Serotonin reuptake inhibitors and mortality in epilepsy: A linked primary‐care cohort study

Josephson, Colin B.; González-Izquierdo, Arturo; Denaxas, Spiros; Sajobi, Tolulope T.; Engbers, Jordan D. T.; Patten, Scott B.; Wiebe, Samuel

doi:10.1111/epi.13904

Cited by 8 publications

(8 citation statements)

References 32 publications

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“…with epilepsy, but we cannot exclude a protective effect of SSRIs given the limited number of exposed. 27 We did neither observe an increased nor reduced SUDEP risk with concomitant use of neuroleptics or beta blockers. In our study, statin use was associated with a 66% reduced SUDEP risk even after adjusting for GTCS frequency.…”

Section: A C C E P T E Dcontrasting

confidence: 62%

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Pharmacologic treatment and SUDEP risk

et al. 2020

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Objective: We conducted a nationwide case-control study in Sweden to test the hypothesis that antiepileptic drugs (AEDs), mono- polytherapy, adherence, antidepressants, neuroleptics, beta-blockers, and statins are associated with sudden unexpected death in epilepsy (SUDEP) risk.Methods: Included were 255 SUDEP cases and 1148 matched controls. Information on clinical factors and medications came from medical records and the National Patient and Prescription Registers. The association between SUDEP and medications was assessed by odds ratios (OR) with 95% confidence intervals (CI) adjusted for potential risk factors including type of epilepsy, living conditions, co-morbidity and frequency of generalized tonic-clonic seizures (GTCS).Results: Polytherapy, especially taking three or more AEDs was associated with a substantially reduced risk of SUDEP (OR 0.31, 95% CI: 0.14-0.67). Combinations including lamotrigine (OR 0.55, 95% CI 0.31-0.97), valproic acid (OR 0.53, 95% CI: 0.29-0.98) and levetiracetam (OR 0.49, 95% CI 0.27-0.90) were associated with reduced risk. No specific AED was associated with increased risk. Regarding monotherapy, although limited numbers, the lowest SUDEP risk was seen in users of levetiracetam (0.10, 95% CI: 0.02-0.61). Having non-adherence mentioned in the medical record was associated with an OR of 2.75 (95% CI 1.58-4.78). Statin use was associated with a reduced SUDEP risk (OR 0.34, 95% CI: 0.11-0.99) but not SSRI use.Interpretation: These results provide support for the importance of medication adherence and intensified AED treatment for patients with poorly controlled GTCS in the efforts to reduce SUDEP risks and suggest that comedication with statins may reduce risks.

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Section: A C C E P T E Dcontrasting

confidence: 62%

“…This negative finding is in line with a study that did not find evidence that SSRIs protected against all-cause mortality in a large population-based cohort study of people with epilepsy, but we cannot exclude a protective effect of SSRIs given the limited number of exposed. 27 …”

Section: Discussionmentioning

confidence: 99%

Pharmacologic treatment and SUDEP risk

et al. 2020

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“…Serotonin reuptake inhibitors can display proconvulsant properties only at toxic doses [45]. In one study, SRI use in patients with epilepsy neither protected nor elevated seizure-related mortality [46]. However, seizure-related deaths were a broad category, not limited to SUDEP.…”

Section: Discussionmentioning

confidence: 99%

The association of serotonin reuptake inhibitors and benzodiazepines with ictal central apnea

Lacuey

Martins

Vilella³

et al. 2019

Epilepsy & Behavior

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Objective: Ictal (ICA) and postconvulsive central apnea (PCCA) have been implicated in sudden unexpected death in epilepsy (SUDEP) pathomechanisms. Previous studies suggest that serotonin reuptake inhibitors (SRIs) and benzodiazepines (BZDs) may influence breathing. The aim of this study was to investigate if chronic use of these drugs alters central apnea occurrence in patients with epilepsy. Methods: Patients with epilepsy admitted to epilepsy monitoring units (EMUs) in nine centers participating in a SUDEP study were consented. Polygraphic physiological parameters were analyzed, including video-electroencephalography (VEEG), thoracoabdominal excursions, and pulse oximetry. Outpatient medication details were collected. Patients and seizures were divided into SRI, BZD, and control (no SRI or BZD) groups. Ictal central apnea and PCCA, hypoxemia, and electroclinical features were assessed for each group. Results: Four hundred and seventy-six seizures were analyzed (204 patients). The relative risk (RR) for ICA in the SRI group was half that of the control group (p = 0.02). In the BZD group, ICA duration was significantly shorter than in the control group (p = 0.02), as was postictal generalized EEG suppression (PGES) duration (p = 0.021). Both SRI and BZD groups were associated with smaller seizure-associated oxygen desaturation (p = 0.009; p ≪ 0.001). Neither presence nor duration of PCCA was significantly associated with SRI or BZD (p ≫ 0.05). Conclusions: Seizures in patients taking SRIs have lower occurrence of ICA, and patients on chronic treatment with BZDs have shorter ICA and PGES durations. Preventing or shortening ICA duration by using SRIs and/or BZD in patients with epilepsy may play a possible role in SUDEP risk reduction.

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“…Analyses from validated epidemiological data have yielded remarkable insights into the incidence 92,93 and prevalence 92,94 of epilepsy, the comorbid profile of epilepsy, 94 the bidirectionality of depression and epilepsy, 95,96 the association between epilepsy and autism, 97,98 and debunking the spurious putative link between AED use and suicide. 99,100 Overall mortality 101,102 and SUDEP 101,103 have been studied with large quantities of EHR and administrative data. Initial endeavors at applying machine learning to big data for the purposes of predicting epilepsy outcomes appear promising.…”

Section: Data Sources and Validationmentioning

confidence: 99%

Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy

et al. 2020

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Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches [Correction added on Aug 30, 2020, after first online publication: Affiliation of author "Satya S. Sahoo" was changed and the rest of the affiliations were renumbered accordingly.] 1870 | LHATOO eT AL. 1 | INTRODUCTION Big data is an intuitive, colloquially used term 1-first in business, and latterly in science and health care. MetaGroup's 2014 definition describes big data as high-volume, high-velocity, and high-variety information assets that demand costeffective, innovative forms of information processing for enhanced insight and decision-making. In addition to these "3 V's," 2 the fourth "V" of data veracity is particularly pertinent, because suspect data produce suspect conclusions (Figure 1). In an era of unprecedented collaboration and resource pooling, big data's promise is both inviting and challenging, especially in epilepsy due to its inherent heterogeneity and the vast array of scientific disciplines it involves. This review examines big data aspects specific to epilepsy and describes the current state of the art as well as future directions. 2 | THE MEANING OF BIG DATA In epilepsy, a plethora of disparate data drive variety (phenotype, genotype, video-electroencephalographic [EEG], extracranial and intracranial physiological signal, structural to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data.

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Serotonin reuptake inhibitors and mortality in epilepsy: A linked primary‐care cohort study

Cited by 8 publications

References 32 publications

Pharmacologic treatment and SUDEP risk

Pharmacologic treatment and SUDEP risk

The association of serotonin reuptake inhibitors and benzodiazepines with ictal central apnea

Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy

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