Dataset Information

Neurological failure in ICU patients with hematological malignancies: A prospective cohort study.

ABSTRACT:

Background

Epidemiological studies of neurological complications in patients with hematological malignancies are scant. The objective of the study was to identify determinants of survival in patients with hematological malignancy and neurological failure.

Methods

Post hoc analysis of a prospective study of adults with hematological malignancies admitted for any reason to one of 17 university or university-affiliated participating ICUs in France and Belgium (2010-2012). The primary outcome was vital status at hospital discharge.

Results

Of the 1011 patients enrolled initially, 226 (22.4%) had neurological failure. Presenting manifestations were dominated by drowsiness or stupor (65%), coma (32%), weakness (26%), and seizures (19%). Neuroimaging, lumbar puncture, and electroencephalography were performed in 113 (50%), 73 (32%), and 63 (28%) patients, respectively. A neurosurgical biopsy was done in 1 patient. Hospital mortality was 50%. By multivariate analysis, factors independently associated with higher hospital mortality were poor performance status (odds ratio [OR], 3.99; 95%CI, 1.82-9.39; P = 0.0009), non-Hodgkin's lymphoma (OR, 2.60; 95%CI, 1.35-5.15; P = 0.005), shock (OR, 1.95; 95%CI, 1.04-3.72; P = 0.04), and respiratory failure (OR, 2.18; 95%CI, 1.14-4.25; P = 0.02); and factors independently associated with lower hospital mortality were GCS score on day 1 (OR, 0.88/point; 95%CI, 0.81-0.95; P = 0.0009) and autologous stem cell transplantation (OR, 0.25; 95%CI, 0.07-0.75; P = 0.02).

Conclusions

In ICU patients with hematological malignancies, neurological failure is common and often fatal. Independent predictors of higher hospital mortality were type of underlying hematological malignancy, poor performance status, hemodynamic and respiratory failures, and severity of consciousness impairment. Knowledge of these risk factors might help to optimize management strategies.

SUBMITTER: Marzorati C

PROVIDER: S-EPMC5466302 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Neurological failure in ICU patients with hematological malignancies: A prospective cohort study.

Marzorati Chiara C Mokart Djamel D Pène Frederic F Lemiale Virginie V Kouatchet Achille A Mayaux Julien J Vincent François F Nyunga Martine M Bruneel Fabrice F Rabbat Antoine A Lebert Christine C Perez Pierre P Benoit Dominique D Citerio Giuseppe G Azoulay Elie E Legriel Stephane S

PloS one 20170609 6

<h4>Background</h4>Epidemiological studies of neurological complications in patients with hematological malignancies are scant. The objective of the study was to identify determinants of survival in patients with hematological malignancy and neurological failure.<h4>Methods</h4>Post hoc analysis of a prospective study of adults with hematological malignancies admitted for any reason to one of 17 university or university-affiliated participating ICUs in France and Belgium (2010-2012). The primary ...[more]

PMID: 28598990

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Project description:BackgroundNosocomial infection (NI) causes prolonged hospital stays, increased healthcare costs, and higher mortality among patients with hematological malignancies (HM). However, few studies have compared the incidence of NI according to the HM lineage.ObjectiveTo compare the incidence of NI according to the type of HM lineage, and identify the risk factors for NI.MethodsThis prospective observational study monitored adult patients with HM admitted for >48 hours to the General Hospital of the People's Liberation Army during 2010-2013. Attack rates and incidences of NI were compared, and multivariable logistic regression was used to control for confounding effects.ResultsThis study included 6,613 admissions from 1,922 patients. During these admissions, 1,023 acquired 1,136 NI episodes, with an attack rate of 15.47% and incidence of 9.6‰ (95% CI: 9.1-10.2). Higher rates and densities of NIs were observed among myeloid neoplasm (MN) admissions, compared to lymphoid neoplasm (LN) admissions (28.42% vs. 11.00%, P<0.001 and 11.4% vs. 8.4‰, P<0.001). NI attack rates in acute myeloid leukemia (AML) and myelodysplastic/myeloproliferative neoplasm (MDS/MPN) were higher than those in MDS (30.69% vs. 20.19%, P<0.001; 38.89% vs. 20.19%, P = 0.003). Attack rates in T/NK-cell neoplasm and B-cell neoplasm were higher than those in Hodgkin lymphoma (15.04% vs. 3.65%; 10.94% vs. 3.65%, P<0.001). Multivariable regression analysis indicated prolonged hospitalization, presence of central venous catheterization, neutropenia, current stem cell transplant, infection on admission, and old age were independently associated with higher NI incidence. After adjusting for these factors, MN admissions still had a higher risk of infection (odds ratio 1.34, 95% CI: 1.13-1.59, P<0.001).ConclusionDifferent NI attack rates were observed for HM from different lineages, with MN lineages having a higher attack rate and incidence than LN lineages. Special attention should be paid to MN admissions, especially AML and MDS/MPN admissions, to control NI incidence.

Project description:BACKGROUND:ICU patients undergoing invasive mechanical ventilation experience cognitive decline associated with their critical illness and its management. The early detection of different cognitive phenotypes might reveal the involvement of diverse pathophysiological mechanisms and help to clarify the role of the precipitating and predisposing factors. Our main objective is to identify cognitive phenotypes in critically ill survivors 1 month after ICU discharge using an unsupervised machine learning method, and to contrast them with the classical approach of cognitive impairment assessment. For descriptive purposes, precipitating and predisposing factors for cognitive impairment were explored. METHODS:A total of 156 mechanically ventilated critically ill patients from two medical/surgical ICUs were prospectively studied. Patients with previous cognitive impairment, neurological or psychiatric diagnosis were excluded. Clinical variables were registered during ICU stay, and 100 patients were cognitively assessed 1 month after ICU discharge. The unsupervised machine learning K-means clustering algorithm was applied to detect cognitive phenotypes. Exploratory analyses were used to study precipitating and predisposing factors for cognitive impairment. RESULTS:K-means testing identified three clusters (K) of patients with different cognitive phenotypes: K1 (n?=?13), severe cognitive impairment in speed of processing (92%) and executive function (85%); K2 (n?=?33), moderate-to-severe deficits in learning-memory (55%), memory retrieval (67%), speed of processing (36.4%) and executive function (33.3%); and K3 (n?=?46), normal cognitive profile in 89% of patients. Using the classical approach, moderate-to-severe cognitive decline was recorded in 47% of patients, while the K-means method accurately classified 85.9%. The descriptive analysis showed significant differences in days (p?=?0.016) and doses (p?=?0.039) with opioid treatment in K1 vs. K2 and K3. In K2, there were more women, patients were older and had more comorbidities (p?=?0.001) than in K1 or K3. Cognitive reserve was significantly (p?=?0.001) higher in K3 than in K1 or K2. CONCLUSION:One month after ICU discharge, three groups of patients with different cognitive phenotypes were identified through an unsupervised machine learning method. This novel approach improved the classical classification of cognitive impairment in ICU survivors. In the exploratory analysis, gender, age and the level of cognitive reserve emerged as relevant predisposing factors for cognitive impairment in ICU patients. TRIAL REGISTRATION:ClinicalTrials.gov Identifier:NCT02390024; March 17,2015.

Dataset Information

Neurological failure in ICU patients with hematological malignancies: A prospective cohort study.

Background

Methods

Results

Conclusions

Publications

Neurological failure in ICU patients with hematological malignancies: A prospective cohort study.

Similar Datasets

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