Clinical Frailty Scale (CFS) reliably stratifies octogenarians in German ICUs: a multicentre prospective cohort study

Background: In intensive care units (ICU) octogenarians become a routine patients group with aggravated therapeutic and diagnostic decision-making. Due to increased mortality and a reduced quality of life in this high-risk population, medical decision-making a fortiori requires an optimum of risk stratification. Recently, the VIP-1 trial prospectively observed that the clinical frailty scale (CFS) performed well in ICU patients in overall-survival and short-term outcome prediction. However, it is known that healthcare systems differ in the 21 countries contributing to the VIP-1 trial. Hence, our main focus was to investigate whether the CFS is usable for risk stratification in octogenarians admitted to diversified and high tech German ICUs. Methods: This multicentre prospective cohort study analyses very old patients admitted to 20 German ICUs as a sub-analysis of the VIP-1 trial. Three hundred and eight patients of 80 years of age or older admitted consecutively to participating ICUs. CFS, cause of admission, APACHE II, SAPS II and SOFA scores, use of ICU resources and ICU- and 30-day mortality were recorded. Multivariate logistic regression analysis was used to identify factors associated with 30-day mortality. Results: Patients had a median age of 84 [IQR 82–87] years and a mean CFS of 4.75 (± 1.6 standard-deviation) points. More than half of the patients (53.6%) were classified as frail (CFS ≥ 5). ICU-mortality was 17.3% and 30-day mortality was 31.2%. The cause of admission (planned vs. unplanned), (OR 5.74) and the CFS (OR 1.44 per point increase) were independent predictors of 30-day survival. Conclusions: The CFS is an easy determinable valuable tool for prediction of 30-day ICU survival in octogenarians, thus, it may facilitate decision-making for intensive care givers in Germany. Trial registration: The VIP-1 study was retrospectively registered on ClinicalTrials.gov (ID: NCT03134807 ) on May 1, 2017

Factors influencing the time to aseptic loosening by univariate and multivariate Cox-regression analysis.

<p>Factors influencing the time to aseptic loosening by univariate and multivariate Cox-regression analysis.</p

Clinical characteristics and genotype distribution in patients with primary THA and patients suffering from aseptic loosening.

<p>Clinical characteristics and genotype distribution in patients with primary THA and patients suffering from aseptic loosening.</p

Median time to aseptic loosening according to <i>BCL2</i> genotype.

<p>Median time to aseptic loosening according to <i>BCL2</i> genotype.</p

Time to aseptic loosening depending on <i>BCL2</i>–938 genotype.

<p>Time to aseptic loosening in the aseptic loosening group based on Kaplan-Meier-curves. (A) patients (n = 234), based on <i>BCL2</i> -938C>A genotype. (B) patients (n = 234) based on <i>BCL2</i> -938C>A CC+CA and AA genotype.</p