Early Warning of Infection in Patients Undergoing Hematopoietic Stem Cell Transplantation Using Heart Rate Variability and Serum Biomarkers.

Early warning of infection Heart rate variability Hematopoietic stem cell transplantation Machine learning Predictive modeling Serum biomarkers

Journal

Transplantation and cellular therapy
ISSN: 2666-6367
Titre abrégé: Transplant Cell Ther
Pays: United States
ID NLM: 101774629

Informations de publication

Date de publication:
03 2022
Historique:
received: 14 12 2020
revised: 22 04 2021
accepted: 25 04 2021
pubmed: 9 5 2021
medline: 21 4 2022
entrez: 8 5 2021
Statut: ppublish

Résumé

Early warning of infection is critical to reduce the risk of deterioration and mortality, especially in neutropenic patients following hematopoietic stem cell transplantation (HCT). Given that heart rate variability (HRV) is a sensitive and early marker for infection, and that serum inflammatory biomarkers can have high specificity for infection, we hypothesized their combination may be useful for accurate early warning of infection. In this study, we developed and evaluated a composite predictive model using continuous HRV with daily serum biomarker measurements to provide risk stratification of future deterioration in HCT recipients. A total of 116 ambulatory outpatients about to undergo HCT consented to collection of prospective demographic, clinical (daily vital signs), HRV (continuous electrocardiography [ECG] monitoring, laboratory [daily serum samples frozen at -80 °C]), and infection outcome variables (defined as the time of escalation of antibiotics), all from 24 hours pre-HCT to the onset of infection or 14 days post-HCT. Indications for antibiotic escalation were adjudicated as "true infection" or not by 2 blinded HCT clinicians. A composite time series of 8 HRV metrics was created for each patient, and the probability of deterioration within the next 72 hours was estimated using logistic regression modeling of composite HRV and serum biomarkers using a rule-based naïve Bayes model if the HRV-based probability exceeded a median threshold. Thirty-five patients (30%) withdrew within <24 hours owing to intolerability of ECG monitoring, leaving 81 patients, of whom 48 (59%) had antibiotic escalation adjudicated as true infection. The combined HRV and biomarker (TNF-α, IL-6, and IL-7) predictive model began increasing at ~48 hours on average before the diagnosis of infection, could distinguish between high risk of impending infection (>90% incidence of subsequent infection within 72 hours), average risk (~50%), and low risk (<10%), with an area under the receiver operating characteristic curve of 0.87. However, given that prophylactic predictive ECG monitoring and daily serum collection proved challenging for many patients, further refinement in measurement is necessary for further study.

Identifiants

pubmed: 33964517
pii: S2666-6367(21)00884-8
doi: 10.1016/j.jtct.2021.04.023
pii:
doi:

Substances chimiques

Anti-Bacterial Agents 0
Biomarkers 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

166.e1-166.e8

Informations de copyright

Copyright © 2022. Published by Elsevier Inc.

Auteurs

C Arianne Buchan (CA)

Division of Infectious Diseases, Department of Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada; Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada; Ottawa Hospital Research Institute, Ottawa, Ontario, Canada. Electronic address: abuchan@toh.ca.

Heidi Oi-Yee Li (HO)

Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.

Christophe L Herry (CL)

Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.

Nathan Scales (N)

Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.

Paul MacPherson (P)

Division of Infectious Diseases, Department of Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada; Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada; Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.

Elliott Faller (E)

Division of Infectious Diseases, Department of Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada; Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.

Christopher Bredeson (C)

Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada; Ottawa Hospital Research Institute, Ottawa, Ontario, Canada; Division of Hematology, Department of Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada.

Lothar Huebsch (L)

Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada; Division of Hematology, Department of Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada.

Michael Hodgins (M)

Division of Hematology, Department of Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada.

Andrew J E Seely (AJE)

Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada; Ottawa Hospital Research Institute, Ottawa, Ontario, Canada; Departments of Critical Care Medicine and Surgery, The Ottawa Hospital, Ottawa, Ontario, Canada.

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Classifications MeSH