Development of a Frailty Index from Routine Hospital Data in Perioperative and Critical Care.

BACKGROUND/OBJECTIVES: Frailty is common in surgical and intensive care unit (ICU) populations, yet it is not routinely measured. Frailty indices are able to quantify this condition across a range of health deficits. We aimed to develop a frailty index (FI) from routinely collected hospital data in a surgical and ICU population. DESIGN: Prospective observational single-center cohort study. SETTING: Tertiary referral metropolitan Australian hospital. PARTICIPANTS: A total of 336 individuals aged 65 and older undergoing surgery or aged 50 and older admitted to the ICU. MEASUREMENTS: Routine admission health data were used to derive an FI comprising 36 health deficits. We examined the FI correlation with existing frailty tools (Clinical Frailty Scale [CFS] and Edmonton Frail Scale [EFS]) and assessed its predictive ability for negative outcomes including 30-day mortality. RESULTS: Median FI was .17 (interquartile range [IQR]) = .10-.24) for ICU patients and .17 (IQR = .11-.25) for surgical patients; maximum FI was .58, and 25% (95% confidence interval [CI] = 10.4-29.6) of patients overall were diagnosed with frailty (FI score ≥.25). Correlation was strong between the FI and the EFS: ρ = .76 (95% CI = .70-.83) for ICU patients and .71 (95% CI = .64-.78) for surgical patients, and the CFS was .77 (95% CI = .70-.84) for ICU patients and .72 (95% CI = .65-.79) for surgical patients. The FI had good discriminative ability for prediction of 30-day mortality in ICU patients (multivariate odds ratio for each increase in FI of .1 = 2.04 [95% CI = 1.19-3.48]), comparable with the performance of the Acute Physiology and Chronic Health Evaluation III score (ICU patients) and the Portsmouth Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity score (surgical patients). CONCLUSION: It is feasible to construct an FI from hospital admission data in a cohort of critically ill and surgical patients.

A checklist for intrahospital transport of critically ill patients improves compliance with transportation safety guidelines.

OBJECTIVES: Critically ill patients are often transferred from the intensive care unit (ICU) to other locations around the hospital during which adverse events, some life threatening, are common. An intercollegiate guideline covering the transport of critically ill patients exists in Australasia; however, compliance with this guideline has previously been shown to be poor, and its role in improving safety in transportation of patients in the ICU is unknown. We performed a pre-post interventional study in a tertiary metropolitan ICU, assessing the impact of the introduction of a transport checklist on guideline compliance. METHODS: We performed a prospective, pre-post interventional study, including a total of 76 transfers of critically ill patients between August 2016 and April 2017. RESULTS: After introduction of the checklist, aggregate median (interquartile range) guideline compliance improved from 86.7% (80.0-92.9) to 90% (86.7-100) (p = 0.01). Significant improvements were found in notification of the transport destination (83.7% vs 100%, p = 0.010) and transporting doctors' knowledge of the Cormack-Lehane grade of laryngoscopy (60.5% vs. 84.2%, p = 0.021). There was, however, a reduction in the proportion of full oxygen cylinders taken on transports (100% vs. 76.3%, p = 0.002). CONCLUSIONS: We conclude that a checklist is useful in improving safety in the transport of a critically ill patient population.

Contributors to frailty in critical illness: Multi-dimensional analysis of the Clinical Frailty Scale.

PURPOSE: Frailty in critical illness is common and associated with poor outcomes, however little is known about contributing factors. We compared the Clinical Frailty Scale (CFS) with a multi-dimensional validated tool, the Edmonton Frail Scale (EFS), and investigated which health domains are affected by frailty in ICU. MATERIALS AND METHODS: This prospective cohort study enrolled patients aged ≥50 years admitted between February-June 2017, comparing the CFS and EFS using Spearman correlation and Kappa coefficients, assessing frailty status across health domains, and examining outcomes including mortality. RESULTS: One hundred and sixty patients were enrolled, 33.8% were frail. Frail patients had greater in-hospital and 6-month mortality [25.9% vs. 8.5%; adjusted OR (95% CI) = 3.31 (1.17, 9.39), p = .024; and 40.4% vs. 17.3%; OR (95% CI) = 2.84 (1.18, 6.83), p = .020 respectively]. CFS and EFS scales were highly correlated [Spearman correlation coefficient = 0.85 (95% CI 0.81-0.88)], with high agreement [kappa coefficient = 0.78 (95% CI: 0.68-0.88)]. Frail patients had worse health status across the spectrum of frailty domains, in particular functional dependence, malnutrition, and prior hospital admissions. CONCLUSIONS: Frailty in the critically ill affects a range of health deficits, adequately measured via the CFS.

Protocol for a prospective observational study to develop a frailty index for use in perioperative and critical care.

INTRODUCTION: Frailty is of increasing importance to perioperative and critical care medicine, as the proportion of older patients increases globally. Evidence continues to emerge of the considerable impact frailty has on adverse outcomes from both surgery and critical care, which has led to a proliferation of different frailty measurement tools in recent years. Despite this, there remains a lack of easily implemented, comprehensive frailty assessment tools specific to these complex populations. Development of a frailty index using routinely collected hospital data, able to leverage the automated aspects of an electronic medical record, would aid risk stratification and benefit clinicians and patients alike. METHODS AND ANALYSIS: This is a prospective observational study. 150 intensive care unit (ICU) patients aged ≥50 years and 200 surgical patients aged ≥65 years will be enrolled. The primary objective is to develop a frailty index. Secondary objectives include assessing its ability to predict in-hospital mortality and/or discharge to a new non-home location; the performance of the frailty index in predicting postoperative and ICU complications, as well as health-related quality of life at 6 months; to compare the performance of the frailty index against existing frailty measurement and risk stratification tools; and to assess its modification by patients' health assets. ETHICS AND DISSEMINATION: This study has been approved by the Melbourne Health Human Research Ethics Committee(20 January 2017, HREC/16/MH/321). Dissemination will be via international and national anaesthetic and critical care conferences, and publication in the peer-reviewed literature.