{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T23:48:25Z","timestamp":1782172105848,"version":"3.54.5"},"reference-count":24,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100004587","name":"Instituto de Salud Carlos III","doi-asserted-by":"publisher","award":["PMPTA23\/00033"],"award-info":[{"award-number":["PMPTA23\/00033"]}],"id":[{"id":"10.13039\/501100004587","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Environ\ufffdHealth\ufffdInsights"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:p>\n                    Environmental exposures are recognized as determinants of health, particularly in vulnerable populations such as hemodialysis patients, whose impaired kidney function may heighten susceptibility. This study assesses the association between meteorological and air-pollution factors and the risk of hospital admission and mortality in end-stage kidney disease patients, considering both acute peaks and sustained exposure through weekly and monthly averages. A retrospective cohort of 336 hemodialysis patients treated between 2016 and 2024 at Hospital Universitario Pr\u00edncipe de Asturias (Madrid, Spain) was analyzed, including 563 admissions and 90 deaths. Time-to-event analyses were conducted separately for mortality and admissions. Cox proportional hazards and parametric survival models (Weibull, log-normal, log-logistic) were applied for mortality, while recurrent-event models (Andersen\u2013Gill, Prentice\u2013Williams\u2013Peterson, frailty) used for admissions. Sulfur dioxide (SO\n                    <jats:sub>2<\/jats:sub>\n                    ) was consistently associated with increased risk in both acute and cumulative exposure models for mortality and admissions. Nitrogen dioxide (NO\n                    <jats:sub>2<\/jats:sub>\n                    ) predicted mortality only in long-term analyses, suggesting a cumulative effect. Solar radiation was linked to accelerated mortality in non-linear models, whereas atmospheric pressure appeared protective for admissions. These findings highlight the influence of environmental exposures, particularly SO\n                    <jats:sub>2<\/jats:sub>\n                    , on adverse outcomes in hemodialysis patients and support incorporating environmental indicators into clinical risk prediction and public health strategies.\n                  <\/jats:p>","DOI":"10.1177\/11786302261451620","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T11:23:52Z","timestamp":1781781832000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Influence of Weather and Air Quality on Clinical Outcomes in End-Stage Kidney Disease: A Retrospective Hospital-Based Study"],"prefix":"10.1177","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2323-192X","authenticated-orcid":false,"given":"Mar\u00eda","family":"Santamera-Lastras","sequence":"first","affiliation":[{"name":"Dept. of Medicine and Medical Specialties, Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Health Computing and Intelligent Systems Research Group (HCIS), Universidad de Alcal\u00e1, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6517-6110","authenticated-orcid":false,"given":"Melisa","family":"Granda","sequence":"additional","affiliation":[{"name":"Dept. of Medicine and Medical Specialties, Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Health Computing and Intelligent Systems Research Group (HCIS), Universidad de Alcal\u00e1, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1365-9280","authenticated-orcid":false,"given":"Alberto","family":"Garc\u00e9s-Jim\u00e9nez","sequence":"additional","affiliation":[{"name":"Health Computing and Intelligent Systems Research Group (HCIS), Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Dept. of Computer Science, Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Ram\u00f3n y Cajal Institute for Health Research (IRYCIS), Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8069-0288","authenticated-orcid":false,"given":"Francisco Javier","family":"Bueno-Guill\u00e9n","sequence":"additional","affiliation":[{"name":"Health Computing and Intelligent Systems Research Group (HCIS), Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Dept. of Computer Science, Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Ram\u00f3n y Cajal Institute for Health Research (IRYCIS), Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4544-7581","authenticated-orcid":false,"given":"Patricia","family":"Mart\u00ednez-Miguel","sequence":"additional","affiliation":[{"name":"Nephrology Department and Research Foundation, Hospital Universitario Pr\u00edncipe de Asturias, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9125-9311","authenticated-orcid":false,"given":"Diego Mar\u00eda","family":"Rodr\u00edguez-Puyol","sequence":"additional","affiliation":[{"name":"Dept. of Medicine and Medical Specialties, Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Ram\u00f3n y Cajal Institute for Health Research (IRYCIS), Madrid, Spain"},{"name":"Nephrology Department and Research Foundation, Hospital Universitario Pr\u00edncipe de Asturias, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6897-8262","authenticated-orcid":false,"given":"Jos\u00e9 Manuel","family":"G\u00f3mez-Pulido","sequence":"additional","affiliation":[{"name":"Health Computing and Intelligent Systems Research Group (HCIS), Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Dept. of Computer Science, Universidad de Alcal\u00e1, Madrid, Spain"},{"name":"Ram\u00f3n y Cajal Institute for Health Research (IRYCIS), Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,6,18]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.18203\/2394-6040.ijcmph20204384"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/S2214-109X(23)00570-3"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(14)61601-9"},{"key":"e_1_3_3_5_2","unstructured":"United States Renal Data System. Epidemiology of Kidney Disease in the United States. Published online 2023. https:\/\/adr.usrds.org"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1681\/ASN.2012040392"},{"key":"e_1_3_3_7_2","unstructured":"World Meteorological Organization. World Meteorological Organization Home. WMO. Accessed May 21 2025. https:\/\/wmo.int"},{"key":"e_1_3_3_8_2","unstructured":"World Health Organization. World Health Organization Home. WHO. Accessed May 21 2025. https:\/\/www.who.int"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12940-022-00836-0"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2022.04.008"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.34067\/KID.0003822022"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2022.158215"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2020-041177"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17020546"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.23876\/j.krcp.21.228"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2024.1390999"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2019.8904"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ekir.2024.07.015"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2024.04.010"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.2215\/CJN.0000000000000174"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1681\/ASN.2021111520"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2021.152481"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-38522-w"},{"key":"e_1_3_3_24_2","unstructured":"Visual Crossing Weather Data. 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