A double-hit: End-stage renal disease patients suffer worse outcomes in intracerebral hemorrhage.

BACKGROUND: Intracerebral hemorrhage (ICH) carries significant morbidity and mortality. Previous single-center retrospective analysis suggests that end-stage renal disease (ESRD) is a risk factor for severe ICH and worse outcomes. This investigation aims to examine the impact of ESRD on ICH severity, complications, and outcomes using a multicenter national database. METHODS: The International Classification of Disease, Ninth and Tenth Revision Clinical Modification codes were used to query the National Inpatient Sample for patients with ICH and ESRD between 2010 and 2019. Primary endpoints were the functional outcome, length of stay (LOS), and in-hospital mortality. Multivariate variable regression models and a propensity-score matched analysis were established to analyze patient outcomes associated with baseline patient characteristics. RESULTS: We identified 211,266 patients with ICH, and among them, 7,864 (3.77%) patients had a concurrent diagnosis of ESRD. Patients with ESRD were younger (60.85 vs. 67.64, P < 0.01) and demonstrated increased ICH severity (0.78 vs. 0.77, P < 0.01). ESRD patients experienced higher rates of sepsis (15.9% vs. 6.15%, P < 0.01), acute myocardial infarction (8.05% vs. 3.65%, P < 0.01), and cardiac arrest (5.94% vs. 2.4%, P < 0.01). In addition, ESRD predicted poor discharge disposition (odds ratio [OR]: 2.385, 95% confidence interval [CI]: 2.227-2.555, P < 0.01), longer hospital LOS (OR: 1.629, 95% CI: 1.553-1.709, P < 0.01), and in-hospital mortality (OR: 2.786, 95% CI: 2.647-2.932, P < 0.01). CONCLUSIONS: This study utilizes a multicenter database to analyze the effect of ESRD on ICH outcomes. ESRD is a significant predictor of poor functional outcomes, in-hospital mortality, and prolonged stay in the ICH population.

Implementer report: ICD-10 code F44.5 review for functional seizure disorder.

OBJECTIVE: The study aimed to measure the validity of International Classification of Diseases, 10th Edition (ICD-10) code F44.5 for functional seizure disorder (FSD) in the Veterans Affairs Connecticut Healthcare System electronic health record (VA EHR). METHODS: The study used an informatics search tool, a natural language processing algorithm and a chart review to validate FSD coding. RESULTS: The positive predictive value (PPV) for code F44.5 was calculated to be 44%. DISCUSSION: ICD-10 introduced a specific code for FSD to improve coding validity. However, results revealed a meager (44%) PPV for code F44.5. Evaluation of the low diagnostic precision of FSD identified inconsistencies in the ICD-10 and VA EHR systems. CONCLUSION: Information system improvements may increase the precision of diagnostic coding by clinicians. Specifically, the EHR problem list should include commonly used diagnostic codes and an appropriately curated ICD-10 term list for 'seizure disorder,' and a single ICD code for FSD should be classified under neurology and psychiatry.

Clinical Reasoning: An Older Woman With Headaches and Lethargy After a Fall.

In this case, a 77-year-old woman presented with generalized weakness, difficulty ambulating, lethargy, loss of appetite, and headaches after a mechanical fall. This case discusses the management of acute neurologic emergencies such as subdural hematoma, status epilepticus, and bacterial meningitis. Potential etiologies for stroke and CNS infection are highlighted. Readers are led through the diagnostic approach to a patient presenting with a complex array of neurologic symptoms causing rapid clinical decompensation.

Significant increase in mortality and risk of acute ischemic stroke in infective endocarditis patients with subarachnoid hemorrhage secondary to mycotic aneurysms.

Infective Endocarditis (IE) patients are known to have a variety of complications with one of the rarest, but serious being cerebral mycotic aneurysm, which can result in subarachnoid hemorrhage (SAH). Using the National In-Patient Sample database, we sought to determine the rate of acute ischemic stroke (AIS) and outcomes in IE- patients with and without SAH. In total, we identified 82,844 IE-patients from 2010 to 2016, of which 641 had a concurrent diagnosis of SAH. IE patients with SAH had a more complicated course, higher mortality rate (OR 4.65 CI 95% 3.9-5.5, P < 0.001), and worse outcomes. This patient population also had a significantly higher rate of AIS (OR 6.3 CI 95% 5.4-7.4, P < 0.001). Overall, 41.5% of IE-patients with SAH had AIS during their hospitalization as compared to 10.1% of IE only patients. IE-patients with SAH were more likely to undergo endovascular treatment (3.6%) with 0.8% of the IE patients with AIS undergoing mechanical thrombectomy. While IE-patients are at risk for various complications, our study suggests a significant increase in the mortality and risk of AIS in those with SAH.

Aneurysmal Subarachnoid Hemorrhage and Cardiac Related Fatality: Who Dies and Why?

Medical complications are a notable source of in-hospital death following aneurysmal subarachnoid hemorrhage (aSAH). However, there is a paucity of literature examining medical complications on a national scale. This study uses a national dataset to analyze the incidence rates, case fatality rates, and risk factors for in-hospital complications and mortality following aSAH. We found that the most common complications in aSAH patients (N = 170, 869) were hydrocephalus (29.3%) and hyponatremia (17.3%). Cardiac arrest was the most common cardiac complication (3.2%) and was associated with the highest case fatality rate overall (82%). Patients with cardiac arrest also had the highest odds of in-hospital mortality [odds ratio (OR), 22.92; 95% confidence interval (CI), 19.24-27.30; P < 0.0001], followed by patients with cardiogenic shock (OR, 2.96; 95% CI, 2.146-4.07; P < 0.0001). Advanced age and National Inpatient Sample-SAH Severity Score were found to be associated with an increased risk of in-hospital mortality (OR, 1.03; 95% CI, 1.03-1.03; P < 0.0001 and OR, 1.70; 95% CI, 1.65-1.75; P < 0.0001, respectively). Renal and cardiac complications are significant factors to consider in aSAH management, with cardiac arrest being the strongest indicator of case fatality and in-hospital mortality. Further research is needed to characterize factors that have contributed to the decreasing trend in case fatality rates identified for certain complications.

Suicide and Seizures: A National Cohort Study in Veterans.

OBJECTIVE: The increased rate of suicide associated with epilepsy has been described, but no studies have reported the rates of suicide and suicide-related behavior (SRB) associated with psychogenic nonepileptic seizures (PNESs). METHODS: This retrospective cohort study analyzed data from October 2002 to October 2017 within Veterans Health Administration services. Of 801,734 veterans, 0.09% had PNES, 1.37% had epilepsy, and 98.5% had no documented seizures. Veterans coded for completed suicide, suicide attempts, and suicidal ideation were identified from electronic health records. The primary measure was the suicide-specific standardized mortality ratio (SMR) based on the number of suicide deaths and CDC national suicide mortality database. A Poisson regression was used to calculate the relative risk (RR) of suicide across groups. RESULTS: A total of 1,870 veterans (mean age [SD] 33.76 [7.81] years) completed suicide. Veterans with PNES (RR = 1.75, 95% confidence interval [CI] 0.84-4.24) and veterans with epilepsy (RR = 2.19, 95% CI 2.10-2.28) had a higher risk of suicide compared with the general veteran population. Veterans with PNES or epilepsy had a higher risk of suicide and SRB if they had comorbid alcohol abuse, illicit drug abuse, major depression, posttraumatic stress disorder, and use of psychotropic medications. Conversely, those who were married or attained higher education were at a decreased risk. The SMR for completed suicide for PNES, epilepsy, and the comparison group was 2.65 (95% CI 1.95-5.52), 2.04 (95% CI 1.60-2.55), and 0.70 (95% CI 0.67-0.74), respectively. CONCLUSIONS: Veterans with seizures (both psychogenic and epileptic) are at a greater risk of death by suicide and SRB than the comparison group. These findings suggest that although the pathophysiology of PNES and epilepsy is different, the negative impact of seizures is evident in the psychosocial outcomes in both groups.

Managing Functional Neurological Disorders: Protocol of a Cohort Study on Psychogenic Non-Epileptic Seizures Study.

BACKGROUND: Functional neurological disorders (FNDs) are neurological symptoms that cannot be explained by an underlying neurological lesion or other medical illness and that do not have clear neuropathological correlates. Psychogenic non-epileptic seizures (PNES) are a common and highly disabling form of FND, characterized by paroxysmal episodes of involuntary movements and altered consciousness that can appear clinically similar to epileptic seizures. PNES are unique among FNDs in that they are diagnosed by video electroencephalographic (VEEG), a well-established biomarker for the disorder. The course of illness and response to treatment of PNES remain controversial. This study aims to describe the epidemiology of PNES in the Department of Veterans Affairs Healthcare System (VA), evaluate outcomes of veterans offered different treatments, and compare models of care for PNES. METHODS: This electronic health record (EHR) cohort study utilizes an informatics search tool and a natural language processing algorithm to identify cases of PNES nationally. We will use VA inpatient, outpatient, pharmacy, and chart abstraction data across all 170 medical centers to identify cases in fiscal years 2002-2018. Outcome measurements such as seizure frequency, emergency room visits, hospital admissions, suicide-related behavior, and the utilization of psychotherapy prior to and after PNES diagnosis will be used to assess the effectiveness of models of care. DISCUSSION: This study will describe the risk factors and course of treatment of a large cohort of people with PNES. Since PNES are cared for by a variety of different modalities, treatment orientations, and models of care, effectiveness outcomes such as seizure outcomes and utilization of emergency visits for seizures will be assessed. Outcome measurements such as seizure frequency, emergency room visits, hospital admissions, suicide-related behavior, and psychotherapy prior to and after PNES diagnosis will be used to assess the effectiveness of models of care.