Short-term mortality of patients ≥80 years old admitted to European intensive care units: an international observational study

Mortality rate analysis of patients on invasive mechanical ventilation in the intensive care unit on day 28

Outcomes in patients receiving invasive mechanical ventilation (IMV) are currently unclear. The present study aimed to explore the prognostic factors of the mortality rate on day 28 in patients treated in the intensive care unit (ICU) and undergoing IMV. The IMV Mortality Prediction Score (IMPRES) of 129 patients in the ICU receiving IMV after emergency (or selective) endotracheal intubation from March 2018 to August 2020 was calculated. The patients were divided into survival (n=73) and death groups (n=56) on day 28. The predictive factors of independent and combined mortality rates were determined using a receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). The AUC of the IMPRES for predicting patient death on day 28 was 0.785 (95% confidence interval (CI): 0.704-0.864, P<0.01). When the IMPRES cut-off was 4.50, the Youden index was at its maximum (0.487) with a sensitivity of 85.7% and a specificity of 63.0%. The AUC of the ventilator use time (days) at 12.5 days cut-off was 0.653 (95% CI: 0.56-0.746, P<0.01), the Youden index was 0.235 with a sensitivity of 52.1% and a specificity of 71.4%. The AUC of the IMPRES combined with the duration of ventilator use was 0.856 (95% CI: 0.789-0.922, P<0.001), the Youden index was 0.635 with a sensitivity of 84.9% and a specificity of 78.6%. The IMPRES was observed to be the main factor influencing the mortality rate of patients receiving IMV at the ICU on day 28, and the IMPRES combined with the duration of ventilator use had a significant predictive value for the 28-day mortality rates of these patients.

Frailty assessment in critically ill older adults: a narrative review

Frailty, a condition that was first defined 20 years ago, is now assessed via multiple different tools. The Frailty Phenotype was initially used to identify a population of "pre-frail" and "frail" older adults, so as to prevent falls, loss of mobility, and hospitalizations. A different definition of frailty, via the Clinical Frailty Scale, is now actively used in critical care situations to evaluate over 65 year-old patients, whether it be for Intensive Care Unit (ICU) admissions, limitation of life-sustaining treatments or prognostication. Confusion remains when mentioning "frailty" in older adults, as to which tools are used, and what the impact or the bias of using these tools might be. In addition, it is essential to clarify which tools are appropriate in medical emergencies. In this review, we clarify various concepts and differences between frailty, functional autonomy and comorbidities; then focus on the current use of frailty scales in critically ill older adults. Finally, we discuss the benefits and risks of using standardized scales to describe patients, and suggest ways to maintain a complex, three-dimensional, patient evaluation, despite time constraints. Frailty in the ICU is common, involving around 40% of patients over 75. The most commonly used scale is the Clinical Frailty Scale (CFS), a rapid substitute for Comprehensive Geriatric Assessment (CGA). Significant associations exist between the CFS-scale and both short and long-term mortality, as well as long-term outcomes, such as loss of functional ability and being discharged home. The CFS became a mainstream tool newly used for triage during the Covid-19 pandemic, in response to the pressure on healthcare systems. It was found to be significantly associated with in-hospital mortality. The improper use of scales may lead to hastened decision-making, especially when there are strains on healthcare resources or time-constraints. Being aware of theses biases is essential to facilitate older adults' access to equitable decision-making regarding critical care. The aim is to help counteract assessments which may be abridged by time and organisational constraints.

Hospital and regional variations in intensive care unit admission for patients with invasive mechanical ventilation

BACKGROUND

Patients who receive invasive mechanical ventilation (IMV) in the intensive care unit (ICU) have exhibited lower in-hospital mortality rates than those who are treated outside. However, the patient-, hospital-, and regional factors influencing the ICU admission of patients with IMV have not been quantitatively examined.

METHODS

This retrospective cohort study used data from the nationwide Japanese inpatient administrative database and medical facility statistics. We included patients aged ≥ 15 years who underwent IMV between April 2018 and March 2019. The primary outcome was ICU admission on the day of IMV initiation. Multilevel logistic regression analyses incorporating patient-, hospital-, or regional-level variables were used to assess cluster effects by calculating the intraclass correlation coefficient (ICC), median odds ratio (MOR), and proportional change in variance (PCV).

RESULTS

Among 83,346 eligible patients from 546 hospitals across 140 areas, 40.4% were treated in ICUs on their IMV start day. ICU admission rates varied widely between hospitals (median 0.7%, interquartile range 0-44.5%) and regions (median 28.7%, interquartile range 0.9-46.2%). Multilevel analyses revealed significant effects of hospital cluster (ICC 82.2% and MOR 41.4) and regional cluster (ICC 67.3% and MOR 12.0). Including patient-level variables did not change these ICCs and MORs, with a PCV of 2.3% and - 1.0%, respectively. Further adjustment for hospital- and regional-level variables decreased the ICC and MOR, with a PCV of 95.2% and 85.6%, respectively. Among the hospital- and regional-level variables, hospitals with ICU beds and regions with ICU beds had a statistically significant and strong association with ICU admission.

CONCLUSIONS

Our results revealed that primarily hospital and regional factors, rather than patient-related ones, opposed ICU admissions for patients with IMV. This has important implications for healthcare policymakers planning interventions for optimal ICU resource allocation.

Frailty trajectories in ICU survivors: A comparison between the clinical frailty scale and the Tilburg frailty Indicator and association with 1 year mortality

PURPOSE

To test the agreement of the Clinical Frailty Scale (CFS) and the Tilburg Frailty Indicator (TFI), their association with 3, 6 months and 1-year mortality and the trajectory of frailty in a mixed population of ICU survivors.

MATERIAL AND METHODS

This is a prospective, multicenter, longitudinal study on ICU survivors ≥18 years old with an ICU stay >72 h. For each patient, sociodemographic and clinical data were collected. Frailty was assessed during ICU stay and at 3, 6, 12 months after ICU discharge, through both CFS and TFI.

RESULTS

124 patients with a mean age of 66 years old were enrolled. The baseline prevalence of frailty was 15.3% by CFS and 44.4% by TFI. Baseline CFS and TFI correlated but showed low agreement (Cohen's K = 0.23, p < 0.001). Baseline CFS score, but not TFI, was significantly associated to 1 year mortality. Moreover, CFS score during the follow-up was independently associated 1-year mortality (OR = 1.43; 95% CI: 1.18-1.73).

CONCLUSIONS

CFS and TFI identify different populations of frail ICU survivors. Frail patients before ICU according to CFS have a significantly higher mortality after ICU discharge. The CFS during follow-up is an independent negative prognostic factor of long-term mortality in the ICU population.

Surgery in older patients: learning from shared decision-making in intensive care

An increasing number of older patients are having surgical treatments. Similar to older patients admitted to intensive care, they present with additional problems including multimorbidity, frailty, and cognitive impairment. In both intensive care and surgical settings, comprehensive assessment can inform targeted interventions and shared decision-making. We explore the challenges faced by older patients, and by the clinicians treating them.