, and the variations in the vital signs of the: patients before and after arrival at the hospital.: Methods: A multicenter retrospective cohort study was conducted in Japan. We collected data from: the Japan Trauma Data Bank (JTDB) . We included the words “adult” and “shock” (systolic blood: pressure < 90 mmHg) in our search, and then considered age, sex, treatment before hospital arrival,: variations in the vital signs and transportation time. The outcome was the status at hospital discharge: (dead/alive). A stepwise logistic regression model was constructed for the model development and: the bootstrapping method was used for internal validation.: Results: A total of 4,881 patients were included, and mortality was 10.5%. According to: multivariate analysis, predictors for death included age (4 categories), type of injury (2 categories),: treatment before hospital arrival (2 categories), variation in systolic blood pressure (6 categories),: variation in respiratory rate (5 categories) and transportation time (2 categories). The AUC (area: under the receiver operating characteristic curve) was 0.726 (95% CI, 0.702 – 0.749). Our prediction: model was validated internally by a bootstrapping method.: Conclusion: We suggest a new prognostic prediction model for severe trauma patients that consists: of six predictors and is focused on variations in vital signs. This score can be calculated just after the: patient’s arrival at the hospital.","subitem_description_type":"Abstract"}]},"item_10006_dissertation_number_12":{"attribute_name":"学位授与番号","attribute_value_mlt":[{"subitem_dissertationnumber":"32633公修専第046"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山田, 浩平"},{"creatorName":"ヤマダ, コウヘイ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{"nameIdentifier":"4966","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Yamada, Kohei","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"6620","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2021-09-15"}],"displaytype":"detail","filename":"MP[046]_abst.pdf","filesize":[{"value":"93.1 kB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"論文要旨","url":"https://luke.repo.nii.ac.jp/record/2131/files/MP[046]_abst.pdf"},"version_id":"acf204a5-f409-4415-ab82-2a4a4ed0422c"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"trauma","subitem_subject_scheme":"Other"},{"subitem_subject":"prediction model","subitem_subject_scheme":"Other"},{"subitem_subject":"observational study","subitem_subject_scheme":"Other"},{"subitem_subject":"registry","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"thesis","resourceuri":"http://purl.org/coar/resource_type/c_46ec"}]},"item_title":"Prognostic Prediction Model of Severe Trauma Patients: using Japanese Nationwide Trauma Registry","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Prognostic Prediction Model of Severe Trauma Patients: using Japanese Nationwide Trauma Registry"}]},"item_type_id":"10006","owner":"4","path":["1","17","30","217"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-06-05"},"publish_date":"2020-06-05","publish_status":"0","recid":"2131","relation_version_is_last":true,"title":["Prognostic Prediction Model of Severe Trauma Patients: using Japanese Nationwide Trauma Registry"],"weko_creator_id":"4","weko_shared_id":-1},"updated":"2025-07-03T07:37:37.804348+00:00"}