{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T23:46:51Z","timestamp":1782604011526,"version":"3.54.5"},"reference-count":16,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2020,4,27]],"date-time":"2020-04-27T00:00:00Z","timestamp":1587945600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Gen and Family Med"],"published-print":{"date-parts":[[2020,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Introduction<\/jats:title><jats:p>This study aimed to clarify the accuracy of an in\u2010hospital mortality prediction score for patients with hypothermia. The score consists of five variables (age \u226570\u00a0years, mean arterial pressure &lt;90\u00a0mm\u00a0Hg, pH\u00a0&lt;\u00a07.35, creatinine &gt;1.5\u00a0mg\/dL, and confusion). In contrast to the previously reported population in southern Israel, a desert climate, we apply the score system to a Japanese humid subtropical climate.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The study included patients with a principal diagnosis of hypothermia who were admitted to our community hospital between January 2008 and January 2019. Using the medical records from initial visits, we retrospectively calculated in\u2010hospital mortality prediction scores along with sensitivity and specificity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We recruited 69 patients, 67 of which had analyzable data. Among them, the in\u2010hospital mortality rate was 25.4%. Hypothermia was defined as mild (32\u201035\u00b0C) in 34 cases (50.7%), moderate (28\u201032\u00b0C) in 23 cases (34.3%), and severe (&lt;28\u00b0C) in 10 cases (14.9%). The C\u2010statistics of the in\u2010hospital mortality prediction score was 0.703 (95% confidence interval, 0.55\u20100.84) for thirty\u2010day survival prediction. After adjustment of the cutoff point of each item with ROC analysis and selection of the variants, the C\u2010statistics of the in\u2010hospital mortality prediction score rose to 0.81 (95% confidence interval, 0.69\u20100.92).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The in\u2010hospital mortality prediction scores showed slightly less predictive value than those in the previous report. With some modification, however, the score system could still be applied efficiently in the humid Japanese subtropical climate. An appropriate management strategy could be established based on the predicted mortality risk.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jgf2.323","type":"journal-article","created":{"date-parts":[[2020,4,27]],"date-time":"2020-04-27T07:35:34Z","timestamp":1587972934000},"page":"134-139","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Hypothermia in a Japanese subtropical climate: Retrospective validation study of severity score and mortality prediction"],"prefix":"10.1002","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3034-7588","authenticated-orcid":false,"given":"Naoto","family":"Ishimaru","sequence":"first","affiliation":[{"name":"Department of General Internal Medicine Akashi Medical Center Akashi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saori","family":"Kinami","sequence":"additional","affiliation":[{"name":"Department of General Internal Medicine Akashi Medical Center Akashi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshio","family":"Shimokawa","sequence":"additional","affiliation":[{"name":"Clinical Study Support Centre Wakayama Medical University Wakayama Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroyuki","family":"Seto","sequence":"additional","affiliation":[{"name":"Department of General Internal Medicine Akashi Medical Center Akashi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yohei","family":"Kanzawa","sequence":"additional","affiliation":[{"name":"Department of General Internal Medicine Akashi Medical Center Akashi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2020,4,27]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.wem.2019.10.002"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1378\/chest.120.6.1998"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM199412293312607"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajem.2018.06.025"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajem.2007.10.016"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/1556-4029.12451"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40560-019-0384-2"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13049-019-0681-8"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/ams2.478"},{"key":"e_1_2_9_11_1","unstructured":"Japan Meteorological Agency.Monthly mean air temperature 1\u20133\u20104 Otemachi Chiyoda\u2010ku Tokyo 100\u20138122.Japan:Japan Meteorological Agency; Available from:https:\/\/www.data.jma.go.jp\/obd\/stats\/etrn\/view\/monthly_s3_en.php?block_no=47401&view=1. 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