Surveying haemoperfusion impact on COVID-19 from machine learning using Shapley values.

Corticosteroid Haemoperfusion Mortality Shapley values Ventilation

Journal

Inflammopharmacology
ISSN: 1568-5608
Titre abrégé: Inflammopharmacology
Pays: Switzerland
ID NLM: 9112626

Informations de publication

Date de publication:
19 May 2024
Historique:
received: 02 04 2024
accepted: 05 05 2024
medline: 19 5 2024
pubmed: 19 5 2024
entrez: 19 5 2024
Statut: aheadofprint

Résumé

Haemoperfusion (HP) is an innovative extracorporeal therapy that utilizes special cartridges to filter the blood, effectively removing pro-inflammatory cytokines, toxins, and pathogens in COVID-19 patients. This retrospective cohort study aimed to assess the clinical benefits of HP for severe COVID-19 cases using Shapley values for machine learning models. The research involved 578 inpatients (≥ 20 years old) admitted to Baqiyatallah hospital (Tehran, Iran). The control group (359 patients) received standard treatment, including high doses of corticosteroids (a single 500 mg methylprednisolone pulse, followed by 250 mg for 2 days), categorized as regimen (I). On the other hand, the HP group (219 patients) received regimen II, consisting of the same corticosteroid treatment (regimen I) along with haemoperfusion using Cytosorb H300. The frequency of haemoperfusion sessions varied based on the type of lung involvement determined by chest CT scans. In addition, the value function Our data showed a favorable clinical response in the HP group compared to the control group. Notably, one-to-three sessions of HP using the CytoSorb The findings indicated that haemoperfusion played a crucial role in predicting patient survival, making it a significant feature in classifying patients' prognoses.

Sections du résumé

BACKGROUND BACKGROUND
Haemoperfusion (HP) is an innovative extracorporeal therapy that utilizes special cartridges to filter the blood, effectively removing pro-inflammatory cytokines, toxins, and pathogens in COVID-19 patients. This retrospective cohort study aimed to assess the clinical benefits of HP for severe COVID-19 cases using Shapley values for machine learning models.
METHODS METHODS
The research involved 578 inpatients (≥ 20 years old) admitted to Baqiyatallah hospital (Tehran, Iran). The control group (359 patients) received standard treatment, including high doses of corticosteroids (a single 500 mg methylprednisolone pulse, followed by 250 mg for 2 days), categorized as regimen (I). On the other hand, the HP group (219 patients) received regimen II, consisting of the same corticosteroid treatment (regimen I) along with haemoperfusion using Cytosorb H300. The frequency of haemoperfusion sessions varied based on the type of lung involvement determined by chest CT scans. In addition, the value function
RESULTS RESULTS
Our data showed a favorable clinical response in the HP group compared to the control group. Notably, one-to-three sessions of HP using the CytoSorb
CONCLUSION CONCLUSIONS
The findings indicated that haemoperfusion played a crucial role in predicting patient survival, making it a significant feature in classifying patients' prognoses.

Identifiants

pubmed: 38762840
doi: 10.1007/s10787-024-01494-z
pii: 10.1007/s10787-024-01494-z
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.

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Auteurs

Behzad Einollahi (B)

Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran. behzad.einollahi@gmail.com.

Mohammad Javanbakht (M)

Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.

Mehrdad Ebrahimi (M)

Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.

Mohammad Ahmadi (M)

Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.

Morteza Izadi (M)

Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.

Sholeh Ghasemi (S)

Department of Nephrology, Shahid Hasheminejad Kidney Center, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.

Zahra Einollahi (Z)

Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.

Bentolhoda Beyram (B)

Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.

Abolfazl Mirani (A)

Biomedical Engineering Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran. rsr.mirani@bmsu.ac.ir.

Ehsan Kianfar (E)

Biomedical Engineering Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran. ehsan_kianfar2010@yahoo.com.

Classifications MeSH