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Record W7124176003 · doi:10.1093/ijnp/pyaf080

Durability of the benefit of vagus nerve stimulation in markedly treatment-resistant major depression: a RECOVER trial report

2025· article· en· W7124176003 on OpenAlexafffund
Charles R Conway, Augustus John Rush, Scott T Aaronson, Mark Bunker, Charles M. Gordon, Mark S. George, Patricio Riva‐Posse, Rebecca M. Allen, Ziad Nahas, Christopher L Kriedt, John Zajecka, David L Dunner, João Quevedo, Yvette I. Sheline, Walter Duffy, Brian J. Mickey, Mary Stedman, Gustavo Alva, Lucian Manu, Quyen Tran, Zorumski Cf, Matthew Macaluso, Michael Banov, Cristina Cusin, Jeffrey I. Bennett, Hunter Brown, J.M. Way, Olivia Shy, Ying-Chieh Lee, Richard Hamish McAllister-Williams, R. W. McIntyre, Harold A. Sackeïm

Bibliographic record

VenueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicVagus Nerve Stimulation Research
Canadian institutionsUniversity of Toronto
FundersCenters for Medicare and Medicaid ServicesLivaNovaAugusta UniversityStony Brook UniversityUniversity of MinnesotaUniversity of South CarolinaRush UniversityUniversity of California, San DiegoCarilion ClinicUniversity of MissouriDairy Farmers of CanadaTexas Tech UniversityOhio State UniversityEmory UniversityMassachusetts General Hospital
KeywordsVagus nerve stimulationVagus nerveStimulationDurabilityPeripheral nerve stimulationMEDLINE

Abstract

fetched live from OpenAlex

IMPORTANCE: Greater levels of treatment resistance in major depressive disorder (MDD) are associated with lower rates of initial benefit and higher rates of relapse (lower durability). OBJECTIVE: Characterize depressive symptoms, function, and quality of life (QoL) over 24 months of adjunctive vagus nerve stimulation (VNS) in participants with markedly treatment-resistant depression. DESIGN: Prospective, open-label, single-arm, long-term extension study (RECOVER) conducted from September 2019 to April 2025. SETTING: Outpatient. PARTICIPANTS: Adults with moderate-severe MDD with ≥ 4 failed antidepressant trials in the current episode, randomized to blinded, adjunctive VNS for 12 months, who subsequently received open-label, adjunctive VNS for 12 additional months (n = 214). INTERVENTIONS: Vagus nerve stimulation and concomitant psychotropic medications and interventional psychiatric modalities (electroconvulsive therapy, transcranial magnetic stimulation, and ketamine/esketamine) were characterized over the 12-month extension. MAIN OUTCOMES AND MEASURES: The durability of benefit achieved at 12 months was assessed at 18 and 24 months for depressive symptoms (3 scales), daily function, QoL, a tripartite composite of all 3 domains, and the Clinical Global Impression-Improvement (CGI-I) scale (overall improvement). Loss of benefit and relapse were assessed, along with the emergence of meaningful benefit in participants without benefit at 12 months. Substantial benefit (at least 50% symptom reduction from baseline; CGI-I of 1 or 2; tripartite measures with at least 2 of 3 subscales evidencing benefit) and meaningful benefit thresholds for symptoms (at least 30% reduction from baseline), function, QoL, CGI-I, and the tripartite measure were set a priori. RESULTS: Most participants with substantial benefit maintained their benefit (18-month median = 78.8%; 24-month median = 79.0% across 5 measures), as did participants with at least meaningful benefit at 12 months (18-month median = 83.1%; 24-month median = 81.3% across 7 measures). Furthermore, many participants with no meaningful benefit at 12 months achieved it at 18 (median = 30.6%) and 24 (median = 37.8%) months. The strong maintenance of benefit was not accounted for by changes in psychotropic medications or interventional psychiatric modalities. CONCLUSIONS AND RELEVANCE: Depressive symptom, daily function, and QoL benefits obtained after 12 months of adjunctive VNS were sustained in about 80% of participants continuing VNS. Approximately 30% with no meaningful benefit at 12 months accrued increased benefit over the subsequent year.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.391
Teacher spread0.351 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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