ArticleAnnals of intensive care2019
Impact of a computer-assisted decision support system (CDSS) on nutrition management in critically ill hematology patients: the NUTCHOCO study (nutritional care in hematology oncologic patients and critical outcome).
Article in Annals of intensive care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Identifying Behaviour Change Techniques in Cancer Nutrition Interventions and Their Implementation Contexts: A Systematic Review.Nutrients · 2026Pooled it
- Splenectomy in Onco-Hematologic Patients: A Retrospective Study of Early Complications and 1-Year Mortality.Cancers · 2025Article
- Artificial Intelligence in the Intensive Care Unit: Current Evidence on an Inevitable Future Tool.Cureus · 2024Review
- Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care-A Feasibility Study.Nutrients · 2023Article
- Refeeding Syndrome.Deutsches Arzteblatt international · 2023Review
- Machine-assisted nutritional and metabolic support.Intensive care medicine · 2022Article
- Usability study of a new tool for nutritional and glycemic management in adult intensive care: Glucosafe 2.Journal of clinical monitoring and computing · 2021Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMortality of critically ill hematology (HM) patients has improved over time. Thus, those patients require an extensive diagnostic workup and the optimal use of available treatments. There are no data regarding nutrition strategy for critically ill HM patients, while nutritional support is crucial for both HM and critically ill patients. We hypothesized that the implementation of a computer-assisted decision support system (CDSS), designed to supervise a nutritional intervention by a multidisciplinary team, would be able to increase guidelines adherence and outcomes.
resultsIn this before/after study, 275 critically ill hematology patients admitted to the ICU over 5-year period were included. Energy and protein intakes were delivered using standard protocol in the 147 patients (53%) of the 'before group' and using a CDSS in order to reach every day predefined caloric and protein targets accordingly to the catabolic or anabolic status in the 128 patients (47%) of the 'after group.' Using a Poisson regression, we showed that the use of CDSS allowed to reach a relative increase in the rate of days in compliance with caloric (1.57; 95% confidence interval (CI), [1.17-2.10], p = 0.0025) and protein targets (3.86 [2.21-6.73], p < 0.0001) in the 'after group' by more than 50% as compared with the 'before group.' Interestingly, compliance rates were low and only reached 30% after intervention. Hospital mortality, ICU-acquired infection, and hospital, and ICU length of stay were similar in the two groups of patients. Importantly, exploratory analysis showed that hospital mortality was lower in the 'after group' for neutropenic and severely ill patients.
conclusionFor critically ill hematology patients, the use of a nutritional CDSS allowed to increase the days in compliance with caloric and protein targets as compared with no CDSS use. In this context, overall hospital mortality was not affected.
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