Dataset Information

Prospective Validation of a Checklist to Predict Short-term Death in Older Patients After Emergency Department Admission in Australia and Ireland.

ABSTRACT:

Background

Emergency departments (EDs) are pressured environment where patients with supportive and palliative care needs may not be identified. We aimed to test the predictive ability of the CriSTAL (Criteria for Screening and Triaging to Appropriate aLternative care) checklist to flag patients at risk of death within 3 months who may benefit from timely end-of-life discussions.

Methods

Prospective cohorts of >65-year-old patients admitted for at least one night via EDs in five Australian hospitals and one Irish hospital. Purpose-trained nurses and medical students screened for frailty using two instruments concurrently and completed the other risk factors on the CriSTAL tool at admission. Postdischarge telephone follow-up was used to determine survival status. Logistic regression and bootstrapping techniques were used to test the predictive accuracy of CriSTAL for death within 90 days of admission as primary outcome. Predictability of in-hospital death was the secondary outcome.

Results

A total of 1,182 patients, with median age 76 to 80 years (IRE-AUS), were included. The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% confidence interval [CI] = 7.7-8.6) versus 5.7 (95% CI = 5.1-6.2) and Irish mean of 7.7 (95% CI = 6.9-8.5) versus 5.7 (95% CI = 5.1-6.2). The model with Fried frailty score was optimal for the derivation (Australian) cohort but prediction with the Clinical Frailty Scale (CFS) was also good (areas under the receiver-operating characteristic [AUROC] = 0.825 and 0.81, respectively). Values for the validation (Irish) cohort were AUROC = 0.70 with Fried and 0.77 using CFS. A minimum of five of 29 variables were sufficient for accurate prediction, and a cut point of 7+ or 6+ depending on the cohort was strongly indicative of risk of death. The most significant independent predictor of short-term death in both cohorts was frailty, carrying a twofold risk of death. CriSTAL's accuracy for in-hospital death prediction was also good (AUROC = 0.795 and 0.81 in Australia and Ireland, respectively), with high specificity and negative predictive values.

Conclusions

The modified CriSTAL tool (with CFS instead of Fried's frailty instrument) had good discriminant power to improve certainty of short-term mortality prediction in both health systems. The predictive ability of models is anticipated to help clinicians gain confidence in initiating earlier end-of-life discussions. The practicalities of embedding screening for risk of death in routine practice warrant further investigation.

SUBMITTER: Cardona M

PROVIDER: S-EPMC6619350 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Prospective Validation of a Checklist to Predict Short-term Death in Older Patients After Emergency Department Admission in Australia and Ireland.

Cardona Magnolia M O'Sullivan Michael M Lewis Ebony T ET Turner Robin M RM Garden Frances F Alkhouri Hatem H Asha Stephen S Mackenzie John J Perkins Margaret M Suri Sam S Holdgate Anna A Winoto Luis L Chang David C W DCW Gallego-Luxan Blanca B McCarthy Sally S Hillman Ken K Breen Dorothy D

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine 20181214 6

<h4>Background</h4>Emergency departments (EDs) are pressured environment where patients with supportive and palliative care needs may not be identified. We aimed to test the predictive ability of the CriSTAL (Criteria for Screening and Triaging to Appropriate aLternative care) checklist to flag patients at risk of death within 3 months who may benefit from timely end-of-life discussions.<h4>Methods</h4>Prospective cohorts of >65-year-old patients admitted for at least one night via EDs in five A ...[more]

PMID: 30428145

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Project description:IntroductionRapid-response teams (RRTs) are interdisciplinary groups created to rapidly assess and treat patients with unexpected clinical deterioration marked by decline in vital signs. Traditionally emergency department (ED) disposition is partially based on the patients' vital signs (VS) at the time of hospital admission. We aimed to identify which patients will have RRT activation within 12 hours of admission based on their ED VS, and if their outcomes differed.MethodsWe conducted a case-control study of patients presenting from January 2009 to December 2012 to a tertiary ED who subsequently had RRT activations within 12 hours of admission (early RRT activations). The medical records of patients 18 years and older admitted to a non-intensive care unit (ICU) setting were reviewed to obtain VS at the time of ED arrival and departure, age, gender and diagnoses. Controls were matched 1:1 on age, gender, and diagnosis. We evaluated VS using cut points (lowest 10%, middle 80% and highest 10%) based on the distribution of VS for all patients. Our study adheres to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting observational studies.ResultsA total of 948 patients were included (474 cases and 474 controls). Patients who had RRT activations were more likely to be tachycardic (odds ratio [OR] 2.02, 95% CI [1.25-3.27]), tachypneic (OR 2.92, 95% CI [1.73-4.92]), and had lower oxygen saturations (OR 2.25, 95% CI [1.42-3.56]) upon arrival to the ED. Patients who had RRT activations were more likely to be tachycardic at the time of disposition from the ED (OR 2.76, 95% CI [1.65-4.60]), more likely to have extremes of systolic blood pressure (BP) (OR 1.72, 95% CI [1.08-2.72] for low BP and OR 1.82, 95% CI [1.19-2.80] for high BP), higher respiratory rate (OR 4.15, 95% CI [2.44-7.07]) and lower oxygen saturation (OR 2.29, 95% CI [1.43-3.67]). Early RRT activation was associated with increased healthcare utilization and worse outcomes including increased rates of ICU admission within 72 hours (OR 38.49, 95%CI [19.03-77.87]), invasive interventions (OR 5.49, 95%CI [3.82-7.89]), mortality at 72 hours (OR 4.24, 95%CI [1.60-11.24]), and mortality at one month (OR 4.02, 95%CI [2.44-6.62]).ConclusionAfter matching for age, gender and ED diagnosis, we found that patients with an abnormal heart rate, respiratory rate or oxygen saturation at the time of ED arrival or departure are more likely to trigger RRT activation within 12 hours of admission. Early RRT activation was associated with higher mortality at 72 hours and one month, increased rates of invasive intervention and ICU admission. Determining risk factors of early RRT activation is of clinical, operational, and financial importance, as improved medical decision-making regarding disposition would maximize allocation of resources while potentially limiting morbidity and mortality.

Project description:BackgroundExtensive literature has shown an association of Adverse Childhood Experiences (ACEs) with adverse health outcomes; however, its ability to predict events or stratify risks is less known. Individuals with mental illness and ACE exposure have been shown to visit emergency departments (ED) more often than those in the general population. This study thus examined the ability of the ACEs checklist to predict ED visits within the subsequent year among children and adolescents presenting to mental health clinics with pre-existing mental health issues.MethodsThe study analyzed linked data (n = 6100) from two databases provided by Alberta Health Services (AHS). The Regional Access and Intake System (RAIS 2016-2018) database provided data on the predictors (ACE items, age, sex, residence, mental health program type, and primary diagnosis) regarding children and adolescents (aged 0-17 years) accessing addiction and mental health services within Calgary Zone, and the National Ambulatory Care Reporting System (NACRS 2016-2019) database provided data on ED visits. A 25% random sample of the data was reserved for validation purposes. Two Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression models, each employing a different method to tune the shrinkage parameter lambda (namely cross-validated and adaptive) and performing 10-fold cross-validation for a set of 100 lambdas in each model were examined.ResultsThe adaptive LASSO model had a slightly better fit in the validation dataset than the cross-validated model; however, it still demonstrated poor discrimination (AUC 0.60, sensitivity 37.8%, PPV 49.6%) and poor calibration (over-triaged in low-risk and under-triaged in high-risk subgroups). The model's poor performance was evident from an out-of-sample deviance ratio of - 0.044.ConclusionThe ACEs checklist did not perform well in predicting ED visits among children and adolescents with existing mental health concerns. The diverse causes of ED visits may have hindered accurate predictions, requiring more advanced statistical procedures. Future studies exploring other machine learning approaches and including a more extensive set of childhood adversities and other important predictors may produce better predictions. Furthermore, despite highly significant associations being observed, ACEs may not be deterministic in predicting health-related events at the individual level, such as general ED use.

Project description:ObjectivesTo devise an assessment tool to aid discharge and admission decision-making in relation to children and young people in hospital urgent and emergency care facilities, and thereby improve the quality of care that patients receive, using a clinical prediction modelling approach.DesignObservational cohort study with internal and external validation of a predictive tool.SettingTwo general emergency departments (EDs) and an urgent care centre in the North of England.ParticipantsThe eligibility criteria were children and young people 0-16 years of age who attended one of the three hospital sites within one National Health Service (NHS) organisation. Children were excluded if they opted out of the study, were brought to the ED following their death in the community or arrived in cardiac arrest when the heart rate and respiratory rate would be unmeasurable.Main outcome measuresAdmission or discharge. A participant was defined as being admitted to hospital if they left the ED to enter the hospital for further assessment, (including being admitted to an observation and assessment unit or hospital ward), either on first presentation or with the same complaint within 7 days. Those who were not admitted were defined as having been discharged.ResultsThe study collected data on 36 365 participants. 15 328 participants were included in the final analysis cohort (21 045 observations) and 17 710 participants were included in the validation cohort (23 262 observations). There were 14 variables entered into the regression analysis. Of the 13 that remained in the final model, 10 were present in all 500 bootstraps. The resulting Paediatric Admission Guidance in the Emergency Department (PAGE) score demonstrated good internal validity. The C-index (area under the ROC) was 0.779 (95% CI 0.772 to 0.786).ConclusionsFor units without the immediate availability of paediatricians the PAGE score can assist staff to determine risk of admission. Cut-off values will need to be adjusted to local circumstance.Study protocolThe study protocol has been published in an open access journal: Riaz et al Refining and testing the diagnostic accuracy of an assessment tool (Pennine Acute Hospitals NHS Trust-Paediatric Observation Priority Score) to predict admission and discharge of children and young people who attend an ED: protocol for an observational study. BMC Pediatr 18, 303 (2018). https://doi.org/10.1186/s12887-018-1268-7.Trial registration numberThe protocol has been published and the study registered (NIHR RfPB Grant: PB-PG-0815-20034; ClinicalTrials.gov:213469).

Dataset Information

Prospective Validation of a Checklist to Predict Short-term Death in Older Patients After Emergency Department Admission in Australia and Ireland.

Background

Methods

Results

Conclusions

Publications

Prospective Validation of a Checklist to Predict Short-term Death in Older Patients After Emergency Department Admission in Australia and Ireland.

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