Intensive care unit burden is associated with increased mortality in critically ill COVID-19 patients.

BACKGROUND: Traditional models to predict intensive care outcomes do not perform well in COVID-19. We undertook a comprehensive study of factors affecting mortality and functional outcome after severe COVID-19. METHODS: In this prospective multicentre cohort study, we enrolled laboratory-confirmed, critically ill COVID-19 patients at six ICUs in the Skåne Region, Sweden, between May 11, 2020, and May 10, 2021. Demographics and clinical data were collected. ICU burden was defined as the total number of ICU-treated COVID-19 patients in the region on admission. Surviving patients had a follow-up at 90 days for assessment of functional outcome using the Glasgow Outcome Scale-Extended (GOSE), an ordinal scale (1-8) with GOSE ≥5 representing a favourable outcome. The primary outcome was 90-day mortality; the secondary outcome was functional outcome at 90 days. RESULTS: Among 498 included patients, 74% were male with a median age of 66 years and a median body mass index (BMI) of 30 kg/m2 . Invasive mechanical ventilation was employed in 72%. Mortality in the ICU, in-hospital and at 90 days was 30%, 38% and 39%, respectively. Mortality increased markedly at age 60 and older. Increasing ICU burden was independently associated with a two-fold increase in mortality. Higher BMI was not associated with increased mortality. Besides age and ICU burden, smoking status, cortisone use, Pa CO2 >7 kPa, and inflammatory markers on admission were independent factors of 90-day mortality. Lower GOSE at 90 days was associated with a longer stay in the ICU. CONCLUSION: In critically ill COVID-19 patients, the 90-day mortality was 39% and increased considerably at age 60 or older. The ICU burden was associated with mortality, whereas a high BMI was not. A longer stay in the ICU was associated with unfavourable functional outcomes at 90 days.

Prevalence, Intensity, and Clinical Impact of Dyspnea in Critically Ill Patients Receiving Invasive Ventilation.

Rationale: Dyspnea is a traumatic experience. Only limited information is available on dyspnea in intubated critically ill patients. Objectives: Our objectives were 1) to quantify the prevalence and severity of dyspnea; and 2) to evaluate the impact of dyspnea on ICU length of stay and post-traumatic stress disorder (PTSD) 90 days after ICU discharge. Methods: This was a prospective cohort study in 10 ICUs in France. In patients intubated for more than 24 hours, dyspnea was quantified with a visual analog scale (from 0 to 10) as soon as they were able to communicate, the following day, and before spontaneous breathing trials. PTSD was defined by an Impact of Event Scale-Revised score of at least 22. Measurements and Main Results: Among the 612 patients assessed, 34% reported dyspnea, with a median dyspnea rating of 5 (interquartile range, 4-7). ICU length of stay was not significantly different between patients with versus without dyspnea (6 [3-12] and 6 [3-13] days, respectively; P = 0.781). Mortality was not different between groups. Of the 153 patients interviewed on Day 90, a higher proportion of individuals with probable PTSD was observed among patients who were dyspneic on enrollment (29% vs. 13%; P = 0.017). The density of dyspnea (number of dyspneic episodes divided by time from enrollment to extubation) was independently associated with PTSD (odds ratio, 1.07; 95% confidence interval, 1.01-1.13; P = 0.031). Conclusions: Dyspnea was frequent and intense in intubated critically ill patients. ICU length of stay was not significantly different among patients reporting dyspnea, but PTSD was more frequent at Day 90. Clinical trial registered with www.clinicaltrials.gov (NCT02336464).

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.

A randomised controlled trial of a nurse facilitator to promote communication for family members of critically ill patients.

PURPOSE: Suboptimal communication with clinicians, fragmented care and failure to align with patients' preferences are determinants of post intensive care unit (ICU) burden in family members. Our aim was to evaluate the impact of a nurse facilitator on family psychological burden. METHODS: We carried out a randomised controlled trial in five ICUs in France comparing standard communication by ICU clinicians to additional communication and support by nurse facilitators. We included patients > 18 years, with expected ICU length of stay > 2 days, chronic life-limiting illness, and their family members. Facilitators were trained to help families to secure care in line with patient's goals, beginning in ICU and continuing for 3 months. Assessments were made at baseline and 1, 3 and 6 months post-randomisation. Primary outcome was the evolution of family symptoms of depression over 6 months using a linear mixed effects model on the depression subscale of the Hospital Anxiety and Depression Scale (HADS). Secondary outcomes included HADS-Anxiety, Impact of Event Scale-6, goal-concordant care and experience of serious illness (QUAL-E). RESULTS: 385 patients and family members were enrolled. Follow-up at 1-, 3- and 6-month was completed by 284 (74%), 264 (68.6%) and 260 (67.5%) family members respectively. The intervention was associated with significantly more formal meetings between the ICU team and the family (1 [1-3] vs 2 [1-4]; p < 0.001). There was no significant difference between the intervention and control groups in evolution of symptoms of depression over 6 months (p = 0.91), nor in symptoms of depression at 6 months [0.53 95% CI (- 0.48; 1.55)]. There were no significant differences in secondary outcomes. CONCLUSION: This study does not support the use of facilitators for family members of ICU patients.