Electroconvulsive therapy during a highly contagious respiratory pandemic-A framework during COVID-19.

Roman Schumann, Edward K Silberman, Heidi M Hotin, Sadeq A Quraishi

Abstract read

In one paragraph

Article in Saudi journal of anaesthesia. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Roman SchumannProfessor of Anesthesiology, Professor of Surgery (Sec), Tufts University School of Medicine, Associate Chief of Anesthesia for Research and Development, VA Boston Healthcare System, Department Anesthesiology and Critical Care Medicine, 1400 VFW Parkway, West Roxbury, 800 Washington St, Boston, MA, USA.

Edward K SilbermanProfessor of Psychiatry, Tufts University School of Medicine, Director of Inpatient Services, Tufts Medical Center, Department of Psychiatry, 800 Washington St, Boston, MA, USA.

Heidi M HotinAssistant Professor of Psychiatry, Tufts University School of Medicine, Director Psychiatry ECT Service, Tufts Medical Center, Department of Psychiatry, 800 Washington St, Boston, MA, USA.

Sadeq A QuraishiVisiting Associate Professor of Anesthesiology, Tufts University School of Medicine, Vice-Chair for Research, Director, Tufts Anesthesia Research Center, Tufts Medical Center, Department of Anesthesiology and Perioperative Medicine, 800 Washington St, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Necessary procedures during the COVID-19 pandemic include electroconvulsive therapy (ECT). Providing ECT has been considered an essential service during COVID-19 in the Singapore healthcare system, not least to contribute to disease control within a society in part due to the nature of the ECT patient population. There is limited evidence-based scientific information available regarding a procedural framework for ECT during a respiratory pandemic, when much attention in the healthcare system is focused on different areas of clinical care. This article attempts to describe such a framework for ECT procedures acknowledging limited solid scientific evidence at this time and being mindful of future changes to these suggestions as testing, immunization, and treatment options develop. This approach can be adopted in whole or in part to assist practitioners to protect the patient and themselves during the procedure.

Indexed as

Care teamcognitive aidCOVID-19ECTelectroconvulsive therapy

Identifiers

PMID32934633

DOI10.4103/sja.SJA_455_20

PMCPMC7458008

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-SA

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.