Benzodiazepine Initiation and the Risk of Falls or Fall-Related Injuries in Older Adults Following Acute Ischemic Stroke

Background

Benzodiazepine use in older adults following acute ischemic stroke (AIS) is common, yet short-term safety concerning falls or fall-related injuries remains unexplored.

Methods

We emulated a hypothetical randomized trial of benzodiazepine use during the acute post stroke recovery period to assess incidence of falls or fall related injuries in older adults. Using linked data from the Get With the Guidelines Registry and Mass General Brigham's electronic health records, we selected patients aged 65 and older admitted for Acute Ischemic Stroke (AIS) between 2014 and 2021 with no documented prior stroke and no benzodiazepine prescriptions in the previous 3 months. Potential for immortal-time and confounding biases was addressed via separate inverse-probability weighting strategies.

Results

The study included 495 patients who initiated inpatient benzodiazepines within three days of admission and 2,564 who did not. After standardization, the estimated 10-day risk of falls or fall-related injuries was 694 events per 1000 (95% confidence interval CI: 676-709) for the benzodiazepine initiation strategy and 584 events per 1000 (95% CI: 575-595) for the non-initiation strategy. Subgroup analyses showed risk differences of 142 events per 1000 (95% CI: 111-165) and 85 events per 1000 (95% CI: 64-107) for patients aged 65 to 74 years and for those aged 75 years or older, respectively. Risk differences were 187 events per 1000 (95% CI: 159-206) for patients with minor (NIHSS≤ 4) AIS and 32 events per 1000 (95% CI: 10-58) for those with moderate-to-severe AIS.

Conclusions

Initiating inpatient benzodiazepines within three days of AIS is associated with an elevated 10-day risk of falls or fall-related injuries, particularly for patients aged 65 to 74 years and for those with minor strokes. This underscores the need for caution with benzodiazepines, especially among individuals likely to be ambulatory during the acute and sub-acute post-stroke period.

Improving Seizure Frequency Documentation and Classification

Background and Objectives

Accurate and reliable seizure data are essential for evaluating treatment strategies and tracking the quality of care in epilepsy clinics. This quality improvement project aimed to increase seizure documentation (i.e., documentation of seizure frequency from 80% to 100%, date of last seizure from 35% to 50%, and International League Against Epilepsy (ILAE) seizure classification from 35% to at least 50%) over 6 months.

Methods

We surveyed 7 epileptologists to determine their perceived seizure frequency, ILAE classification, and date of last seizure documentation habits. Baseline data were collected weekly from September to December 2021. Subsequently, we implemented a newly created flowsheet in our Electronic Health Record (EHR) based on the Epilepsy Learning Healthcare System (ELHS) Case Report Forms to increase seizure documentation in a standardized way. Two epileptologists tested this flowsheet tool in their epilepsy clinics between February 2022 and July 2022. Data were collected weekly and compared with documentation from other epileptologists within the same group.

Results

Epileptologists at our center believed they documented seizure frequency for 84%-87% of clinic visits, which aligned with baseline data collection, showing they recorded seizure frequency for 83% of clinic visits. Epileptologists believed they documented ILAE classification for 47%-52% of clinic visits, and baseline data showed this was documented in 33% of clinic visits. They also reported documenting the date of the last seizure for 52%-63% of clinic visits, but this occurred in only 35% of clinic visits. After implementing the new flowsheet, documentation increased to nearly 100% for all fields being completed by the providers who tested the flowsheet.

Discussion

We demonstrated that by implementing an easy-to-use standardized EHR documentation tool, our documentation of critical metrics, as defined by the ELHS, improved dramatically. This shows that simple and practical interventions can substantially improve clinically meaningful documentation.

Brain health scores to predict neurological outcomes from electronic health records

BACKGROUND

Preserving brain health is a critical priority in primary care, yet screening for these risk factors in face-to-face primary care visits is challenging to scale to large populations. We aimed to develop automated brain health risk scores calculated from data in the electronic health record (EHR) enabling population-wide brain health screening in advance of patient care visits.

METHODS

This retrospective cohort study included patients with visits to an outpatient neurology clinic at Massachusetts General Hospital, between January 2010 and March 2021. Survival analysis with an 11-year follow-up period was performed to predict the risk of intracranial hemorrhage, ischemic stroke, depression, death and composite outcome of dementia, Alzheimer's disease, and mild cognitive impairment. Variables included age, sex, vital signs, laboratory values, employment status and social covariates pertaining to marital, tobacco and alcohol status. Random sampling was performed to create a training (70%) set for hyperparameter tuning in internal 5-fold cross validation and an external hold-out testing (30%) set of patients, both stratified by age. Risk ratios for high and low risk groups were evaluated in the hold-out test set, using 1000 bootstrapping iterations to calculate 95% confidence intervals (CI).

RESULTS

The cohort comprised 17,040 patients with an average age of 49 ± 15.6 years; majority were males (57 %), White (78 %) and non-Hispanic (80 %). The low and high groups average risk ratios [95 % CI] were: intracranial hemorrhage 0.46 [0.45-0.48] and 2.07 [1.95-2.20], ischemic stroke 0.57 [0.57-0.59] and 1.64 [1.52-1.69], depression 0.68 [0.39-0.74] and 1.29 [0.78-1.38], composite of dementia 0.27 [0.26-0.28] and 3.52 [3.18-3.81] and death 0.24 [0.24-0.24] and 3.96 [3.91-4.00].

CONCLUSIONS

Simple risk scores derived from routinely collected EHR accurately quantify the risk of developing common neurologic and psychiatric diseases. These scores can be computed automatically, prior to medical care visits, and may thus be useful for large-scale brain health screening.

Association of Early Seizure Prophylaxis With Posttraumatic Seizures and Mortality: A Meta-analysis With Evidence Quality Assessment

Purpose of the Review

To evaluate the quality of evidence about the association of primary seizure prophylaxis with antiseizure medication (ASM) within 7 days postinjury and the 18- or 24-month epilepsy/late seizure risk or all-cause mortality in adults with new-onset traumatic brain injury (TBI), in addition to early seizure risk.

Results

Twenty-three studies met the inclusion criteria (7 randomized and 16 nonrandomized studies). We analyzed 9,202 patients, including 4,390 in the exposed group and 4,812 in the unexposed group (894 in placebo and 3,918 in no ASM groups). There was a moderate to serious bias risk based on our assessment. Within the limitations of existing studies, our data revealed a lower risk for early seizures in the ASM prophylaxis group compared with placebo or no ASM prophylaxis (risk ratio [RR] 0.43, 95% confidence interval [CI] 0.33-0.57, p < 0.00001, I 2 = 3%). We identified high-quality evidence in favor of acute, short-term primary ASM use to prevent early seizures. Early ASM prophylaxis was not associated with a substantial difference in the 18- or 24-month risk of epilepsy/late seizures (RR 1.01, 95% CI 0.61-1.68, p = 0.96, I 2 = 63%) or mortality (RR 1.16, 95% CI 0.89-1.51, p = 0.26, I 2 = 0%). There was no evidence of strong publication bias for each main outcome. The overall quality of evidence was low and moderate for post-TBI epilepsy risk and all-cause mortality, respectively.

Summary

Our data suggest that the evidence showing no association between early ASM use and 18- or 24-month epilepsy risk in adults with new-onset TBI was of low quality. The analysis indicated a moderate quality for the evidence showing no effect on all-cause mortality. Therefore, higher-quality evidence is needed as a supplement for stronger recommendations.

Identification of patients with epilepsy using automated electronic health records phenotyping

OBJECTIVE

Unstructured data present in electronic health records (EHR) are a rich source of medical information; however, their abstraction is labor intensive. Automated EHR phenotyping (AEP) can reduce the need for manual chart review. We present an AEP model that is designed to automatically identify patients diagnosed with epilepsy.

METHODS

The ground truth for model training and evaluation was captured from a combination of structured questionnaires filled out by physicians for a subset of patients and manual chart review using customized software. Modeling features included indicators of the presence of keywords and phrases in unstructured clinical notes, prescriptions for antiseizure medications (ASMs), International Classification of Diseases (ICD) codes for seizures and epilepsy, number of ASMs and epilepsy-related ICD codes, age, and sex. Data were randomly divided into training (70%) and hold-out testing (30%) sets, with distinct patients in each set. We trained regularized logistic regression and an extreme gradient boosting models. Model performance was measured using area under the receiver operating curve (AUROC) and area under the precision-recall curve (AUPRC), with 95% confidence intervals (CI) estimated via bootstrapping.

RESULTS

Our study cohort included 3903 adults drawn from outpatient departments of nine hospitals between February 2015 and June 2022 (mean age = 47 ± 18 years, 57% women, 82% White, 84% non-Hispanic, 70% with epilepsy). The final models included 285 features, including 246 keywords and phrases captured from 8415 encounters. Both models achieved AUROC and AUPRC of 1 (95% CI = .99-1.00) in the hold-out testing set.

SIGNIFICANCE

A machine learning-based AEP approach accurately identifies patients with epilepsy from notes, ICD codes, and ASMs. This model can enable large-scale epilepsy research using EHR databases.

No short-term mortality from benzodiazepine use post-acute ischemic stroke after accounting for bias

BACKGROUND AND OBJECTIVES

Older adults receive benzodiazepines for agitation, anxiety, and insomnia after acute ischemic stroke (AIS). No trials have been conducted to determine if benzodiazepine use affects poststroke mortality in the elderly.

METHODS

We examined the association between initiating benzodiazepines within 1 week after AIS and 30-day mortality. We included patients ≥65 years, admitted for new nonsevere AIS (NIH-Stroke-Severity[NIHSS]≤ 20), 2014-2020, with no recorded benzodiazepine use in the previous 3 months and no contraindication for use. We linked a stroke registry to electronic health records, used inverse-probability weighting to address confounding, and estimated the risk difference (RD). A process of cloning, weighting, and censoring was used to avoid immortal time bias.

RESULTS

Among 2,584 patients, 389 received benzodiazepines. The crude 30-day mortality risk from treatment initiation was 212/1,000 among patients who received benzodiazepines, while the 30-day mortality was 34/1,000 among those who did not. When follow-up was aligned on day of AIS admission and immortal time was assigned to the two groups, the estimated risks were 27/1,000 and 22/1,000, respectively. Upon further adjustment for confounders, the RD was 5 (-12 to 19) deaths/1,000 patients.

CONCLUSION

The observed higher 30-day mortality associated with benzodiazepine initiation within 7 days was largely due to bias.

Evaluating The Accuracy Of Medicare Risk Adjustment For Alzheimer's Disease And Related Dementias

In 2020 Medicare reintroduced Alzheimer's disease and related dementias (ADRD) Hierarchical Condition Categories (HCCs) to risk-adjust Medicare Advantage and accountable care organization (ACO) payments. The potential for Medicare spending increases from this policy change are not well understood because the baseline accuracy of ADRD HCCs is uncertain. Using linked 2016-18 claims and electronic health record data from a large ACO, we evaluated the accuracy of claims-based ADRD HCCs against a reference standard of clinician-adjudicated disease. An estimated 7.5 percent of beneficiaries had clinician-adjudicated ADRD. Among those with ADRD HCCs, 34 percent did not have clinician-adjudicated disease. The false-negative and false-positive rates were 22.7 percent and 3.2 percent, respectively. Medicare spending for those with false-negative ADRD HCCs exceeded that of true positives by $14,619 per beneficiary. If, after the reintroduction of risk adjustment for ADRD, all false negatives were coded as having ADRD, expenditure benchmarks for beneficiaries with ADRD would increase by 9 percent. Monitoring ADRD coding could become challenging in the setting of concurrent incentives to decrease false-negative rates and increase false-positive rates.

Anti-seizure medication treatment and outcomes in acute ischemic stroke patients undergoing continuous EEG monitoring

OBJECTIVES

To determine the association of anti-seizure medication (ASM) treatment with outcomes in acute ischemic stroke (AIS) patients undergoing continuous electroencephalography (cEEG).

METHODS

Retrospective analysis of AIS patients admitted between 2012 and 2019. The following are the inclusion criteria: age ≥ 18 years and ≥ 16 h of cEEG within the first 7 days of admission. ASM treatment exposure was defined as > 48 h of treatment after the first 24 h of cEEG. The primary outcome measure was 90-day mortality, and the secondary outcome was 90-day functional recovery (Modified Ranking Scale 0-3). Propensity scores were used to adjust for baseline covariates and presence of epileptiform abnormalities (seizures, periodic and rhythmic patterns).

RESULTS

One hundred thirteen patients met the inclusion criteria; 39 (34.5%) were exposed to ASM. ASM treatment was not associated with 90-day mortality (propensity adjusted HR 1.0 [0.31-3.27], p = 0.999) or functional outcomes (adjusted HR 0.99 [0.32-3.02], p = 0.989), compared to no treatment.

CONCLUSIONS

In our study, ASM treatment in AIS patients with cEEG abnormalities was not significantly associated with a change in 90-day mortality and functional recovery. Larger comparative effectiveness studies are indicated to identify which acute ischemic stroke patients with cEEG abnormalities benefit most from ASM treatment.

Drivers of US health care spending for persons with seizures and/or epilepsies, 2010-2018

OBJECTIVE

This study was undertaken to characterize spending for persons classified with seizure or epilepsy and to determine whether spending has increased over time.

METHODS

In this cross-sectional study, we pooled data from the Medical Expenditure Panel Survey (MEPS) household component files for 2010-2018. We matched cases to controls on age and sex of a population-based sample of MEPS respondents (community-dwelling persons of all ages) with records associated with a medical event (e.g., outpatient visit, hospital inpatient) for seizure, epilepsy, or both. Outcomes were weighted to be representative of the civilian, noninstitutionalized population. We estimated the treated prevalence of epilepsy and seizure, health care spending overall and by site of care, and trends in spending growth.

RESULTS

We identified 1078 epilepsy cases and 2344 seizure cases. Treated prevalence was .38% (95% confidence interval [CI] = .34-.41) for epilepsy, .76% (95% CI = .71-.81) for seizure, and 1.14% (95% CI = 1.08-1.20) for epilepsy or seizure. The difference in annual spending for cases compared to controls was $4580 (95% CI = $3362-$5798) for epilepsy, $7935 (95% CI, $6237-$9634) for seizure, and $6853 (95% CI = $5623-$8084) for epilepsy or seizure, translating into aggregate costs of $5.4 billion, $19.0 billion, and $24.5 billion. From 2010 to 2018, the annual growth rate in total spending incurred for seizures and/or epilepsies was 7.6% compared to 3.6% among controls.

SIGNIFICANCE

US economic burden of seizures and/or epilepsies is substantial and warrants interventions focused on their unique and overlapping causes.

Linking the Paul Coverdell National Acute Stroke Program to commercial claims to establish a framework for real-world longitudinal stroke research

BACKGROUND

Non-interventional large-scale research on real-world patients who had a stroke requires the use of multiple data sources ensuring access to longitudinal data from large populations with clinically-detailed information. We sought to establish a framework for longitudinal research on patients hospitalised with stroke by linking information-rich, deidentified inpatient data from the Paul Coverdell National Acute Stroke Program (PCNASP) to commercial and Medicare Advantage longitudinal claims data.

METHODS

All stroke admissions in PCNASP between 2008 and 2015 were evaluated for linkage to longitudinal claims from a commercial insurer using an algorithm based on six available common data fields (patient age, gender, admission date, discharge date, discharge diagnosis and state) and a hospital match. We evaluated the linkage quality (via the percentage of unique records in the linked dataset) and the representativeness of the linked population. We also described medical history, stroke severity and patterns of medication use among the PCNASP-claims linked cohort.

RESULTS

The linkage produced uniqueness equal to 99.1%. We identified 5644 linked and 98 896 unlinked patients who had an ischaemic stroke hospitalisation in claims data. Linked patients were younger than unlinked (69.7 vs 72.5 years), but otherwise similar by medical history, prestroke medication use or lab values. Stroke severity was mild and most patients were discharged home. Prestroke and discharge use of antihypertensive and statins in the PCNASP were greater than their use as measured by filled prescriptions in claims.

CONCLUSIONS

High-quality linkage between the PCNASP and commercial claims data is feasible. This linkage identified differences between reported or recommended versus actual out-of-hospital medication utilisation, highlighting the importance of longitudinal data availability for research aimed to improve the care of patients who had a stroke.

Seizure Prophylaxis After Spontaneous Intracerebral Hemorrhage

Importance

Limited evidence is available concerning optimal seizure prophylaxis after spontaneous intracerebral hemorrhage (sICH).

Objective

To evaluate which of 4 seizure prophylaxis strategies provides the greatest net benefit for patients with sICH.

Design, Setting, and Participants

This decision analysis used models to simulate the following 4 common scenarios: (1) a 60-year-old man with low risk of early (≤7 days after stroke) (10%) and late (3.6% or 9.8%) seizures and average risk of short- (9%) and long-term (30%) adverse drug reaction (ADR); (2) an 80-year-old woman with low risk of early (10%) and late (3.6% or 9.8%) seizures and high short- (24%) and long-term (80%) ADR risks; (3) a 55-year-old man with high risk of early (19%) and late (34.8% or 46.2%) seizures and low short- (9%) and long-term (30%) ADR risks; and (4) a 45-year-old woman with high risk of early (19%) and late (34.8% or 46.2%) seizures and high short- (18%) and long-term (60%) ADR risks.

Interventions

The following 4 antiseizure drug strategies were included: (1) conservative, consisting of short-term (7-day) secondary early-seizure prophylaxis with long-term therapy after late seizure; (2) moderate, consisting of long-term secondary early-seizure prophylaxis or late-seizure therapy; (3) aggressive, consisting of long-term primary prophylaxis; and (4) risk guided, consisting of short-term secondary early-seizure prophylaxis among low-risk patients (2HELPS2B score, 0), short-term primary prophylaxis among patients at higher risk (2HELPS2B score, ≥1), and long-term secondary therapy for late seizure.

Main Outcomes and Measures

Quality-adjusted life-years (QALYs).

Results

For scenario 1, the risk-guided strategy (8.13 QALYs) was preferred over the conservative (8.08 QALYs), moderate (8.07 QALYs), and aggressive (7.88 QALYs) strategies. For scenario 2, the conservative strategy (2.18 QALYs) was preferred over the risk-guided (2.17 QALYs), moderate (2.09 QALYs), and aggressive (1.15 QALYs) strategies. For scenario 3, the aggressive strategy (9.21 QALYs) was preferred over the risk-guided (8.98 QALYs), moderate (8.93 QALYs), and conservative (8.77 QALYs) strategies. For scenario 4, the risk-guided strategy (11.53 QALYs) was preferred over the conservative (11.23 QALYs), moderate (10.93 QALYs), and aggressive (8.08 QALYs) strategies. Sensitivity analyses suggested that short-term strategies (conservative and risk guided) are preferred under most scenarios, and the risk-guided strategy performs comparably to or better than alternative strategies in most settings.

Conclusions and Relevance

This decision analytical model suggests that short-term (7-day) prophylaxis dominates longer-term therapy after sICH. Use of the 2HELPS2B score to guide clinical decisions for initiation of short-term primary vs secondary early-seizure prophylaxis should be considered for all patients after sICH.

Identifying Medicare beneficiaries with dementia

BACKGROUND/OBJECTIVES

No data exist regarding the validity of International Classification of Disease (ICD)-10 dementia diagnoses against a clinician-adjudicated reference standard within Medicare claims data. We examined the accuracy of claims-based diagnoses with respect to expert clinician adjudication using a novel database with individual-level linkages between electronic health record (EHR) and claims.

DESIGN

In this retrospective observational study, two neurologists and two psychiatrists performed a standardized review of patients' medical records from January 2016 to December 2018 and adjudicated dementia status. We measured the accuracy of three claims-based definitions of dementia against the reference standard.

SETTING

Mass-General-Brigham Healthcare (MGB), Massachusetts, USA.

PARTICIPANTS

From an eligible population of 40,690 fee-for-service (FFS) Medicare beneficiaries, aged 65 years and older, within the MGB Accountable Care Organization (ACO), we generated a random sample of 1002 patients, stratified by the pretest likelihood of dementia using administrative surrogates.

INTERVENTION

None.

MEASUREMENTS

We evaluated the accuracy (area under receiver operating curve [AUROC]) and calibration (calibration-in-the-large [CITL] and calibration slope) of three ICD-10 claims-based definitions of dementia against clinician-adjudicated standards. We applied inverse probability weighting to reconstruct the eligible population and reported the mean and 95% confidence interval (95% CI) for all performance characteristics, using 10-fold cross-validation (CV).

RESULTS

Beneficiaries had an average age of 75.3 years and were predominately female (59%) and non-Hispanic whites (93%). The adjudicated prevalence of dementia in the eligible population was 7%. The best-performing definition demonstrated excellent accuracy (CV-AUC 0.94; 95% CI 0.92-0.96) and was well-calibrated to the reference standard of clinician-adjudicated dementia (CV-CITL <0.001, CV-slope 0.97).

CONCLUSION

This study is the first to validate ICD-10 diagnostic codes against a robust and replicable approach to dementia ascertainment, using a real-world clinical reference standard. The best performing definition includes diagnostic codes with strong face validity and outperforms an updated version of a previously validated ICD-9 definition of dementia.

Patient reported outcomes in ALS: characteristics of the self-entry ALS Functional Rating Scale-revised and the Activities-specific Balance Confidence Scale

Objective: This study characterized two patient-reported outcome measures (PROMs): a patient-facing adaptation of the revised amyotrophic lateral sclerosis (ALS) Functional Rating Scale ("self-entry ALSFRS-R") and the Activities-specific Balance Confidence (ABC) Scale. Methods: ALS patients presenting to clinic completed PROMs that included (1) the self-entry ALSFRS-R, (2) the Activities-specific Balance Confidence Scale (ABC Scale), and (3) a question about falls. PROM data were compared to one another and to the traditional ALSFRS-R collected by trained evaluators in clinic ("standard ALSFRS-R"). Results: Over the data collection period, 449 ALS patients completed at least one of the three PROMs. Self-entry vs. standard ALSFRS-R total scores (n = 183) had high agreement (intraclass correlation (ICC)=0.81, 95% CI = 0.67, 0.88). Self-entry ALSFRS-R total scores were significantly higher than standard ALSFRS-R total scores (2.3 points, p < 0.001). In a subset of participants who contributed data at two timepoints, the average ALSFRS-R decline was not significantly different between methods (n = 49). ABC scores correlated highly with self-entry and standard ALSFRS-R Gross Motor subdomain scores (Pearson's r = 0.72, p < 0.001 and Pearson's r = 0.76, p < 0.001, respectively; n = 130). ABC score was negatively correlated with the number of reported falls within the last month (Spearman's r=-0.40; p < 0.001; n = 130). A 10-point decrease in ABC score increased odds of a reported fall by 16%. Conclusions: In a multidisciplinary clinic setting, self-entry and standard ALSFRS-R scores were similar, but not interchangeable. Self-entry scores were higher than standard ALSFRS-R scores but declined at a similar rate to the standard ALSFRS-R. ABC scores correlated with self-reported fall history and thus may provide useful data for clinical care.

Patterns of anticonvulsant use and adverse drug events in older adults

PURPOSE

To examine indications for, duration of use, and rate of adverse drug events (ADE) attributable to anticonvulsant initiation, as adjudicated by expert review of electronic health records (EHR) of older adults.

METHODS

We identified a cohort of community dwelling Medicare beneficiaries with linked EHR (aged 65+, continuously enrolled with a large health system/until death between 2012 and 2014, n = 20 945) and drew a stratified EHR review sample (n = 1534). An expert reviewed all records to adjudicate anticonvulsant use, years of use, indication for use, and evidence of ADEs attributable to anticonvulsant initiation. After excluding patients with insufficient EHR data (n = 37; 2%), we reconstructed the cohort using inverse probability weights to resemble the original cohort of eligible beneficiaries (n = 20 380). Among incident users of a single anticonvulsant, we estimated the rate of ADEs and described the type and severity of ADEs.

RESULTS

Overall, 12% (n = 2469) of eligible beneficiaries used at least one anticonvulsant in the 2012 to 2014 period (4% [n = 757] incident users, 8% [n = 1712] prevalent users). Incident users were most frequently prescribed gabapentin (n = 461/757, 61%), benzodiazepines (n = 122/757, 16%), and levetiracetam (n = 74/757, 10%); the most common indication was pain relief (n = 214; 28%) followed by epilepsy (n = 53; 7%). Among incident users, the overall ADE rate was 10/100 person-years (95% CI 4-20/100 person-years), of which 29% (n = 28/97) were life threatening (eg, somnolence). Most ADEs among incident monotherapy users were nervous system related (68%, n = 66/97).

CONCLUSION

Many older adult community dwelling traditional Medicare beneficiaries had clinically significant ADEs likely attributable to the initiation of anticonvulsant therapy, which was begun for a range of indications.

Implementing standardized provider documentation in a tertiary epilepsy clinic

OBJECTIVE

To incorporate standardized documentation into an epilepsy clinic and to use these standardized data to compare patients' perception of epilepsy diagnosis to provider documentation.

METHODS

Using quality improvement methodology, we implemented interventions to increase documentation of epilepsy diagnosis, seizure frequency, and type from 49.8% to 70% of adult nonemployee patients seen by 6 providers over 5 months of routine clinical care. The main intervention consisted of an interactive SmartPhrase that mirrored a documentation template developed by the Epilepsy Learning Healthcare System. We assessed the weekly proportion of complete SmartPhrases among eligible patient encounters with a statistical process control chart. We used a subset of patients with established epilepsy care linked to existing patient-reported survey data to examine the proportion of patient-to-provider agreement on epilepsy diagnosis (yes vs no/unsure). We also examined sociodemographic and clinical characteristics of patients who disagreed vs agreed with provider's documentation of epilepsy diagnosis.

RESULTS

The median SmartPhrase weekly completion rate was 78%. Established patients disagreed with providers with respect to epilepsy diagnosis in 18.5% of encounters (κ = 0.13), indicating that they did not have or were unsure if they had epilepsy despite having a provider-documented epilepsy diagnosis. Patients who disagreed with providers were similar to those who agreed with respect to age, sex, ethnicity, marital status, seizure frequency, type, and other quality-of-life measures.

CONCLUSION

This project supports the feasibility of implementing standardized documentation of data relevant to epilepsy care in a tertiary epilepsy clinic and highlights an opportunity for improvement in patient-provider communication.

Accuracy of ICD-10-CM claims-based definitions for epilepsy and seizure type

OBJECTIVE

To evaluate the accuracy of ICD-10-CM claims-based definitions for epilepsy and classifying seizure types in the outpatient setting.

METHODS

We reviewed electronic health records (EHR) for a cohort of adults aged 18+ years seen by six neurologists who had an outpatient visit at a level 4 epilepsy center between 01/2019-09/2019. The neurologists used a standardized documentation template to capture the diagnosis of epilepsy (yes/no/unsure), seizure type (focal/generalized/unknown), and seizure frequency in the EHR. Using linked ICD-10-CM codes assigned by the provider, we assessed the accuracy of claims-based definitions for epilepsy, focal seizure type, and generalized seizure type against the reference-standard EHR documentation by estimating sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

There were 673 eligible outpatient encounters. After review of EHRs for standardized documentation, an analytic sample consisted of 520 encounters representing 402 unique patients. In the EHR documentation, 93.5 % (n = 486/520) of encounters were with patients with a diagnosis of epilepsy. Of those, 66.0 % (n = 321/486) had ≥1 focal seizure, 41.6 % (n = 202/486) had ≥1 generalized seizure, and 7% (n = 34/486) had ≥1 unknown seizure. An ICD-10-CM definition for epilepsy (i.e., ICD-10 G40.X) achieved Sn = 84.4 % (95 % CI 80.8-87.5%), Sp = 79.4 % (95 % CI 62.1-91.3%), PPV = 98.3 % (95 % CI 96.6-99.3%), and NPV = 26.2 % (95 % CI 18.0-35.8%). The classification of focal vs generalized/unknown seizures achieved Sn = 69.8 % (95 % CI 64.4-74.8%), Sp = 79.4 % (95 % CI 72.4-85.3%), PPV = 86.8 % (95 % CI 82.1-90.7%), and NPV = 57.5 % (95 % CI 50.8-64.0%).

CONCLUSIONS

Claims-based definitions using groups of ICD-10-CM codes assigned by neurologists in routine outpatient clinic visits at a level 4 epilepsy center performed well in discriminating between patients with and without a diagnosis of epilepsy and between seizure types.

A feasibility assessment of functioning and quality-of-life patient-reported outcome measures in adult epilepsy clinics: A systematic review

OBJECTIVE

The objective of the study was to identify functioning and quality-of-life (QOL) patient-reported outcome measurements (PROMs) feasible for use in the waiting room of adult epilepsy clinics.

MATERIAL AND METHODS

We searched PubMed and Web of Science for articles on in English, Spanish, Portuguese, Italian, and French published by the end of February 15th, 2019. We screened retrieved titles and abstracts looking for publications that reported the use of PROMs to measure functioning and QOL in epilepsy. The authors, clinical experts, and patient advocates from the Epilepsy Foundation of America conceptualized a set of desirable feasibility attributes for PROMs implementation in the waiting room of adult epilepsy clinics. These attributes included brief time for completion (i.e., ≤3 min), free cost, coverage of four minimum QOL domains and respective facets, and good evidence of psychometric properties. We defined QOL domains according to the World Health Organization's classification and created psychometric appraisal criteria based on the Food and Drug Administration's (FDA) Guidance.

RESULTS

Eighteen candidate instruments were identified and compared with respect to desirable attributes for use in adult epilepsy clinics. We found that the Quality-of-life in epilepsy (QOLIE)-10 and Patient-Reported Outcome Measurement Information System-10 (PROMIS-10) were the most feasible PROMs for implementation in adult epilepsy clinics based on our criteria. The QOLIE-10 and PROMIS-10 still lack ideal evidence of responsiveness in people with epilepsy.

CONCLUSION

This is the first systematic review that aimed to assess feasibility properties of available functioning and QOL PROMs. The QOLIE-10 and PROMIS-10 are potentially feasible instruments for implementation in the waiting room of adult epilepsy clinics. Further studies assessing the responsiveness of these PROMs are needed and will contribute to the selection of the most appropriate instrument for longitudinal use in adult epilepsy clinical practice.

Implementation of quality measures and patient-reported outcomes in an epilepsy clinic

OBJECTIVE

To see if systematic collection of patient-reported epilepsy quality measures can identify opportunities to improve care, and to examine the associations between these measures and physical and mental health.

METHODS

We developed a patient-reported questionnaire for medication adherence, seizure frequency, medication side effects, and driving that included the Patient-Reported Outcome Measurement Information System-10 (PROMIS-10) (physical and mental health). We offered it to all adult patients seen twice in an epilepsy clinic (January 2017-January 2018). The questionnaire was available on the web as well as a tablet provided at appointment check-in. We used the first completed questionnaire to explore the relationship between patient-reported care quality and measures of physical and mental health.

RESULTS

A total of 610 unique patients (15% of the total encounters) completed a survey. Respondents were comparable to nonrespondents. Respondents reported gaps in care or opportunities for quality improvement in 48.4% (n = 295) of the encounters. Of patients who reported at least 1 seizure per month over the previous 3 months, 55.2% (n = 100) reported problems with adherence, 30.0% (n = 131) reported having problems believed to be adverse reactions to anticonvulsants, and 15.2% (n = 41) reported driving. In addition, respondents who reported either seizures over the recent 3 months, nonadherence to treatment due to cost, or anticonvulsant-associated adverse effects had consistently worse physical and mental health (all p < 0.05).

CONCLUSIONS

Systematic collection of epilepsy quality measures endorsed by the American Academy of Neurology can identify opportunities for quality improvement. Measures of epilepsy care quality predict outcomes that matter to patients.

Medicare claims can identify post-stroke epilepsy

OBJECTIVE

There have been no validated Medicare claims-based algorithms available to identify epilepsy by discrete etiology of stroke (e.g., post-stroke epilepsy, PSE) in community-dwelling elderly individuals, despite the increasing availability of large datasets. Our objective was to validate algorithms that detect which patients have true PSE.

METHODS

We linked electronic health records (EHR) to Medicare claims from a Medicare Pioneer Accountable Care Organization (ACO) to identify PSE. A neurologist reviewed 01/2012-12/2014 EHR data from a stratified sample of Medicare patients aged 65+ years to adjudicate a reference-standard to develop an algorithm for identifying patients with PSE. Patient sampling strata included those with: A) epilepsy-related claims diagnosis (n = 534 [all]); B) no diagnosis but neurologist visit (n = 500 [randomly sampled from 4346]); C) all others (n = 500 [randomly sampled from 16,065]). We reconstructed the full sample using inverse probability sampling weights; then used half to derive algorithms and assess performance, and the remainder to confirm performance. We evaluated predictive performance across several measures, e.g., specificity, sensitivity, negative and positive predictive values (NPV, PPV). We selected our best performing algorithms based on the greatest specificity and sensitivity.

RESULTS

Of 20,943 patients in the reconstructed sample, 13.6% of patients with epilepsy had reference-standard PSE diagnosis, which represents a 3-year overall prevalence of 0.28% or 28/10,000, and a prevalence within the subpopulation with stroke of 3%. The best algorithm included three conditions: (a) at least one cerebrovascular claim AND one epilepsy-specific anticonvulsant OR (b) at least one cerebrovascular claim AND one electroencephalography claim (specificity 100.0% [95% CI 99.9%-100.0%], NPV 98.8% [98.6%-99.0%], sensitivity 20.6% [95% CI 14.6%-27.9%], PPV 86.5% [95% CI 71.2%-95.5%]).

CONCLUSION

Medicare claims can identify elderly Medicare beneficiaries with PSE with high accuracy. Future epidemiological surveillance of epilepsy could incorporate similar algorithms to accurately identify epilepsy by varying etiologies.

Antiepileptic drug treatment after an unprovoked first seizure: A decision analysis

OBJECTIVE

To compare the expected quality-adjusted life-years (QALYs) in adult patients undergoing immediate vs deferred antiepileptic drug (AED) treatment after a first unprovoked seizure.

METHODS

We constructed a simulated clinical trial (Markov decision model) to compare immediate vs deferred AED treatment after a first unprovoked seizure in adults. Three base cases were considered, representing patients with varying degrees of seizure recurrence risk and effect of seizures on quality of life (QOL). Cohort simulation was performed to determine which treatment strategy would maximize the patient's expected QALYs. Sensitivity analyses were guided by clinical data to define decision thresholds across plausible measurement ranges, including seizure recurrence rate, effect of seizure recurrence on QOL, and efficacy of AEDs.

RESULTS

For patients with a moderate risk of recurrent seizures (52.0% over 10 years after first seizure), immediate AED treatment maximized QALYs compared to deferred treatment. Sensitivity analyses showed that for the preferred choice to change to deferred AED treatment, key clinical measures needed to reach implausible values were 10-year seizure recurrence rate ≤38.0%, QOL reduction with recurrent seizures ≤0.06, and efficacy of AEDs on lowering seizure recurrence rate ≤16.3%.

CONCLUSION

Our model determined that immediate AED treatment is preferable to deferred treatment in adult first-seizure patients over a wide and clinically relevant range of variables. Furthermore, our analysis suggests that the 10-year seizure recurrence rate that justifies AED treatment (38.0%) is substantially lower than the 60% threshold used in the current definition of epilepsy.

Accuracy of claims-based algorithms for epilepsy research: Revealing the unseen performance of claims-based studies

OBJECTIVE

To evaluate published algorithms for the identification of epilepsy cases in medical claims data using a unique linked dataset with both clinical and claims data.

METHODS

Using data from a large, regional health delivery system, we identified all patients contributing biologic samples to the health system's Biobank (n = 36K). We identified all subjects with at least one diagnosis potentially consistent with epilepsy, for example, epilepsy, convulsions, syncope, or collapse, between 2014 and 2015, or who were seen at the epilepsy clinic (n = 1,217), plus a random sample of subjects with neither claims nor clinic visits (n = 435); we then performed a medical chart review in a random subsample of 1,377 to assess the epilepsy diagnosis status. Using the chart review as the reference standard, we evaluated the test characteristics of six published algorithms.

RESULTS

The best-performing algorithm used diagnostic and prescription drug data (sensitivity = 70%, 95% confidence interval [CI] 66-73%; specificity = 77%, 95% CI 73-81%; and area under the curve [AUC] = 0.73, 95%CI 0.71-0.76) when applied to patients age 18 years or older. Restricting the sample to adults aged 18-64 years resulted in a mild improvement in accuracy (AUC = 0.75,95%CI 0.73-0.78). Adding information about current antiepileptic drug use to the algorithm increased test performance (AUC = 0.78, 95%CI 0.76-0.80). Other algorithms varied in their included data types and performed worse.

SIGNIFICANCE

Current approaches for identifying patients with epilepsy in insurance claims have important limitations when applied to the general population. Approaches incorporating a range of information, for example, diagnoses, treatments, and site of care/specialty of physician, improve the performance of identification and could be useful in epilepsy studies using large datasets.

cEEG electrode-related pressure ulcers in acutely hospitalized patients

BACKGROUND

Pressure ulcers resulting from continuous EEG (cEEG) monitoring in hospitalized patients have gained attention as a preventable medical complication. We measured their incidence and risk factors.

METHODS

We performed an observational investigation of cEEG-electrode-related pressure ulcers (EERPU) among acutely ill patients over a 22-month period. Variables analyzed included age, sex, monitoring duration, hospital location, application methods, vasopressor usage, nutritional status, skin allergies, fever, and presence/severity of EERPU. We examined risk for pressure ulcers vs monitoring duration using Kaplan-Meyer survival analysis, and performed multivariate risk assessment using Cox proportional hazard model.

RESULTS

Among 1,519 patients, EERPU occurred in 118 (7.8%). Most (n = 109, 92.3%) consisted of hyperemia only without skin breakdown. A major predictor was monitoring duration, with 3-, 5-, and 10-day risks of 16%, 32%, and 60%, respectively. Risk factors included older age (mean age 60.65 vs 50.3, p < 0.01), care in an intensive care unit (9.37% vs 5.32%, p < 0.01), lack of a head wrap (8.31% vs 27.3%, p = 0.02), use of vasopressors (16.7% vs 9.64%, p < 0.01), enteral feeding (11.7% vs 5.45%, p = 0.04), and fever (18.4% vs 9.3%, p < 0.01). Elderly patients (71-80 years) were at higher risk (hazard ratio 6.84 [1.95-24], p < 0.01), even after accounting for monitoring time and other pertinent variables in multivariate analysis.

CONCLUSIONS

EERPU are uncommon and generally mild. Elderly patients and those with more severe illness have higher risk of developing EERPU, and the risk increases as a function of monitoring duration.

Burden of illness for super-refractory status epilepticus patients

OBJECTIVE

To provide an estimate of the annual number of super-refractory status epilepticus (SRSE) cases in the US and to evaluate utilization of hospital resources by these patients.

METHODS

The Premier Hospital Database was utilized to estimate the number of SRSE cases based on hospital discharges during 2012. Discharges were classified as SRSE cases based on an algorithm using seizure-related International Classification of Diseases-9 (ICD-9) codes, Intensive Care Unit (ICU) length of stay (LOS), and treatment protocols (e.g. benzodiazepines, anti-epileptic drugs (AEDs), and ventilator use). Secondary analyses were conducted using more restrictive algorithms for SRSE.

RESULTS

A total of 6,325 hospital discharges were classified as SRSE cases from a total of 5,300,000 hospital discharges. Applying a weighting based on hospital characteristics and 2012 US demographics, this projected to an estimated 41,156 cases of SRSE in the US during 2012, an estimated incidence rate of ∼13/100,000 annually for SRSE in the US. Secondary analyses using stricter SRSE algorithms resulted in estimated incidence rates of ∼11/100,000 and 8/100,000 annually. The mean LOS for SRSE hospitalizations was 16.5 days (median =11; interquartile range [IQR] = 6-20), and the mean ICU LOS was 9.3 days (median =6; IQR =3-12). The mean cost of an SRSE hospitalization was $51,247 (median = $33,294; 95% CI = $49,634-$52,861).

LIMITATIONS

The analysis uses ICD-9 diagnostic codes and claims information, and there are inherent limitations in any methodology based on treatment protocol, which created challenges in distinguishing with complete accuracy between SRSE, RSE, and SE on the basis of care patterns in the database.

CONCLUSION

SRSE is associated with high mortality and morbidity, which place a high burden on healthcare resources. Projections based upon the findings of this study suggest an estimated 25,821-41,959 cases of SRSE may occur in the US each year, but more in-depth studies are required.

Feasibility of the collection of patient-reported outcomes in an ambulatory neurology clinic

OBJECTIVE

To determine whether patients could self-report physical and mental health assessments in the waiting room and whether these assessments would be associated with modified Rankin Scale (mRS) and Quality of Life in Epilepsy (QOLIE-10) scores.

METHODS

We offered iPad-based surveys to consecutive adult neurology patients at check-in to collect patient-reported outcome measures (PROMs). We collected demographic and clinical data on 6,075 patients through survey or administrative claims and PROMs from participating patients. We compared demographic characteristics of participants and nonparticipants and tested associations between physical and mental health scores and mRS and QOLIE-10.

RESULTS

Of 6,075 patients seen by neurologists during the study period, 2,992 (49.3%) participated in the survey. Compared to nonparticipating patients, participating patients more often were privately insured (53.5% vs 42.7%, p < 0.01), married (51.5% vs 47.9%, p < 0.01), and seen in general neurology (nonsubspecialty) clinics (53.1% vs 46.6%, p < 0.01) and more likely to report English as their preferred language (50.1% vs 38.4%, p < 0.01). Participating patients had a mean physical health T score of 28.7 (SD 15) and mental health T score of 33 (SD 15), which were 3 and 2 SD worse than the average for the US general population, respectively. Mean T scores in every category of the mRS were different from every other category (n = 232, p < 0.01). Patient Reported Outcomes Measurement Information System-10 T scores were linearly associated with QOLIE-10 scores (n = 202, p < 0.01) CONCLUSIONS: Systematic digital collection of PROMs is feasible. Differences among survey participants and nonparticipants highlight the need to develop multilingual measurement tools that may improve collection from vulnerable populations.

Anterior temporal lobectomy for older adults with mesial temporal sclerosis

OBJECTIVE

To compare postoperative seizure-free survival between older and younger adults.

METHODS

A retrospective cohort of 107 temporal lobe epilepsy patients with a diagnosis of mesial temporal sclerosis (MTS) received anterior temporal lobectomy (ATL) between 1993 and 2014. We divided the lower three quartiles (younger) and top quartile (older, all 47+ years) of patients, then reviewed patient registry and electronic medical records to determine time to first self-reported seizure after ATL, the primary outcome (mean=3.5years of follow-up, SD=3.6). We also assessed Engel classifications, intraoperative and postoperative treatment complications, and social disability. We used Cox proportional hazard models to assess the association between individual traits and time of seizure recurrence.

RESULTS

During follow-up, 35/107 (32.7%) patients had post-operative seizure(s). After adjustment for potential confounders there were no significant differences in the probability of post-operative seizures between the older and younger groups, though we had limited precision (hazard ratio of 0.67 [0.28-1.59]), (p=0.36). There were more treatment complications and disability in older patients (18% vs. 1.3% for any complications, 84.62% vs. 58.23% for driving disability, and 84.6% vs. 60.7% for work disability, p<0.05).

CONCLUSION

Older patients appear to have more complications after ATL, compared with younger patients. Age, however, does not appear to have a large independent association with seizure recurrence.

Patient perceptions of physician-documented quality care in epilepsy

OBJECTIVE

The aim of this study was to compare physician encounter documentation with patient perceptions of quality of epilepsy care and examine the association between quality and patient assessment of provider communication.

METHODS

We identified 505 adult patients with epilepsy aged 18years or older over a 3-year period in two large academic medical centers. We abstracted individual, clinical, and care measures from 2723 electronic clinical notes written by physicians. We then randomly selected 245 patients for a phone interview. We compared patient perceptions of care with the documented care for several established epilepsy quality measures. We also explored the association of patient's perception of provider communication with provider documentation of key encounter interventions.

RESULTS

There were 88 patients (36%) who completed the interviews. Fifty-seven (24%) refused to participate, and 100 (40%) could not be contacted. Participants and nonparticipants were comparable in their demographic and clinical characteristics; however, participants were more often seen by epilepsy specialists than nonparticipants (75% vs. 61.9%, p<0.01). Quality scores based on patient perceptions differed from those determined by assessing the documentation in the medical record for several quality measures, e.g., documentation of side effects of antiseizure therapy (p=0.05), safety counseling (p<0.01), and counseling for women of childbearing potential with epilepsy (McNemar's p=0.03; intraclass correlation coefficient, ICC=0.07). There was a significant, positive association between patient-reported counseling during the encounter (e.g., personalized safety counseling) and patient-reported scores of provider communication (p=0.05).

CONCLUSIONS

The association between the patient's recollection of counseling during the visit and his/her positive perception of the provider's communication skills highlights the importance of spending time counseling patients about their epilepsy and not just determining if seizures are controlled.

Association between addressing antiseizure drug side effects and patient-reported medication adherence in epilepsy

BACKGROUND AND AIM

Adherence to treatment is a critical component of epilepsy management. This study examines whether addressing antiepileptic drug (AED) side effects at every visit is associated with increased patient-reported medication adherence.

PATIENTS AND METHODS

This study identified 243 adults with epilepsy who were seen at two academic outpatient neurology settings and had at least two visits over a 3-year period. Demographic and clinical characteristics were abstracted. Evidence that AED side effects were addressed was measured through 1) phone interview (patient-reported) and 2) medical records abstraction (physician-documented). Medication adherence was assessed using the validated Morisky Medication Adherence Scale-4. Complete adherence was determined as answering "no" to all questions.

RESULTS

Sixty-two (25%) patients completed the interviews. Participants and nonparticipants were comparable with respect to demographic and clinical characteristics; however, a smaller proportion of participants had a history of drug-resistant epilepsy than nonparticipants (17.7% vs 30.9%, P=0.04). Among the participants, evidence that AED side effects were addressed was present in 48 (77%) medical records and reported by 51 (82%) patients. Twenty-eight (45%) patients reported complete medication adherence. The most common reason for incomplete adherence was missed medication due to forgetfulness (n=31, 91%). There was no association between addressing AED side effects (neither physician-documented nor patient-reported) and complete medication adherence (P=0.22 and 0.20).

DISCUSSION AND CONCLUSION

Among patients with epilepsy, addressing medication side effects at every visit does not appear to increase patient-reported medication adherence.

Association of adherence to epilepsy quality standards with seizure control

OBJECTIVE

We assessed the relationship between adherence to epilepsy quality measures (EQM) and seizure control over 2-3 years in a retrospective cohort study.

METHODS

6150 patients were identified at two large academic medical centers with a primary or secondary diagnosis of epilepsy, were 18-85 years old and seen in outpatient general neurology or epilepsy units between June 2011 and May 2014. Patients were included if: their initial visit was between June 2011 and June 2012, treatment was with ≥1 anti-seizure drug, there was ≥1 visit per year during the timeframe, and seizure frequency was documented at initial and final visits, yielding 162 patients/1055 visits from which socio-demographic, clinical and care quality data were abstracted. Quality care was assessed as (1) percent adherence to up to 8 eligible EQM, and (2) defect-free care (DFC: adherence to all eligible EQM). Seizure control (SC) was defined as ≥50% reduction in average seizures/month between initial and final visits. Chi-square and t-test compared care quality with seizure control. Logistic regression was used to assess the relationships between SC, quality of care and subspecialist involvement.

RESULTS

Care quality, reflected by documentation of seizure frequency, addressing therapeutic interventions, and referral to a comprehensive epilepsy center, all exceeded 80% adherence. Care quality as reflected by documentation of seizure type, etiology or syndrome; assessment of side effects, counseling about epilepsy safety and women's issues, and screening for psychiatric disorders ranged from 40 to 57%. Mean EQM adherence across all applicable measures was associated with greater seizure control (p=0.0098). DFC was low (=8%) and did not covary with seizure control (p=0.55). The SC and non-SC groups only differed on epilepsy etiology (p=0.04). Exploratory analysis showed that mean quality scores are associated with seizure control (OR=4.9 [1.3-18.5], p=0.017) while controlling for the effect of subspecialty involvement as a possible confounding variable.

CONCLUSIONS

Average quality of care but not defect-free care was associated with seizure control in this retrospective cohort.

Quality care in epilepsy: Women's counseling and its association with folic acid prescription or recommendation

OBJECTIVE

This study aimed to determine if annual counseling about contraception and pregnancy in the setting of treatment for epilepsy is associated with increased recommending or prescribing of folate.

METHODS

This is a retrospective cohort study with medical record abstraction. We selected records from 77 women of childbearing age who had two or more visits for epilepsy at a neurology clinic. The assessment included a review of documentation from the first three visits for epilepsy within a 24-month follow-up window. We defined perfect adherence to annual counseling about the impact of epilepsy treatment on contraception or pregnancy as defect-free care for women (DFCW). A recommendation that the patient take over-the-counter folate or a prescription for folate was independently abstracted from the chart at each visit.

RESULTS

The group of patients who received DFCW (N=28, 36.36%) and the group who did not receive DFCW (N=49, 63.63%) were comparable with respect to age, disease duration, baseline history of drug-resistant epilepsy (DRE), presence of concurrent psychiatric disease, epileptologist involvement, number of antiepileptic drugs (AEDs) prescribed, seizure type, and etiology. Twenty (71.4%) patients in the DFCW group and 42 (85.7%) in the non-DFCW group were not recommended or prescribed folic acid (p=0.12).

CONCLUSIONS

Even with annual documentation of counseling about how epilepsy treatment may affect contraception and pregnancy, the "action" of prescribing or recommending folic acid during the ensuing 24months is frequently omitted.

The probability of seizures during EEG monitoring in critically ill adults

OBJECTIVE

To characterize the risk for seizures over time in relation to EEG findings in hospitalized adults undergoing continuous EEG monitoring (cEEG).

METHODS

Retrospective analysis of cEEG data and medical records from 625 consecutive adult inpatients monitored at a tertiary medical center. Using survival analysis methods, we estimated the time-dependent probability that a seizure will occur within the next 72-h, if no seizure has occurred yet, as a function of EEG abnormalities detected so far.

RESULTS

Seizures occurred in 27% (168/625). The first seizure occurred early (<30min of monitoring) in 58% (98/168). In 527 patients without early seizures, 159 (30%) had early epileptiform abnormalities, versus 368 (70%) without. Seizures were eventually detected in 25% of patients with early epileptiform discharges, versus 8% without early discharges. The 72-h risk of seizures declined below 5% if no epileptiform abnormalities were present in the first two hours, whereas 16h of monitoring were required when epileptiform discharges were present. 20% (74/388) of patients without early epileptiform abnormalities later developed them; 23% (17/74) of these ultimately had seizures. Only 4% (12/294) experienced a seizure without preceding epileptiform abnormalities.

CONCLUSIONS

Seizure risk in acute neurological illness decays rapidly, at a rate dependent on abnormalities detected early during monitoring. This study demonstrates that substantial risk stratification is possible based on early EEG abnormalities.

SIGNIFICANCE

These findings have implications for patient-specific determination of the required duration of cEEG monitoring in hospitalized patients.

Spectrogram screening of adult EEGs is sensitive and efficient

OBJECTIVE

Quantitatively evaluate whether screening with compressed spectral arrays (CSAs) is a practical and time-effective protocol for assisting expert review of continuous EEG (cEEG) studies in hospitalized adults.

METHODS

Three neurophysiologists reviewed the reported findings of the first 30 minutes of 118 cEEGs, then used CSA to guide subsequent review ("CSA-guided review" protocol). Reviewers viewed 120 seconds of raw EEG data surrounding suspicious CSA segments. The same neurophysiologists performed independent page-by-page visual interpretation ("conventional review") of all cEEGs. Independent conventional review by 2 additional, more experienced neurophysiologists served as a gold standard. We compared review times and detection rates for seizures and other pathologic patterns relative to conventional review.

RESULTS

A total of 2,092 hours of cEEG data were reviewed. Average times to review 24 hours of cEEG data were 8 (±4) minutes for CSA-guided review vs 38 (±17) minutes for conventional review (p < 0.005). Studies containing seizures required longer review: 10 (±4) minutes for CSA-guided review vs 44 (±20) minutes for conventional review (p < 0.005). CSA-guided review was sensitive for seizures (87.3%), periodic epileptiform discharges (100%), rhythmic delta activity (97.1%), focal slowing (98.7%), generalized slowing (100%), and epileptiform discharges (88.5%).

CONCLUSIONS

CSA-guided review reduces cEEG review time by 78% with minimal loss of sensitivity compared with conventional review.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that screening of cEEG with CSAs efficiently and accurately identifies seizures and other EEG abnormalities as compared with standard cEEG visual interpretation.