Evidence map›Paper›PMID 31259023›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2019

Factors Affecting Electroconvulsive Therapy Ictal Outcomes: Duration and Postictal Suppression.

Wendy Marie Ingram, Cody Weston, Wei Dar Lu, Caleb Hodge, S Mark Poler, Fatin Nahi, Sharon Larson

Open access · greenAbstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 3 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Wendy Marie IngramCorresponding author: E-mail address - wingram5@jhu.edu.
Cody WestonJohns Hopkins University, Baltimore, Maryland.
Wei Dar LuGeisinger Health System, Danville, Pennsylvania.
Caleb HodgeGeisinger Health System, Danville, Pennsylvania.
S Mark PolerGeisinger Health System, Danville, Pennsylvania.
Fatin NahiGeisinger Health System, Danville, Pennsylvania.
Sharon LarsonGeisinger Health System, Danville, Pennsylvania.
Geisinger Health System · USJohns Hopkins University · USLankenau Institute for Medical Research · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electroconvulsive therapy (ECT) is an effective and rapid treatment for severe depression, however predictors of therapeutic outcomes remain insufficiently understood. Ictal duration and postictal suppression are two outcomes that may be correlated with patient response, yet patient and treatment variables which may influence these outcomes have not been thoroughly explored. We collected ECT stimulus metrics, EEG parameters, patient demographics, primary diagnosis, and anesthesia type for retrospective ECTs. Univariate and multivariate mixed-effects linear regression models were used to identify variables associated with ictal duration and postictal suppression index. For both outcomes, multivariate models which included all variables resulted in the best fit, reflecting the complex influences of a variety of factors on the ictal response. These results are an important step forward in elucidating patterns in retrospective ECT clinical data which may lead to new clinical knowledge of modifiable factors to optimize ECT treatment outcomes.

Indexed as

outcomes research, clinical epidemiology, population healthprecision medicine;secondary use of EHR data;

Identifiers

PMID31259023
PMCPMC6568129
OpenAlexW2984446569

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.