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Polypharmacy and Proton Pump Inhibitor Use Independently Predict One-Year Mortality in Critical COVID-19: An Explainable AI–Based Survival Analysis

Hjärtström et al., medRxiv, doi:10.1101/2025.10.27.25338863, Oct 2025
https://c19early.org/hjartstrom.html
Mortality -743% SHAP-derived HR improvement lower risk ← → higher risk Proton Pump Inhibitors  Hjärtström et al.  PROPHYLAXIS Is prophylaxis with proton pump inhibitors beneficial for COVID-19? Retrospective 497 patients in Sweden (May 2020 - May 2021) Higher mortality with proton pump inhibitors (p<0.000001) c19early.org Hjärtström et al., medRxiv, October 2025 0 0.5 1 1.5 2+ RR
PPIs for COVID-19
1st treatment shown to increase risk in September 2020, now with p = 0.000000048 from 40 studies.
6,200+ studies for 180+ treatments. c19early.org
Retrospective 497 critically ill COVID-19 patients in Swedish ICUs showing proton pump inhibitor use associated with higher one-year mortality. The machine-learning survival model obscures conventional HR calculation; however, the additive nature of the
SHAP explanation model enables surrogate derivations based on the explanatory importance of SHAP values. The HR should be interpreted as the relative influence on the predicted hazard rather than the relative risk for mortality.
risk of death, 743.0% higher, HR 8.43, p < 0.001, treatment 104, control 393, SHAP-derived HR.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Hjärtström et al., 28 Oct 2025, retrospective, Sweden, preprint, median age 66.0, 6 authors, study period May 2020 - May 2021. Contact: malin.hjartstrom@med.lu.se.
Polypharmacy and Proton Pump Inhibitor Use Independently Predict One-Year Mortality in Critical COVID-19: An Explainable AI–Based Survival Analysis
Malin Hjärtström, Ingrid Didriksson, Martin Spångfors, Hans Friberg, Andreas Jakobsson, Attila Frigyesi
doi:10.1101/2025.10.27.25338863
Mortality among patients admitted to intensive care with coronavirus disease 2019 (COVID-19) remains substantial despite advances in management. The contribution of pre-admission medication profiles to long-term survival is poorly defined. We analysed 497 adults with confirmed COVID-19 admitted to six intensive care units in southern Sweden between May 2020 and May 2021. Clinical and laboratory data were combined with prescription information from the national drug registry; drugs dispensed at least twice within eight months before admission were classified by Anatomical Therapeutic Chemical code. Polypharmacy was defined as the use of five or more medications. An XGBoost survival model with a Cox partial-likelihood objective was trained to predict one-year mortality and interpreted using SHapley Additive exPlanations (SHAP). The model achieved a concordance index of 0.74. Age was the strongest predictor of mortality, followed by the number of medications per patient, which ranked above the Charlson Comorbidity Index and Clinical Frailty Scale. Proton pump inhibitors were the only individual drug class among the top predictors, showing a modest positive association with mortality, whereas angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers had negligible contributions. These findings identify cumulative medication burden as an independent and clinically relevant marker of vulnerability in critical COVID-19.
Author contributions statement Additional information The authors declare no competing interests.
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DOI record: { "DOI": "10.1101/2025.10.27.25338863", "URL": "http://dx.doi.org/10.1101/2025.10.27.25338863", "abstract": "<jats:p>Mortality among patients admitted to intensive care with coronavirus disease 2019 (COVID-19) remains substantial despite advances in management. The contribution of pre-admission medication profiles to long-term survival is poorly defined. We analysed 497 adults with confirmed COVID-19 admitted to six intensive care units in southern Sweden between May 2020 and May 2021. Clinical and laboratory data were combined with prescription information from the national drug registry; drugs dispensed at least twice within eight months before admission were classified by Anatomical Therapeutic Chemical code. Polypharmacy was defined as the use of five or more medications. An XGBoost survival model with a Cox partial-likelihood objective was trained to predict one-year mortality and interpreted using SHapley Additive exPlanations (SHAP). The model achieved a concordance index of 0.74. Age was the strongest predictor of mortality, followed by the number of medications per patient, which ranked above the Charlson Comorbidity Index and Clinical Frailty Scale. Proton pump inhibitors were the only individual drug class among the top predictors, showing a modest positive association with mortality, whereas angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers had negligible contributions. These findings identify cumulative medication burden as an independent and clinically relevant marker of vulnerability in critical COVID-19.</jats:p>", "accepted": { "date-parts": [ [ 2025, 10, 28 ] ] }, "author": [ { "ORCID": "https://orcid.org/0000-0002-5294-8472", "affiliation": [], "authenticated-orcid": false, "family": "Hjärtström", "given": "Malin", "sequence": "first" }, { "ORCID": "https://orcid.org/0000-0003-1334-7583", "affiliation": [], "authenticated-orcid": false, "family": "Didriksson", "given": "Ingrid", "sequence": "additional" }, { "ORCID": "https://orcid.org/0000-0001-8754-899X", "affiliation": [], "authenticated-orcid": false, "family": "Spångfors", "given": "Martin", "sequence": "additional" }, { "affiliation": [], "family": "Friberg", "given": "Hans", "sequence": "additional" }, { "affiliation": [], "family": "Jakobsson", "given": "Andreas", "sequence": "additional" }, { "ORCID": "https://orcid.org/0000-0002-0155-4828", "affiliation": [], "authenticated-orcid": false, "family": "Frigyesi", "given": "Attila", "sequence": "additional" } ], "container-title": [], "content-domain": { "crossmark-restriction": false, "domain": [] }, "created": { "date-parts": [ [ 2025, 10, 29 ] ], "date-time": "2025-10-29T01:05:10Z", "timestamp": 1761699910000 }, "deposited": { "date-parts": [ [ 2025, 10, 29 ] ], "date-time": "2025-10-29T01:05:11Z", "timestamp": 1761699911000 }, "group-title": "Intensive Care and Critical Care Medicine", "indexed": { "date-parts": [ [ 2025, 10, 29 ] ], "date-time": "2025-10-29T08:11:49Z", "timestamp": 1761725509161, "version": "build-2065373602" }, "institution": [ { "name": "medRxiv" } ], "is-referenced-by-count": 0, "issued": { "date-parts": [ [ 2025, 10, 28 ] ] }, "license": [ { "URL": "http://creativecommons.org/licenses/by/4.0/", "content-version": "vor", "delay-in-days": 0, "start": { "date-parts": [ [ 2025, 10, 28 ] ], "date-time": "2025-10-28T00:00:00Z", "timestamp": 1761609600000 } } ], "link": [ { "URL": "https://syndication.highwire.org/content/doi/10.1101/2025.10.27.25338863", "content-type": "unspecified", "content-version": "vor", "intended-application": "similarity-checking" } ], "member": "246", "original-title": [], "posted": { "date-parts": [ [ 2025, 10, 28 ] ] }, "prefix": "10.1101", "published": { "date-parts": [ [ 2025, 10, 28 ] ] }, "publisher": "Cold Spring Harbor Laboratory", "reference-count": 0, "references-count": 0, "relation": {}, "resource": { "primary": { "URL": "http://medrxiv.org/lookup/doi/10.1101/2025.10.27.25338863" } }, "score": 1, "short-title": [], "source": "Crossref", "subject": [], "subtitle": [], "subtype": "preprint", "title": "Polypharmacy and Proton Pump Inhibitor Use Independently Predict One-Year Mortality in Critical COVID-19: An Explainable AI–Based Survival Analysis", "type": "posted-content" }
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