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Rate and predictors of serious neurologic causes of dizziness in the emergency department.

ABSTRACT: OBJECTIVE: To describe the rate and predictors of central nervous system (CNS) disease in emergency department (ED) patients with dizziness in the modern era of neuroimaging. PATIENTS AND METHODS: We retrospectively reviewed the medical records of all adults presenting between January 1, 2007, and December 31, 2009, to an academic ED for a primary triage complaint of dizziness, vertigo, or imbalance. The final diagnosis for the cause of dizziness was independently assigned by 2 neurologists, with a third neurologist resolving any disagreements. The primary outcome was a composite of ischemic stroke, intracranial hemorrhage, transient ischemic attack, seizure, brain tumor, demyelinating disease, and CNS infection. Univariate and multivariate logistic regression were used to assess the association between clinical variables and serious CNS causes of dizziness. RESULTS: Of 907 patients experiencing dizziness (mean age, 59 years; 58% women [n=529]), 49 (5%) had a serious neurologic diagnosis, including 37 cerebrovascular events. Dizziness was often caused by benign conditions, such as peripheral vertigo (294 patients [32%]) or orthostatic hypotension (121 patients [13%]). Age 60 years or older (odds ratio [OR], 5.7; 95% confidence interval [CI], 2.5-11.2), a chief complaint of imbalance (OR, 5.9; 95% CI, 2.3-15.2), and any focal examination abnormality (OR, 5.9; 95% CI, 3.1-11.2) were independently associated with serious neurologic diagnoses, whereas isolated dizziness symptoms were inversely associated (OR, 0.2; 95% CI, 0.0-0.7). CONCLUSION: Dizziness in the ED is generally benign, although a substantial fraction of patients harbor serious neurologic disease. Clinical suspicion should be heightened for patients with advanced age, imbalance, or focal deficits.

SUBMITTER: Navi BB

PROVIDER: S-EPMC3541873 | biostudies-other | 2012 Nov

REPOSITORIES: biostudies-other

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Rate and predictors of serious neurologic causes of dizziness in the emergency department.

Navi Babak B BB Kamel Hooman H Shah Maulik P MP Grossman Aaron W AW Wong Christine C Poisson Sharon N SN Whetstone William D WD Josephson S Andrew SA Johnston S Claiborne SC Kim Anthony S AS

Mayo Clinic proceedings 20121012 11

<h4>Objective</h4>To describe the rate and predictors of central nervous system (CNS) disease in emergency department (ED) patients with dizziness in the modern era of neuroimaging.<h4>Patients and methods</h4>We retrospectively reviewed the medical records of all adults presenting between January 1, 2007, and December 31, 2009, to an academic ED for a primary triage complaint of dizziness, vertigo, or imbalance. The final diagnosis for the cause of dizziness was independently assigned by 2 neur ...[more]

PMID: 23063099

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Project description:ObjectiveTo develop a risk prediction tool for acute ischemic stroke (AIS) for patients presenting to the emergency department (ED) with acute dizziness/vertigo or imbalance.MethodA prospective, multicenter cohort study was designed, and adult patients presenting with dizziness/vertigo or imbalance within 14 days were consecutively enrolled from the EDs of 4 tertiary hospitals between August 10, 2020, and June 10, 2021. Stroke was diagnosed by CT or MRI performed within 14 days of symptom onset. Participants were followed-up for 30 days. The least absolute shrinkage and selection operator (LASSO) logistic regression analysis was conducted to extract predictive factors that best identified patients at high risk of stroke to establish a prediction model. Model discrimination and calibration were assessed and its prediction performance was compared with the age, blood pressure, clinical features, duration, and diabetes (ABCD2) score, nystagmus scheme, and finger to nose test.ResultsIn this study, 790 out of 2,360 patients were enrolled {median age, 60.0 years [interquartile range (IQR), 51-68 years]; 354 (44.8%) men}, with complete follow-up data available. AIS was identified in 80 patients. An online web service tool (https://neuroby.shinyapps.io/dynnomapp/) was developed for stroke risk prediction, including the variables of sex, trigger, isolated symptom, nausea, history of brief dizziness, high blood pressure, finger to nose test, and tandem gait test. The model exhibited excellent discrimination with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.889 (95% CI: 0.855-0.923), compared with the ABCD2 score, nystagmus scheme, and finger to nose test [0.712 (95% CI, 0.652-0.771), 0.602 (95% CI, 0.556-0.648), and 61.7 (95% CI, 0.568-0.666) respectively].ConclusionOur new prediction model exhibited good performance and could be useful for stroke identification in patients presenting with dizziness, vertigo, or imbalance. Further externally validation study is needed to increase the strength of our findings.

Project description:BackgroundEmergency department crowding is a major global healthcare issue. There is much debate as to the causes of the phenomenon, leading to difficulties in developing successful, targeted solutions.AimThe aim of this systematic review was to critically analyse and summarise the findings of peer-reviewed research studies investigating the causes and consequences of, and solutions to, emergency department crowding.MethodThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A structured search of four databases (Medline, CINAHL, EMBASE and Web of Science) was undertaken to identify peer-reviewed research publications aimed at investigating the causes or consequences of, or solutions to, emergency department crowding, published between January 2000 and June 2018. Two reviewers used validated critical appraisal tools to independently assess the quality of the studies. The study protocol was registered with the International prospective register of systematic reviews (PROSPERO 2017: CRD42017073439).ResultsFrom 4,131 identified studies and 162 full text reviews, 102 studies met the inclusion criteria. The majority were retrospective cohort studies, with the greatest proportion (51%) trialling or modelling potential solutions to emergency department crowding. Fourteen studies examined causes and 40 investigated consequences. Two studies looked at both causes and consequences, and two investigated causes and solutions.ConclusionsThe negative consequences of ED crowding are well established, including poorer patient outcomes and the inability of staff to adhere to guideline-recommended treatment. This review identified a mismatch between causes and solutions. The majority of identified causes related to the number and type of people attending ED and timely discharge from ED, while reported solutions focused on efficient patient flow within the ED. Solutions aimed at the introduction of whole-of-system initiatives to meet timed patient disposition targets, as well as extended hours of primary care, demonstrated promising outcomes. While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding, with system-wide solutions tailored to address identified causes.

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Rate and predictors of serious neurologic causes of dizziness in the emergency department.

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Rate and predictors of serious neurologic causes of dizziness in the emergency department.

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