Universität zu Köln

Beck, Moritz ORCID: 0009-0001-1969-3033, Koll, Carolin ORCID: 0000-0001-7940-3264, Dumpis, Uga ORCID: 0000-0001-6778-9411, Giske, Christian G. ORCID: 0000-0003-4327-6122, Göpel, Siri ORCID: 0000-0002-7666-4634, Jørgensen, Silje Bakken ORCID: 0000-0002-3135-1431, Kessel, Johanna, Kleppe, Lars Kaare ORCID: 0009-0000-4466-6187, Oma, Dorthea Hagen, Raz, Noa Eliakim, Semret, Makeda ORCID: 0000-0003-3875-4847, Simonsen, Gunnar Skov ORCID: 0000-0003-0043-7045, Vehreschild, Maria J. G. T. ORCID: 0000-0003-0446-3224, Albus, Kerstin ORCID: 0000-0003-1124-4310, Biehl, Lena M. ORCID: 0000-0001-7613-8119, Vehreschild, Jörg J. ORCID: 0000-0002-5446-7170, Classen, Annika Y. ORCID: 0000-0003-2905-5139, Aldins, Pauls, Akselsen, Per Espen, Asfeldt, Anne Mette, Conzelmann, Nadine, Davison, Kelly, Dietz, Thilo ORCID: 0000-0002-9378-6799, Eisenbeis, Simone, Fein, Lucas J., Farowski, Fedja ORCID: 0000-0002-6730-0038, Georghe, Romina, Samuel, Maayan Huberman, Jardin, Barbara Ann, Kaya, Merve, Kjellander, Christian, Ozola, Zane Linde, Leibovici, Leonard, Schulze, Nick ORCID: 0000-0002-9561-7905, Wåhlin, Hannes, Vilde, Aija and Zvirbulis, Viesturs (2025). Identifying patients at high risk for antibiotic treatment following hospital admission: a predictive score to improve antimicrobial stewardship measures. Infection, 53 (5). pp. 1941-1952. Springer Nature. ISSN 0300-8126

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Abstract

Purpose: Identifying patients for clinical studies evaluating strategies to reduce unnecessary antibiotic usage in hospitals is challenging. This study aimed to develop a predictive score to identify newly hospitalized patients with high likelihood of receiving antibiotics, thus improving patient inclusion in future studies focusing on antimicrobial stewardship (AMS) programs. Methods: This retrospective analysis used data from the PILGRIM study (NCT03765528), which included 1,600 patients across ten international sites. Predictive variables for antibiotic treatment during hospitalization were computed, and an additive score model was developed using logistic regression and 10-fold cross-validation. The PILGRIM score was validated in an independent cohort (validation cohort), with performance metrics assessed. Results: Data from 1,258 patients was included. In the development cohort 52.8% (n = 445) and in the validation cohort 42.4% (n = 134) of patients received antibiotics. Key predictors included hematologic malignancies, immunosuppressive medication, and past hospitalization. The logistic regression model demonstrated an area under the curve of 0.74 in the validation. The final additive score incorporated these predictors plus “planned elective surgery” achieving a specificity of 92%, a positive predictive value of 78%, a sensitivity of 41%, and a negative predictive value (NPV) of 69%in validation set. Conclusion: The PILGRIM score effectively identifies newly hospitalized patients likely to receive antibiotics, demonstrating high specificity and PPV. Its application can improve future AMS programs and trial recruitment by facilitating targeted inclusion of patients, especially in the hematological and oncological setting. Further -external and prospective- validation is needed to broaden the model’s applicability.

Item Type:	Article
Creators:	Creators Email ORCID ORCID Put Code Beck, Moritz UNSPECIFIED https://orcid.org/0009-0001-1969-3033 UNSPECIFIED Koll, Carolin UNSPECIFIED https://orcid.org/0000-0001-7940-3264 UNSPECIFIED Dumpis, Uga UNSPECIFIED https://orcid.org/0000-0001-6778-9411 UNSPECIFIED Giske, Christian G. UNSPECIFIED https://orcid.org/0000-0003-4327-6122 UNSPECIFIED Göpel, Siri UNSPECIFIED https://orcid.org/0000-0002-7666-4634 UNSPECIFIED Jørgensen, Silje Bakken UNSPECIFIED https://orcid.org/0000-0002-3135-1431 UNSPECIFIED Kessel, Johanna UNSPECIFIED UNSPECIFIED UNSPECIFIED Kleppe, Lars Kaare UNSPECIFIED https://orcid.org/0009-0000-4466-6187 UNSPECIFIED Oma, Dorthea Hagen UNSPECIFIED UNSPECIFIED UNSPECIFIED Raz, Noa Eliakim UNSPECIFIED UNSPECIFIED UNSPECIFIED Semret, Makeda UNSPECIFIED https://orcid.org/0000-0003-3875-4847 UNSPECIFIED Simonsen, Gunnar Skov UNSPECIFIED https://orcid.org/0000-0003-0043-7045 UNSPECIFIED Vehreschild, Maria J. G. T. UNSPECIFIED https://orcid.org/0000-0003-0446-3224 UNSPECIFIED Albus, Kerstin UNSPECIFIED https://orcid.org/0000-0003-1124-4310 UNSPECIFIED Biehl, Lena M. UNSPECIFIED https://orcid.org/0000-0001-7613-8119 UNSPECIFIED Vehreschild, Jörg J. UNSPECIFIED https://orcid.org/0000-0002-5446-7170 UNSPECIFIED Classen, Annika Y. UNSPECIFIED https://orcid.org/0000-0003-2905-5139 UNSPECIFIED Aldins, Pauls UNSPECIFIED UNSPECIFIED UNSPECIFIED Akselsen, Per Espen UNSPECIFIED UNSPECIFIED UNSPECIFIED Asfeldt, Anne Mette UNSPECIFIED UNSPECIFIED UNSPECIFIED Conzelmann, Nadine UNSPECIFIED UNSPECIFIED UNSPECIFIED Davison, Kelly UNSPECIFIED UNSPECIFIED UNSPECIFIED Dietz, Thilo UNSPECIFIED https://orcid.org/0000-0002-9378-6799 UNSPECIFIED Eisenbeis, Simone UNSPECIFIED UNSPECIFIED UNSPECIFIED Fein, Lucas J. UNSPECIFIED UNSPECIFIED UNSPECIFIED Farowski, Fedja UNSPECIFIED https://orcid.org/0000-0002-6730-0038 UNSPECIFIED Georghe, Romina UNSPECIFIED UNSPECIFIED UNSPECIFIED Samuel, Maayan Huberman UNSPECIFIED UNSPECIFIED UNSPECIFIED Jardin, Barbara Ann UNSPECIFIED UNSPECIFIED UNSPECIFIED Kaya, Merve UNSPECIFIED UNSPECIFIED UNSPECIFIED Kjellander, Christian UNSPECIFIED UNSPECIFIED UNSPECIFIED Ozola, Zane Linde UNSPECIFIED UNSPECIFIED UNSPECIFIED Leibovici, Leonard UNSPECIFIED UNSPECIFIED UNSPECIFIED Schulze, Nick UNSPECIFIED https://orcid.org/0000-0002-9561-7905 UNSPECIFIED Wåhlin, Hannes UNSPECIFIED UNSPECIFIED UNSPECIFIED Vilde, Aija UNSPECIFIED UNSPECIFIED UNSPECIFIED Zvirbulis, Viesturs UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-803334
Identification Number:	10.1007/s15010-025-02525-9
Journal or Publication Title:	Infection
Volume:	53
Number:	5
Page Range:	pp. 1941-1952
Number of Pages:	12
Date:	15 October 2025
Publisher:	Springer Nature
ISSN:	0300-8126
Language:	English
Faculty:	Faculty of Medicine
Divisions:	Faculty of Medicine > Innere Medizin > Klinik I für Innere Medizin - Hämatologie und Onkologie
Subjects:	Medical sciences Medicine
Uncontrolled Keywords:	Keywords Language Antimicrobial stewardship ; Antibiotic treatment ; Prediction score ; Clinical trial English
['eprint_fieldname_oa_funders' not defined]:	Publikationsfonds UzK
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/80333