scholarly journals Cost-effectiveness analysis of multimodal prognostication in cardiac arrest with EEG monitoring

Neurology ◽  
2020 ◽  
Vol 95 (5) ◽  
pp. e563-e575 ◽  
Author(s):  
Edilberto Amorim ◽  
Shirley S. Mo ◽  
Sebastian Palacios ◽  
Mohammad M. Ghassemi ◽  
Wei-Hung Weng ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Cost Effectiveness ◽  
Cost Effective ◽  
Eeg Monitoring ◽  
Monitoring Cost ◽  
Poor Outcome ◽  
Continuous Eeg ◽  
Continuous Eeg Monitoring ◽  
Increased Sensitivity ◽  
The Cost

ObjectiveTo determine cost-effectiveness parameters for EEG monitoring in cardiac arrest prognostication.MethodsWe conducted a cost-effectiveness analysis to estimate the cost per quality-adjusted life-year (QALY) gained by adding continuous EEG monitoring to standard cardiac arrest prognostication using the American Academy of Neurology Practice Parameter (AANPP) decision algorithm: neurologic examination, somatosensory evoked potentials, and neuron-specific enolase. We explored lifetime cost-effectiveness in a closed system that incorporates revenue back into the medical system (return) from payers who survive a cardiac arrest with good outcome and contribute to the health system during the remaining years of life. Good outcome was defined as a Cerebral Performance Category (CPC) score of 1–2 and poor outcome as CPC of 3–5.ResultsAn improvement in specificity for poor outcome prediction of 4.2% would be sufficient to make continuous EEG monitoring cost-effective (baseline AANPP specificity = 83.9%). In sensitivity analysis, the effect of increased sensitivity on the cost-effectiveness of EEG depends on the utility (u) assigned to a poor outcome. For patients who regard surviving with a poor outcome (CPC 3–4) worse than death (u = −0.34), an increased sensitivity for poor outcome prediction of 13.8% would make AANPP + EEG monitoring cost-effective (baseline AANPP sensitivity = 76.3%). In the closed system, an improvement in sensitivity of 1.8% together with an improvement in specificity of 3% was sufficient to make AANPP + EEG monitoring cost-effective, assuming lifetime return of 50% (USD $70,687).ConclusionIncorporating continuous EEG monitoring into cardiac arrest prognostication is cost-effective if relatively small improvements in sensitivity and specificity are achieved.

Early and persistent impaired percent alpha variability on continuous electroencephalography monitoring as predictive of poor outcome after traumatic brain injury

2002 ◽  
Vol 97 (1) ◽  
pp. 84-92 ◽  
Author(s):  
Paul M. Vespa ◽  
W. John Boscardin ◽  
David A. Hovda ◽  
David L. McArthur ◽  
Marc R. Nuwer ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Eeg Monitoring ◽  
Content Type ◽  
Poor Outcome ◽  
Continuous Electroencephalography ◽  
Continuous Eeg ◽  
Continuous Eeg Monitoring ◽  
Severe Tbi ◽  
Fine Print

Object. Early prediction of outcomes in patients after they suffer traumatic brain injury (TBI) is often nonspecific and based on initial imaging and clinical findings alone, without direct physiological testing. Improved outcome prediction is desirable for ethical, social, and financial reasons. The goal of this study was to determine the usefulness of continuous electroencephalography (EEG) monitoring in determining prognosis early after TBI, while the patient is in the intensive care unit. Methods. The authors hypothesized that the reduced percentage of alpha variability (PAV) in continuous EEG tracings indicates a poor prognosis. Prospective continuous EEG monitoring was performed in 89 consecutive patients with moderate to severe TBI (Glasgow Coma Scale [GCS] Scores 3–12) from 0 to 10 days after injury. The PAV was calculated daily, and the time course and trends of the PAV were analyzed in comparison with the patient's Glasgow Outcome Scale (GOS) score at the time of discharge. In patients with GCS scores of 8 or lower, a PAV value of 0.1 or lower is highly predictive of a poor outcome or death (positive predictive value 86%). The determinant PAV value was obtained by Day 3 after injury. Persistent PAV values of 0.1 or lower over several days or worsening of the PAV to a value of 0.1 or lower indicated a high likelihood of poor outcome (GOS Scores 1 and 2). In comparison with the combination of traditional initial clinical indicators of outcome (GCS score, pupillary response to light, patient age, results of computerized tomography scanning, and early hypotension or hypoxemia), the early PAV value during the initial 3 days after injury independently improved prognostic ability (p < 0.01). Conclusions. Continuous EEG monitoring performed with particular attention paid to the PAV is a sensitive and specific method of prognosis that can indicate outcomes in patients with moderate to severe TBI within 3 days postinjury.

scholarly journals Prognostic value of continuous EEG monitoring during therapeutic hypothermia after cardiac arrest

Critical Care ◽  
2010 ◽  
Vol 14 (5) ◽  
pp. R173 ◽  
Author(s):  
Andrea O Rossetti ◽  
Luis A Urbano ◽  
Frederik Delodder ◽  
Peter W Kaplan ◽  
Mauro Oddo
Keyword(s):  
Cardiac Arrest ◽  
Therapeutic Hypothermia ◽  
Prognostic Value ◽  
Eeg Monitoring ◽  
Continuous Eeg ◽  
Continuous Eeg Monitoring

Abstract 202: The Use of Bispectral Index EEG Monitoring as a Screening Tool for the Reliable Detection of Epileptic Activity in Post--Cardiac Arrest Patients

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Jolien Haesen ◽  
Lien Desteghe ◽  
Ingrid Meex ◽  
Cornelia Genbrugge ◽  
Jelle Demeestere ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Bispectral Index ◽  
Screening Tool ◽  
Interobserver Reliability ◽  
Epileptic Activity ◽  
High Accuracy ◽  
Eeg Monitoring ◽  
Continuous Eeg ◽  
Continuous Eeg Monitoring ◽  
Bis Monitor

Background: Assessment of prognosis in post[[Unable to Display Character: &#8211;]]cardiac arrest (CA) patients became very challenging since the introduction of therapeutic hypothermia (TH). Continuous EEG monitoring has been proposed to improve prognostication; however, its use is limited due to difficulties in readily interpretation. This emerges the need for a simple EEG montage. The bispectral index (BIS) monitor is a simplified EEG system, mainly calculating an index ranging from 0 (isoelectric EEG) to 100 (full consciousness) to provide information on hypnotic depth of anesthesia. The aim of the study was to validate the accuracy of simplified EEG monitoring in a CA - setting. Methods: BIS monitoring (BIS VISTA TM ) was applied to collect frontotemporal data in TH-treated CA patients. A standard 19 [[Unable to Display Character: &#8211;]] channel EEG was performed after return to normothermia. Afterwards, small EEG frames coincident with the time of full EEG registration were extracted from the BIS monitor. We asked 2 neurologists to indicate the presence of status epilepticus (SE), cerebral inactivity (CI), burst suppression (BS) or a diffuse slowing pattern (DS). In addition, these samples were analyzed by 2 inexperienced physicians, who were asked to indicate the presence of SE. Results: Thirty simplified EEG samples were analyzed. According to standard EEG, 11 patients showed a DS pattern, 3 had CI, 6 showed BS and 10 had an SE. Neurologists interpreted all samples with a high accuracy (sensitivity: 82% and specificity: 92%). Only 1 SE was missed by one neurologist. Interobserver reliability was high (kappa=0.843). High correlations were found for the comparison of full and simplified EEG for both neurologists (r=0.809). Further, the 2 inexperienced physicians identified SE with a sensitivity of 85% and specificity of 98%. Conclusion: Simplified EEG monitoring, using BIS, resulted in high accuracy of a simple classification system in post [[Unable to Display Character: &#8211;]] CA patients. Not only neurologists, but also treating physicians were capable to identify SE, which may play an important role in the early detection of SE. We suggest using BIS as a screening tool in post [[Unable to Display Character: &#8211;]] CA patients to save valuable time in the detection of SE, without replacing the need of full EEG monitoring for confirmation.

scholarly journals Cost-Effectiveness Analysis of BCG Vaccination against Tuberculosis in Indonesia: A Model-Based Study

Vaccines ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 707
Author(s):  
Afifah Machlaurin ◽  
Franklin Christiaan Karel Dolk ◽  
Didik Setiawan ◽  
Tjipke Sytse van der Werf ◽  
Maarten J. Postma
Keyword(s):  
Cost Effectiveness ◽  
Univariate Analysis ◽  
Cost Effective ◽  
Epidemiological Data ◽  
Control Programme ◽  
Detection Rates ◽  
Middle Income ◽  
Bcg Vaccination ◽  
Life Years ◽  
The Cost

Bacillus Calmette–Guerin (BCG), the only available vaccine for tuberculosis (TB), has been applied for decades. The Indonesian government recently introduced a national TB disease control programme that includes several action plans, notably enhanced vaccination coverage, which can be strengthened through underpinning its favourable cost-effectiveness. We designed a Markov model to assess the cost-effectiveness of Indonesia’s current BCG vaccination programme. Incremental cost-effectiveness ratios (ICERs) were evaluated from the perspectives of both society and healthcare. The robustness of the analysis was confirmed through univariate and probabilistic sensitivity analysis (PSA). Using epidemiological data compiled for Indonesia, BCG vaccination at a price US$14 was estimated to be a cost-effective strategy in controlling TB disease. From societal and healthcare perspectives, ICERs were US$104 and US$112 per quality-adjusted life years (QALYs), respectively. The results were robust for variations of most variables in the univariate analysis. Notably, the vaccine’s effectiveness regarding disease protection, vaccination costs, and case detection rates were key drivers for cost-effectiveness. The PSA results indicated that vaccination was cost-effective even at US$175 threshold in 95% of cases, approximating the monthly GDP per capita. Our findings suggest that this strategy was highly cost-effective and merits prioritization and extension within the national TB programme. Our results may be relevant for other high endemic low- and middle-income countries.

Sign in / Sign up

Export Citation Format

Share Document