Feasibility and reliability of frailty assessment in the critically ill: a systematic review

Background. For healthcare systems, an ageing population poses challenges in the delivery of equitable and effective care. Frailty assessment has the potential to improve care in the intensive care setting, but applying assessment tools in critical illness may be problematic. The aim of this systematic review was to evaluate evidence for the feasibility and reliability of frailty assessment in critical care. Methods. Our primary search was conducted in Medline, Medline In-process, EMBASE, CINAHL, PsycINFO, AMED, Cochrane Database of Systematic Reviews, and Web of Science (January 2001 to October 2017). We included observational studies reporting data on feasibility and reliability of frailty assessment in critical care setting in patients 16 years and older. Feasibility was assessed in terms of timing of evaluation, the background, training and expertise required for assessors, and reliance upon proxy input. Reliability was assessed in terms of inter-rater reliability. Results. Data from 11 study publications are included, representing eight study cohorts and 7761 patients. Proxy involvement in frailty assessment ranged from 58- 100%. Feasibility data were not well-reported overall, but the exclusion rate due to lack of proxy availability ranged from 0 to 45%, the highest rate observed where family involvement was mandatory and the assessment tool relatively complex (Frailty Index, FI). Conventional elements of Frailty Phenotype (FP) assessment required modification prior to use in two studies. Clinical staff tended to use a simple judgement-based tool, the Clinical Frailty Scale (CFS). Inter-rater reliability was reported in one study using the CFS and although a good level of agreement was observed between clinician assessments, this was a small and single centre study. Conclusion. Though of unproven reliability in the critically ill, CFS was the tool used most widely by critical care clinical staff. Conventional FP assessment required modification for general application in critical care, and a FI-based assessment may be difficult to deliver by the critical care team on a routine basis. There is a high reliance on proxies for frailty assessment, and the reliability of frailty assessment tools in critical care needs further evaluation. PROSPERO CRD42016052073

Prediction models for physical, cognitive, and mental health impairments after critical illness: a systematic review and critical appraisal

Objectives: Improved ability to predict impairments after critical illness could guide clinical decision-making, inform trial enrollment, and facilitate comprehensive patient recovery. A systematic review of the literature was conducted to investigate whether physical, cognitive, and mental health impairments could be predicted in adult survivors of critical illness. Data Sources: A systematic search of PubMed and the Cochrane Library (Prospective Register of Systematic Reviews ID: CRD42018117255) was undertaken on December 8, 2018, and the final searches updated on January 20, 2019. Study Selection: Four independent reviewers assessed titles and abstracts against study eligibility criteria. Studies were eligible if a prediction model was developed, validated, or updated for impairments after critical illness in adult patients. Discrepancies were resolved by consensus or an independent adjudicator. Data Extraction: Data on study characteristics, timing of outcome measurement, candidate predictors, and analytic strategies used were extracted. Risk of bias was assessed using the Prediction model Risk Of Bias Assessment Tool. Data Synthesis: Of 8,549 screened studies, three studies met inclusion. All three studies focused on the development of a prediction model to predict (1) a mental health composite outcome at 3 months post discharge, (2) return-to-pre-ICU functioning and residence at 6 months post discharge, and (3) physical function 2 months post discharge. Only one model had been externally validated. All studies had a high risk of bias, primarily due to the sample size, and statistical methods used to develop and select the predictors for the prediction published model. Conclusions: We only found three studies that developed a prediction model of any post-ICU impairment. There are several opportunities for improvement for future prediction model development, including the use of standardized outcomes and time horizons, and improved study design and statistical methodology.</p

Encoding microcarriers : present and future technologies

In answer to the ever-increasing need to carry out many assays simultaneously in drug screening and drug discovery, several microcarrier-based multiplex technologies have arisen in the past few years. The compounds to be screened are attached to the surface of microcarriers, which can be mixed together in a vessel that contains the target analyte. Each microcarrier has to be encoded to know which compound is attached to its surface. In this article, the methods that have been developed for the encoding of microcarriers are reviewed and discussed