1.
A Portrait of SARS-CoV-2 Infection in Patients Undergoing Hematopoietic Cell Transplantation: A Systematic Review of the Literature
Bailey, A. J. M., Kirkham, A. M., Monaghan, M., Shorr, R., Buchan, C. A., Bredeson, C., Allan, D. S.
Current oncology (Toronto, Ont.). 2022;29(1):337-349
Abstract
The management of COVID-19 in hematopoietic cell transplant (HCT) recipients represents a special challenge given the variable states of immune dysregulation and altered vaccine efficacy in this population. A systematic search (Ovid Medline and Embase on 1 June 2021) was needed to better understand the presenting features, prognostic factors, and treatment options. Of 897 records, 29 studies were identified in our search. Most studies reporting on adults and pediatric recipients described signs and symptoms that were typical of COVID-19. Overall, the mortality rates were high, with 21% of adults and 6% of pediatric HCT recipients succumbing to COVID-19. The factors reported to be associated with increased mortality included age (HR = 1.21, 95% CI 1.03-1.43, p = 0.02), ICU admission (HR = 4.42, 95% CI 2.25-8.65, p < 0.001 and HR = 2.26, 95% CI 1.22-4.20, p = 0.01 for allogeneic and autologous HCT recipients), and low platelet count (OR = 21.37, 95% CI 1.71-267.11, p = 0.01). Performance status was associated with decreased mortality (HR = 0.83, 95% CI 0.74-0.93, p = 0.001). A broad range of treatments was described, although no controlled studies were identified. The risk of bias, using the Newcastle-Ottawa scale, was low. Patients undergoing HCT are at a high risk of severe morbidity and mortality associated with COVID-19. Controlled studies investigating potential treatments are required to determine the efficacy and safety in this population.
2.
Early warning of infection in patients undergoing hematopoietic stem cell transplantation using heart rate variability and serum biomarkers
Buchan, C. A., Li, H. O., Herry, C., Scales, N., MacPherson, P., Faller, E., Bredeson, C., Huebsch, L., Hodgins, M., Seely, A. J.
Transplantation and cellular therapy. 2021
Abstract
BACKGROUND Early warning of infection is critical to reduce 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 serum inflammatory biomarkers can have high specificity for infection, we hypothesized their combination may be useful for accurate early warning of infection. PURPOSE Develop and evaluate a composite predictive model utilizing continuous HRV with daily serum biomarker measurements to provide risk stratification of future deterioration in HCT patients. METHODS 116 ambulatory outpatients about to undergo HCT consented to collection of prospective demographic, clinical (daily vital signs), HRV (continuous electrocardiogram (ECG) monitoring, laboratory (daily serum samples frozen -80°C) and infection outcome variables (defined as the time of escalation of antibiotics), all from 24 hours (h) pre-transplant until infection or 14 days post-transplant. Indications for antibiotic escalation were adjudicated as "true infection" or not by two blinded HCT clinicians. A composite time series of 8 HRV metrics was created for each patient and the probability of deterioration within the next 72h was estimated using logistic regression modelling of composite HRV and serum biomarkers using a rule-based Naïve-Bayes model, if the HRV-based probability exceeded a median threshold. RESULTS 35(30%) patients withdrew within <24h due to intolerability of ECG monitoring, leaving 81 patients, of which 48(59%) had antibiotic escalation adjudicated as true infection. The combined HRV and biomarker (TNFa, IL6 and IL7) predictive model started increasing ~48 hours on average prior to diagnosis of infection, could distinguish between high risk of impending infection (>90% incidence of subsequent infection within 72h), average risk (~50%) and low risk (<10%), with an area under the receiver operating characteristic curve (AUC-ROC) of 0.87. CONCLUSION We derived a predictive model using HRV and serum biomarker to predict being diagnosed with infection within 72h combined in patients at high risk of infection. As prophylactic predictive ECG monitoring and daily serum collection proved challenging for many patients, further refinement in measurement is necessary for further study.