Long-term health-related quality of life of critically ill patients with haematological malignancies: a prospective observational multicenter study

A nursing note-aware deep neural network for predicting mortality risk after hospital discharge

BACKGROUND

ICU readmissions and post-discharge mortality pose significant challenges. Previous studies used EHRs and machine learning models, but mostly focused on structured data. Nursing records contain crucial unstructured information, but their utilization is challenging. Natural language processing (NLP) can extract structured features from clinical text. This study proposes the Crucial Nursing Description Extractor (CNDE) to predict post-ICU discharge mortality rates and identify high-risk patients for unplanned readmission by analyzing electronic nursing records.

OBJECTIVE

Developed a deep neural network (NurnaNet) with the ability to perceive nursing records, combined with a bio-clinical medicine pre-trained language model (BioClinicalBERT) to analyze the electronic health records (EHRs) in the MIMIC III dataset to predict the death of patients within six month and two year risk.

DESIGN

A cohort and system development design was used.

SETTING(S)

Based on data extracted from MIMIC-III, a database of critically ill in the US between 2001 and 2012, the results were analyzed.

PARTICIPANTS

We calculated patients' age using admission time and date of birth information from the MIMIC dataset. Patients under 18 or over 89 years old, or who died in the hospital, were excluded. We analyzed 16,973 nursing records from patients' ICU stays.

METHODS

We have developed a technology called the Crucial Nursing Description Extractor (CNDE), which extracts key content from text. We use the logarithmic likelihood ratio to extract keywords and combine BioClinicalBERT. We predict the survival of discharged patients after six months and two years and evaluate the performance of the model using precision, recall, the F1-score, the receiver operating characteristic curve (ROC curve), the area under the curve (AUC), and the precision-recall curve (PR curve).

RESULTS

The research findings indicate that NurnaNet achieved good F1-scores (0.67030, 0.70874) within six months and two years. Compared to using BioClinicalBERT alone, there was an improvement in performance of 2.05 % and 1.08 % for predictions within six months and two years, respectively.

CONCLUSIONS

CNDE can effectively reduce long-form records and extract key content. NurnaNet has a good F1-score in analyzing the data of nursing records, which helps to identify the risk of death of patients after leaving the hospital and adjust the regular follow-up and treatment plan of relevant medical care as soon as possible.

Long-term survival and functional outcomes of critically ill patients with hematologic malignancies: a Canadian multicenter prospective study

PURPOSE

Patients with hematologic malignancy (HM) commonly develop critical illness. Their long-term survival and functional outcomes have not been well described.

METHODS

We conducted a prospective, observational study of HM patients admitted to seven Canadian intensive care units (ICUs) (2018-2020). We followed survivors at 7 days, 6 months and 12 months following ICU discharge. The primary outcome was 12-month survival. We evaluated functional outcomes at 6 and 12 months using the functional independent measure (FIM) and short form (SF)-36 as well as variables associated with 12-month survival.

RESULTS

We enrolled 414 patients including 35% women. The median age was 61 (interquartile range, IQR: 52-69), median Sequential Organ Failure Assessment (SOFA) score was 9 (IQR: 6-12), and 22% had moderate-severe frailty (clinical frailty scale [CFS] ≥ 6). 51% had acute leukemia, 38% lymphoma/multiple myeloma, and 40% had received a hematopoietic stem cell transplant (HCT). The most common reasons for ICU admission were acute respiratory failure (50%) and sepsis (40%). Overall, 203 (49%) were alive 7 days post-ICU discharge (ICU survivors). Twelve-month survival of the entire cohort was 21% (43% across ICU survivors). The proportion of survivors with moderate-severe frailty was 42% (at 7 days), 14% (6 months), and 8% (12 months). Median FIM at 7 days was 80 (IQR: 50-109). Physical function, pain, social function, mental health, and emotional well-being were below age- and sex-matched population scores at 6 and 12 months. Frailty, allogeneic HCT, kidney injury, and cardiac complications during ICU were associated with lower 12- month survival.

CONCLUSIONS

49% of all HM patients were alive at 7 days post-ICU discharge, and 21% at 12 months. Survival varied based upon hematologic diagnosis and frailty status. Survivors had important functional disability and impairment in emotional, physical, and general well-being.

Long-term, patient-centered, frailty-based outcomes of older critical illness survivors from the emergency department: a post hoc analysis of the LIFE Study

BACKGROUND

Evidence indicates frailty before intensive care unit (ICU) admission leads to poor outcomes. However, it is unclear whether quality of life (QOL) and activities of daily living (ADL) for survivors of critical illness admitted to the ICU via the emergency department remain consistent or deteriorate in the long-term compared to baseline. This study aimed to evaluate long-term QOL/ADL outcomes in these patients, categorized by the presence or absence of frailty according to Clinical Frailty Scale (CFS) score, as well as explore factors that influence these outcomes.

METHODS

This was a post-hoc analysis of a prospective, multicenter, observational study conducted across Japan. It included survivors aged 65 years or older who were admitted to the ICU through the emergency department. Based on CFS scores, participants were categorized into either the not frail group or the frail group, using a threshold CFS score of < 4. Our primary outcome was patient-centered outcomes (QOL/ADL) measured by the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) and the Barthel Index six months post-ICU admission, comparing results from baseline. Secondary outcomes included exploration of factors associated with QOL/ADL six months post-ICU admission using multiple linear regression analyses.

RESULTS

Of 514 candidates, 390 participants responded to the EQ-5D-5L questionnaire, while 237 responded to the Barthel Index. At six months post-admission, mean EQ-5D-5L values declined in both the not frail and frail groups (0.80 to 0.73, p = 0.003 and 0.58 to 0.50, p = 0.002, respectively); Barthel Index scores also declined in both groups (98 to 83, p < 0.001 and 79 to 61, p < 0.001, respectively). Multiple linear regression analysis revealed that baseline frailty (β coefficient, -0.15; 95% CI, - 0.23 to - 0.07; p < 0.001) and pre-admission EQ-5D-5L scores (β coefficient, 0.14; 95% CI, 0.02 to 0.26; p = 0.016) affected EQ-5D-5L scores at six months. Similarly, baseline frailty (β coefficient, -12.3; 95% CI, - 23.9 to - 0.80; p = 0.036) and Barthel Index scores (β coefficient, 0.54; 95% CI, 0.30 to 0.79; p < 0.001) influenced the Barthel Index score at six months.

CONCLUSIONS

Regardless of frailty, older ICU survivors from the emergency department were more likely to experience reduced QOL and ADL six months after ICU admission compared to baseline.

How Does Health-Related Quality of Life Change Over Time in Cancer Survivors Following an Admission to the Intensive Care Unit?: An Integrative Review

BACKGROUND

Cancer survivors account for 15% to 20% of all intensive care unit (ICU) admissions. In general ICU populations, patients are known to experience reduced health-related quality of life (HRQoL). However, little is known about HRQoL impacts among cancer survivors following a critical illness in ICU.

OBJECTIVE

The aim of this study was to critically synthesize the evidence to further understand the impact of a critical illness and ICU admission in cancer survivors.

METHODS

An integrative review was conducted and reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) guidelines. Three electronic databases were searched (MEDLINE, CINAHL, and EMBASE) using keywords and Boolean logic. Quality appraisal, data extraction, and a narrative synthesis were completed for all included studies by 2 reviewers.

RESULTS

Eleven publications met inclusion criteria. Health-related quality-of-life domains most frequently reported in cancer survivors after discharge from ICU included the following: physical function limitations, physical symptoms, and anxiety/depression.

CONCLUSIONS

Health-related quality of life decreased immediately after the admission to ICU with a gradual increase in the 3 to 12 months following. Cancer survivors are vulnerable to physical limitations, pain, and social isolation after an admission to ICU.

IMPLICATIONS FOR PRACTICE

Cancer survivors who have been affected by a critical illness are at risk of reduced HRQoL after an admission to ICU. This integrative review will help clinicians and researchers to develop patient-centered models of care during the recovery of critical illness, which are currently lacking in service delivery.

Prediction of post-traumatic stress disorder in family members of ICU patients: a machine learning approach

PURPOSE

Post-traumatic stress disorder (PTSD) can affect family members of patients admitted to the intensive care unit (ICU). Easily accessible patient's and relative's information may help develop accurate risk stratification tools to direct relatives at higher risk of PTSD toward appropriate management.

METHODS

PTSD was measured 90 days after ICU discharge using validated instruments (Impact of Event Scale and Impact of Event Scale-Revised) in 2374 family members. Various supervised machine learning approaches were used to predict PTSD in family members and evaluated on an independent held-out test dataset. To better understand variables' contributions to PTSD predicted probability, we used machine learning interpretability methods on the best predictive algorithm.

RESULTS

Non-linear ensemble learning tree-based methods showed better predictive performances (Random Forest-area under curve, AUC = 0.73 [0.68-0.77] and XGBoost-AUC = 0.73 [0.69-0.78]) than regularized linear models, kernel-based models, or deep learning models. In the best performing algorithm, most important features that positively contributed to PTSD's predicted probability were all non-modifiable factors, namely, lower patient's age, longer duration of ICU stay, relative's female sex, lower relative's age, relative being a spouse/child, and patient's death in ICU. A sensitivity analysis in bereaved relatives did not alter the algorithm's predictive performance.

CONCLUSION

We propose a machine learning-based approach to predict PTSD in relatives of ICU patients at an individual level. In this model, PTSD is mostly influenced by non-modifiable factors.

Sepsis and acute respiratory failure in patients with cancer: how can we improve care and outcomes even further?

PURPOSE OF REVIEW

Care and outcomes of critically ill patients with cancer have improved over the past decade. This selective review will discuss recent updates in sepsis and acute respiratory failure among patients with cancer, with particular focus on important opportunities to improve outcomes further through attention to phenotyping, predictive analytics, and improved outcome measures.

RECENT FINDINGS

The prevalence of cancer diagnoses in intensive care units (ICUs) is nontrivial and increasing. Sepsis and acute respiratory failure remain the most common critical illness syndromes affecting these patients, although other complications are also frequent. Recent research in oncologic sepsis has described outcome variation - including ICU, hospital, and 28-day mortality - across different types of cancer (e.g., solid vs. hematologic malignancies) and different sepsis definitions (e.g., Sepsis-3 vs. prior definitions). Research in acute respiratory failure in oncology patients has highlighted continued uncertainty in the value of diagnostic bronchoscopy for some patients and in the optimal respiratory support strategy. For both of these syndromes, specific challenges include multifactorial heterogeneity (e.g. in etiology and/or underlying cancer), delayed recognition of clinical deterioration, and complex outcomes measurement.

SUMMARY

Improving outcomes in oncologic critical care requires attention to the heterogeneity of cancer diagnoses, timely recognition and management of critical illness, and defining appropriate ICU outcomes.

High-value care for critically ill oncohematological patients: what do we know thus far?

The number of patients with cancer requiring intensive care unit admission is increasing around the world. The improvement in the pathophysiological understanding of this group of patients, as well as the increasingly better and more targeted treatment options for their underlying disease, has led to a significant increase in their survival over the past three decades. Within the organizational concepts, it is necessary to know what adds value in the care of critical oncohematological patients. Practices in medicine that do not benefit patients and possibly cause harm are called low-value practices, while high-value practices are defined as high-quality care at relatively low cost. In this article, we discuss ten domains with high-value evidence in the care of cancer patients: (1) intensive care unit admission policies; (2) intensive care unit organization; (3) etiological investigation of hypoxemia; (4) management of acute respiratory failure; (5) management of febrile neutropenia; (6) urgent chemotherapy treatment in critically ill patients; (7) patient and family experience; (8) palliative care; (9) care of intensive care unit staff; and (10) long-term impact of critical disease on the cancer population. The disclosure of such policies is expected to have the potential to change health care standards. We understand that it is a lengthy process, and initiatives such as this paper are one of the first steps in raising awareness and beginning a discussion about high-value care in various health scenarios.

Quality of life of patients with solid malignancies at 3 months after unplanned admission in the intensive care unit: A prospective case-control study

BACKGROUND

Although short- and long-term survival in critically ill patients with cancer has been described, data on their quality of life (QoL) after an intensive care unit (ICU) stay are scarce. This study aimed to determine the impact of an ICU stay on QoL assessed at 3 months in patients with solid malignancies.

METHODS

A prospective case-control study was conducted in three French ICUs between February 2020 and February 2021. Adult patients with lung, colorectal, or head and neck cancer who were admitted in the ICU were matched in a 1:2 ratio with patients who were not admitted in the ICU regarding their type of cancer, curative or palliative anticancer treatment, and treatment line. The primary endpoint was the QoL assessed at 3 months from inclusion using the mental and physical components of the Short Form 36 (SF-36) Health Survey. The use of anticancer therapies at 3 months was also evaluated.

RESULTS

In total, 23 surviving ICU cancer patients were matched with 46 non-ICU cancer patients. Four patients in the ICU group did not respond to the questionnaire. The mental component score of the SF-36 was higher in ICU patients than in non-ICU patients: median of 54 (interquartile range: 42-57) vs. 47 (37-52), respectively (p = 0.01). The physical component score of the SF-36 did not differ between groups: 35 (31-47) vs. 42 (34-47) (p = 0.24). In multivariate analysis, no association was found between patient QoL and an ICU stay. A good performance status and a non-metastatic cancer at baseline were independently associated with a higher physical component score. The use of anticancer therapies at 3 months was comparable between the two groups.

CONCLUSION

In patients with solid malignancies, an ICU stay had no negative impact on QoL at 3 months after discharge when compared with matched non-ICU patients.

One-year Mortality of Cancer Patients with an Unplanned ICU Admission: A Cohort Analysis Between 2008 and 2017 in the Netherlands

Introduction: A decrease in short-term mortality of critically ill cancer patients with an unplanned intensive care unit (ICU) admission has been described. Few studies describe a change over time of 1-year mortality. Therefore, we examined the 1-year mortality of cancer patients (hematological or solid) with an unplanned ICU admission and we described whether the mortality changed over time. Methods: We used the National Intensive Care Evaluation (NICE) registry and extracted all patients with an unplanned ICU admission in the Netherlands between 2008 and 2017. The primary outcome was 1-year mortality, analyzed with a mixed-effects Cox proportional hazard regression. We compared the 1-year mortality of cancer patients to that of patients without cancer. Furthermore, we examined changes in mortality over the study period. Results: We included 470,305 patients: 10,401 with hematological cancer, 35,920 with solid cancer, and 423,984 without cancer. The 1-year mortality rates were 60.1%, 46.2%, and 28.3% respectively (P< .01). Approximately 30% of the cancer patients surviving their hospital admission died within 1 year, this was 12% in patients without cancer. In hematological patients, 1-year mortality decreased between 2008 and 2011, after which it stabilized. In solid cancer patients, inspection showed neither an increasing nor decreasing trend over the inclusion period. For patients without cancer, 1-year mortality decreased between 2008 and 2013, after which it stabilized. A clear decrease in hospital mortality was seen within all three groups. Conclusion: The 1-year mortality of cancer patients with an unplanned ICU admission (hematological and solid) was higher than that of patients without cancer. About one-third of the cancer patients surviving their hospital admission died within 1 year after ICU admission. We found a decrease in 1-year mortality until 2011 in hematology patients and no decrease in solid cancer patients. Our results suggest that for many cancer patients, an unplanned ICU admission is still a way to recover from critical illness, and it does not necessarily lead to success in long-term survival. The underlying type of malignancy is an important factor for long-term outcomes in patients recovering from critical illness.

Health-related quality of life in critically ill survivors: specific impact of cardiac arrest in non-shockable rhythm

Background

Intensive care has a strong impact on health-related quality of life (HRQOL). The specific impact of cardiac arrest in non-shockable rhythm is poorly known.

Patients and methods

We gathered patients included in two randomized controlled trials (AWARE and HYPERION). The HYPERION trial included ICU-treated non-shockable cardiac arrest patients. The AWARE study included ICU patients requiring mechanical ventilation. We compared the 3-months HRQOL of these patients to those of a large sample of the French general population. Physical and mental dimension were compared. Multivariable linear regression was used to pick up factors associated with HRQOL.

Results

72 and 307 patients of the HYPERION and the AWARE studies were compared to 20,574 French controls. ICU patients evidenced lower scores in all the SF-36 dimensions compared to the controls. Similar scores were observed in both HYPERION and AWARe trials. The physical component score was lower in patients from the HYPERION trial compared to those from the AWARE trials and to controls (38.6 [29.6-47.8], 35.4 [27.5-46.4] vs. 53.0 [46.0-56.7], \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {p}<0.001$$\end{document}p<0.001). After adjustment for age and gender, HYPERION and AWARE trial status were associated wit lower physical component score.

Conclusion

Health-related quality of life of unshockable cardiac arrest survivors evaluated at 3 months was similar to ICU survivors and significantly lower than in individuals from general population, especially in the physical dimensions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00939-w.

Evolución Funcional Y Del Estado De Ánimo De Pacientes Tras Ingreso Por Covid-19 En Una Unidad De Cuidados Intensivos

Objetivo

Describir la situación funcional de los pacientes al mes y a los dos meses tras el ingreso por neumonía COVID-19 en una unidad de cuidados intensivos (UCI) y afectación del estado de ánimo al mes del alta hospitalaria.

Diseño

Estudio de cohortes prospectivo.

Pacientes

Ingresados en UCI por neumonía COVID-19 durante los meses de febrero a julio de 2020.

Variables de interés

Datos demográficos, mortalidad, estancia media en UCI y hospitalización, destino al alta, situación funcional (índice de Barthel) basal, tras el alta, al mes y a los dos meses, fisioterapia realizada y repercusión en el estado de ánimo (Escala Hospitalaria de Ansiedad y Depresión).

Resultados

Ingresaron en la UCI 89 pacientes. La mortalidad en UCI fue del 48,3%. Entre los supervivientes, 42 pacientes completaron seguimiento a los dos meses. Se objetivó un deterioro funcional al alta de UCI en el 97,6% y al alta hospitalaria en el 76,2%. En el seguimiento, un 66,7% había recuperado su nivel funcional basal al mes de salida del hospital y un 85,7% lo había hecho a los dos meses. Al mes del alta, el 12% presentaban resultados compatibles con ansiedad y un 20% compatibles con depresión.

Conclusiones

Los pacientes ingresados en UCI por neumonía COVID-19 presentan una mortalidad hospitalaria elevada y los supervivientes presentan un deterioro funcional severo. A los dos meses del alta, la mayoría recupera su situación funcional basal y estado emocional previos al ingreso.

Outcome of cancer patients considered for intensive care unit admission in two university hospitals in the Netherlands: the danger of delayed ICU admissions and off-hour triage decisions

Background

Very few studies assessed the association between Intensive Care Unit (ICU) triage decisions and mortality. The aim of this study was to assess whether an association could be found between 30-day mortality, and ICU admission consultation conditions and triage decisions.

Methods

We conducted a retrospective cohort study in two large referral university hospitals in the Netherlands. We identified all adult cancer patients for whom ICU admission was requested from 2016 to 2019. Via a multivariable logistic regression analysis, we assessed the association between 30-day mortality, and ICU admission consultation conditions and triage decisions.

Results

Of the 780 cancer patients for whom ICU admission was requested, 332 patients (42.6%) were considered ‘too well to benefit’ from ICU admission, 382 (49%) patients were immediately admitted to the ICU and 66 patients (8.4%) were considered ‘too sick to benefit’ according to the consulting intensivist(s). The 30-day mortality in these subgroups was 30.1%, 36.9% and 81.8%, respectively. In the patient group considered ‘too well to benefit’, 258 patients were never admitted to the ICU and 74 patients (9.5% of the overall study population, 22.3% of the patients ‘too well to benefit’) were admitted to the ICU after a second ICU admission request (delayed ICU admission). Thirty-day mortality in these groups was 25.6% and 45.9%. After adjustment for confounders, ICU consultations during off-hours (OR 1.61, 95% CI 1.09–2.38, p-value 0.02) and delayed ICU admission (OR 1.83, 95% CI 1.00–3.33, p-value 0.048 compared to “ICU admission”) were independently associated with 30-day mortality.

Conclusion

The ICU denial rate in our study was high (51%). Sixty percent of the ICU triage decisions in cancer patients were made during off-hours, and 22.3% of the patients initially considered “too well to benefit” from ICU admission were subsequently admitted to the ICU. Both decisions during off-hours and a delayed ICU admission were associated with an increased risk of death at 30 days. Our study suggests that in cancer patients, ICU triage decisions should be discussed during on-hours, and ICU admission policy should be broadened, with a lower admission threshold for critically ill cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00898-2.

Long-term quality of life in necrotizing soft-tissue infection survivors: a monocentric prospective cohort study

Background

Compared to other life-threatening infection survivors, long-term health-related quality of life (QOL) of patients surviving necrotizing soft-tissue infections (NSTI) and its determinants are little known.

In this monocentric prospective cohort including NSTI survivors admitted between 2014 and 2017, QOL was assessed during a phone interview using the 36-Item Short-Form Health Survey (SF-36), the Hospital Anxiety and Depression (HAD), the activity of daily living (ADL), instrumental ADL (IADL) scales and the Impact of Event Scale-Revised (IES-R). The primary outcome measure was the SF-36 physical component summary (PCS). NSTI patients were compared according to intensive care unit (ICU) admission status. ICU survivors were matched on SAPS II with non-NSTI related septic shock survivors.

Results

Forty-nine NSTI survivors were phone-interviewed and included in the study. Median PCS was decreased compared to the reference population [− 0.97 (− 2.27; − 0.08) SD]. Previous cardiac disease was the only variable associated with PCS alteration [multivariate regression coefficient: − 8.86 (− 17.64; − 0.07), p  =  0.048]. Of NSTI survivors, 15.2% had a HAD-D score  ≥  5 and 61.2% an IES-R score  ≥  33. ICU admission was not associated with lower PCS [35.21 (25.49–46.54) versus (vs) 41.82 (24.12–51.01), p  =  0.516], but with higher IES-R score [14 (7.5–34) vs 7 (3–18), p  =  0.035] and a higher proportion of HAD-D score  ≥  5 (28.6 vs 4.0%, p  =  0.036). Compared to non-NSTI septic shock-matched controls, NSTI patients had similar PCS [33.81 (24.58; − 44.39) vs 44.87 (26.71; − 56.01), p  =  0.706] but higher HAD-D [3.5 (1–7) vs 3 (1.5–6), p  =  0.048] and IES-R scores [18 (8–35) vs 8 (3–19), p  =  0.049].

Conclusions

Long-term QOL in NSTI survivors is severely impaired, similarly to that of non-NSTI septic shock patients for physical compartments, but with more frequent depressive and/or post-traumatic stress disorders. Only ICU admission and previous cardiac disease were predictive of QOL impairment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00891-9.

Relationship between intensive care unit-acquired weakness, fatigability and fatigue: What role for the central nervous system?

PURPOSE

To provide a comprehensive review of studies that have investigated fatigue in intensive care unit (ICU) survivors and questions the potential link between intensive care unit-acquired weakness (ICUAW), fatigability and fatigue. We also question whether the central nervous system (CNS) may be the link between these entities.

MATERIAL AND METHODS

A narrative review of the literature that investigated fatigue in ICU survivors and review of clinical trials enabling understanding of CNS alterations in response to ICU stays.

RESULTS

Fatigue is a pervasive and debilitating symptom in ICU survivors that can interfere with rehabilitation. Due to the complex pathophysiology of fatigue, more work is required to understand the roles of ICUAW and/or fatigability in fatigue to provide a more holistic understanding of this symptom. While muscle alterations have been well documented in ICU survivors, we believe that CNS alterations developing early during the ICU stay may play a role in fatigue.

CONCLUSIONS

Fatigue should be considered and treated in ICU survivors. The causes of fatigue are likely to be specific to the individual. Understanding the role that ICUAW and fatigability may have in fatigue would allow to tailor individual treatment to prevent this persistent symptom and improve quality of life.

One-year survival of patients with high-grade glioma discharged alive from the intensive care unit

Introduction

Only limited data are available regarding the long-term prognosis of patients with high-grade glioma discharged alive from the intensive care unit. We sought to quantify 1-year mortality and evaluate the association between mortality and (1) functional status, and (2) management of anticancer therapy in patients with high-grade glioma discharged alive from the intensive care unit.

Patients and methods

Retrospective observational cohort study of patients with high-grade glioma admitted to two intensive care units between January 2009 and June 2018. Functional status was assessed by the Karnofsky Performance Status. Anticancer therapy after discharge was classified as (1) continued (unchanged), (2) modified (changed or stopped), or (3) initiated (for newly diagnosed disease).

Results

Ninety-one high-grade glioma patients (73% of whom had glioblastoma) were included and 78 (86%) of these patients were discharged alive from the intensive care unit. Anticancer therapy was continued, modified, and initiated in 41%, 42%, and 17% of patients, respectively. Corticosteroid therapy at the time of ICU admission [odds ratio (OR) 0.07] and cancer progression (OR 0.09) was independently associated with continuation of anticancer therapy. The mortality rate 1 year after ICU admission was 73%. On multivariate analysis, continuation of anticancer therapy (OR 0.18) and Karnofsky performance status on admission (OR 0.90) were independently associated with lower 1-year mortality.

Conclusion

The presence of high-grade glioma is not sufficient to justify refusal of intensive care unit admission. Performance status and continuation of anticancer therapy are associated with higher survival after intensive care unit discharge.

Previous presentation

Preliminary results were presented at the most recent congress of the French Intensive Care Society, Paris, 2019.

Electronic supplementary material

The online version of this article (10.1007/s00415-020-10191-0) contains supplementary material, which is available to authorized users.