Dataset Information

The hanging chin sign as a mortality predictor in geriatric patients at the emergency department: a retrospective cohort study.

ABSTRACT:

Background

At the emergency department, there is a need for an instrument which is quick and easy to use to identify geriatric patients with the highest risk of mortality. The so- called 'hanging chin sign', meaning that the mandibula projects over one or more ribs on the chest X-ray, could be such an instrument. This study aims to investigate if the hanging chin sign is a predictor of mortality in geriatric patients admitted through the emergency department.

Methods

We performed an observational retrospective cohort study in a Dutch teaching hospital. Patients of ≥65 years who were admitted to the geriatric ward following an emergency department visit were included. The primary outcome of this study was mortality. Secondary outcomes included the length of admission, discharge destination and the reliability compared to patient-related variables and the APOP screener.

Results

Three hundred ninety-six patients were included in the analysis. Mean follow up was 300 days; 207 patients (52%) died during follow up. The hanging chin sign was present in 85 patients (21%). Patients with the hanging chin sign have a significantly higher mortality risk during admission (OR 2.94 (1.61 to 5.39), p < 0.001), within 30 days (OR 2.49 (1.44 to 4.31), p = 0.001), within 90 days (OR 2.16 (1.31 to 3.56), p = 0.002) and within end of follow up (OR 2.87 (1.70 to 4.84),p < 0.001). A chest X-ray without a PA view or lateral view was also associated with mortality. This technical detail of the chest x-ray and the hanging chin sign both showed a stronger association with mortality than patient-related variables or the APOP screener.

Conclusions

The hanging chin sign and other details of the chest x-ray were strong predictors of mortality in geriatric patients presenting at the emergency department and admitted to the geriatric ward. Compared to other known predictors, they seem to do even better in predicting mortality.

SUBMITTER: Huijgens ANJ

PROVIDER: S-EPMC8815262 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The hanging chin sign as a mortality predictor in geriatric patients at the emergency department: a retrospective cohort study.

Huijgens Anneloes N J ANJ van Baardewijk Laurens J LJ Keijsers Carolina J P W CJPW

BMC geriatrics 20220203 1

<h4>Background</h4>At the emergency department, there is a need for an instrument which is quick and easy to use to identify geriatric patients with the highest risk of mortality. The so- called 'hanging chin sign', meaning that the mandibula projects over one or more ribs on the chest X-ray, could be such an instrument. This study aims to investigate if the hanging chin sign is a predictor of mortality in geriatric patients admitted through the emergency department.<h4>Methods</h4>We performed ...[more]

PMID: 35114953

Similar Datasets

Project description:ObjectiveWe investigated whether serum high-sensitivity C reactive protein (hs-CRP) levels measured in an emergency department (ED) are associated with inhospital mortality in patients with cardiovascular disease (CVD).DesignA retrospective cohort study.SettingED of a teaching hospital in Japan.Participants12 211 patients with CVD aged ≥18 years who presented to the ED by an ambulance between 1 February 2006 and 30 September 2014 were evaluated.Main outcome measuresInhospital mortality.Results1156 patients had died. The inhospital mortality increased significantly with the hs-CRP levels (<3.0 mg/L: 7.0%, 95% CI 6.4 to 7.6; 3.1-5.4 mg/L: 9.6%, 95% CI 7.9 to 11.3: 5.5-11.5 mg/L: 11.2%, 95% CI 9.4 to 13.0; 11.6-33.2 mg/L: 12.3%, 95% CI 10.5 to 14.1 and ≥33.3 mg/L: 19.9%, 95% CI 17.6 to 22.2). The age-adjusted and sex-adjusted HR for total mortality was increased significantly in the three ≥5.5 mg/L groups compared with the <3.0 mg/L group (5.5-11.5 mg/L: HR=1.32, 95% CI 1.09 to 1.60, p=0.005; 11.6-33.2 mg/L: HR=1.38, 95% CI 1.14 to 1.65, p=0.001 and ≥33.3 mg/L: HR=2.15, 95% CI 1.84 to 2.51, p<0.001). Similar findings were observed for the CVD subtypes of acute myocardial infarction, heart failure, cerebral infarction and intracerebral haemorrhage. This association remained unchanged even after adjustment for age, sex and white cell count and withstood Bonferroni adjustment for multiple testing. When the causes of death were divided into primary CVD and non-CVD deaths, the association between initial hs-CRP levels and mortality remained significant, but the influence of hs-CRP levels was greater in non-CVD deaths than CVD deaths. The percentage of non-CVD deaths increased with hs-CRP levels; among the patients with hs-CRP levels ≥33.3 mg/L, non-CVD deaths accounted for 37.5% of total deaths.ConclusionOur findings suggest that increased hs-CRP is a significant risk factor for inhospital mortality among patients with CVD in an ED. Particular attention should be given to our finding that non-CVD death is a major cause of death among patients with CVD with higher hs-CRP levels.

Project description:BackgroundUrgency triage in the emergency department (ED) is important for early identification of potentially lethal conditions and extensive resource utilization. However, in older patients, urgency triage systems could be improved by taking geriatric vulnerability into account. We investigated the association of geriatric vulnerability screening in addition to triage urgency levels with 30-day mortality in older ED patients.DesignSecondary analysis of the observational multicenter Acutely Presenting Older Patient (APOP) study.SettingEDs within four Dutch hospitals.ParticipantsConsecutive patients, aged 70 years or older, who were prospectively included.MeasurementsPatients were triaged using the Manchester Triage System (MTS). In addition, the APOP screener was used as a geriatric screening tool. The primary outcome was 30-day mortality. Comparison was made between mortality within the geriatric high- and low-risk screened patients in every urgency triage category. We calculated the difference in explained variance of mortality by adding the geriatric screener (APOP) to triage urgency (MTS) by calculating Nagelkerke R2 .ResultsWe included 2,608 patients with a median age of 79 (interquartile range = 74-84) years, of whom 521 (20.0%) patients were categorized as high risk according to geriatric screening. Patients were triaged on urgency as standard (27.2%), urgent (58.5%), and very urgent (14.3%). In total, 132 (5.1%) patients were deceased within a period of 30 days. Within every urgency triage category, 30-day mortality was threefold higher in geriatric high-risk compared to low-risk patients (overall = 11.7% vs 3.4%; P < .001). The explained variance of 30-day mortality with triage urgency was 1.0% and increased to 6.3% by adding the geriatric screener.ConclusionCombining triage urgency with geriatric screening has the potential to improve triage, which may help clinicians to deliver early appropriate care to older ED patients. J Am Geriatr Soc 68:1755-1762, 2020.

Project description:Background: Comprehensive geriatric assessment (CGA) has been shown to improve outcomes in hospitalised older adults; however, there is currently no compelling evidence to support CGA interventions within the Emergency Department (ED). The aim of this study is to explore the clinical and process outcomes of older adults who receive ED-CGA over a period of six months after their initial ED attendance. Design: Prospective cohort study. Methods: The STrengthening the Reporting of the OBservational studies in Epidemiology (STROBE) standardised reporting guidelines will be adhered to. Older adults aged ≥65 years who score ≥2 on the Identification of Seniors at Risk (ISAR) tool and present to the ED with a medical complaint during the operational hours of the dedicated interdisciplinary team, will be considered eligible for recruitment. Demographic and health assessment information will be obtained at the ED index attendance followed by completion of an interdisciplinary CGA. A dedicated research nurse will complete follow-up telephone interviews with participants at 30 days and six months. The primary outcome will be incidence of hospital admission from the ED index attendance. Secondary outcomes will include functional decline, patient satisfaction with the ED index attendance, unscheduled ED reattendance(s), unscheduled hospital (re)admission(s), nursing home admission(s), healthcare utilisation, and death. Descriptive statistics will be used to profile the characteristics of the study participants and multivariate logistic and linear regression analysis will be used to analyse risk of adverse outcomes. Ethics and dissemination: Ethical approval was granted by the University of Limerick Hospital Group Research Ethics Committee (107/2021). The authors will disseminate study findings through publication in a peer-reviewed journal and presentation at national and international conferences. Patient and public involvement will be sought from a panel of older adults at the Ageing Research Centre in the University of Limerick. Clinicaltrials.gov Identifier: NCT05252182.

Project description:ObjectiveGiven the aging population and growing burden of frailty, we conducted this scoping review to describe the available literature regarding the use and impact of frailty assessment tools in the assessment and care of emergency department (ED) patients older than 60 years.MethodsA search was made of the available literature using the Covidence system using various search terms. Inclusion criteria comprised peer-reviewed literature focusing on frailty screening tools used for a geriatric population (60+ years of age) presenting to EDs. An additional search of PubMed, EBSCO, and CINAHL for articles published in the last 5 years was conducted toward the end of the review process (January 2023) to search specifically for literature describing interventions for frailty, yielding additional articles for review. Exclusion criteria comprised articles focusing on an age category other than geriatric and care environments outside the emergency care setting.ResultsA total of 135 articles were screened for inclusion and 48 duplicates were removed. Of the 87 remaining articles, 20 were deemed irrelevant, leaving 67 articles for full-text review. Twenty-eight were excluded for not meeting inclusion criteria, leaving 39 full-text studies. Use of frailty screening tools were reported in the triage, care, and discharge decision-making phases of the ED care trajectory, with varying reports of usefulness for clinical decision-making.ConclusionThe literature reports tools, scales, and instruments for identifying frailty in older patients at ED triage; multiple frailty scores or tools exist with varying levels of utilization. Interventions for frailty directed at the ED environment were scant. Further research is needed to determine the usefulness of frailty identification in the context of emergency care, the effects of care delivery interventions or educational initiatives for front-line medical professionals on patient-oriented outcomes, and to ensure these initiatives are acceptable for patients.

Project description:BackgroundWithin the trauma system, the emergency department (ED) is the hospital's first contact and is vital for allocating medical resources. However, there is generally limited information about patients that die in the ED.ObjectiveThe aim of this study was to develop an artificial intelligence (AI) model to predict trauma mortality and analyze pertinent mortality factors for all patients visiting the ED.MethodsWe used the Korean National Emergency Department Information System (NEDIS) data set (N=6,536,306), incorporating over 400 hospitals between 2016 and 2019. We included the International Classification of Disease 10th Revision (ICD-10) codes and chose the following input features to predict ED patient mortality: age, sex, intentionality, injury, emergent symptom, Alert/Verbal/Painful/Unresponsive (AVPU) scale, Korean Triage and Acuity Scale (KTAS), and vital signs. We compared three different feature set performances for AI input: all features (n=921), ICD-10 features (n=878), and features excluding ICD-10 codes (n=43). We devised various machine learning models with an ensemble approach via 5-fold cross-validation and compared the performance of each model with that of traditional prediction models. Lastly, we investigated explainable AI feature effects and deployed our final AI model on a public website, providing access to our mortality prediction results among patients visiting the ED.ResultsOur proposed AI model with the all-feature set achieved the highest area under the receiver operating characteristic curve (AUROC) of 0.9974 (adaptive boosting [AdaBoost], AdaBoost + light gradient boosting machine [LightGBM]: Ensemble), outperforming other state-of-the-art machine learning and traditional prediction models, including extreme gradient boosting (AUROC=0.9972), LightGBM (AUROC=0.9973), ICD-based injury severity scores (AUC=0.9328 for the inclusive model and AUROC=0.9567 for the exclusive model), and KTAS (AUROC=0.9405). In addition, our proposed AI model outperformed a cutting-edge AI model designed for in-hospital mortality prediction (AUROC=0.7675) for all ED visitors. From the AI model, we also discovered that age and unresponsiveness (coma) were the top two mortality predictors among patients visiting the ED, followed by oxygen saturation, multiple rib fractures (ICD-10 code S224), painful response (stupor, semicoma), and lumbar vertebra fracture (ICD-10 code S320).ConclusionsOur proposed AI model exhibits remarkable accuracy in predicting ED mortality. Including the necessity for external validation, a large nationwide data set would provide a more accurate model and minimize overfitting. We anticipate that our AI-based risk calculator tool will substantially aid health care providers, particularly regarding triage and early diagnosis for trauma patients.

Dataset Information

The hanging chin sign as a mortality predictor in geriatric patients at the emergency department: a retrospective cohort study.

Background

Methods

Results

Conclusions

Publications

The hanging chin sign as a mortality predictor in geriatric patients at the emergency department: a retrospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets