Evidence map›Paper›PMID 27605236›Full record

ReviewHerzschrittmachertherapie & Elektrophysiologie2016

Detection and discrimination of tachycardia in ICDs manufactured by St. Jude Medical.

Jan Zdarek, Carsten W Israel

Abstract readReview
PubMed Publisher
In one paragraph

Review in Herzschrittmachertherapie & Elektrophysiologie, 2016. 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
0.9field-weighted citation impact, top 21% 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, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
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

2 authors at 1 institution in 1 country.

Jan ZdarekSt. Jude Medical, Helfmann-Park 7, 65760, Eschborn, Germany. jzdarek@sjm.com.
Carsten W IsraelEvangelical Hospital Bielefeld, Bielefeld, Germany.
Evangelisches Krankenhaus Bielefeld · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern implantable cardioverter/defibrillator (ICD) systems offer a multitude of algorithms to optimize performance in sensing and tachycardia detection even in difficult circumstances (e. g., ventricular tachycardia during supraventricular tachycardia, fine ventricular fibrillation with intermittent undersensing), to reliably discriminate sustained ventricular tachyarrhythmia from noise, nonsustained and supraventricular tachyarrhythmia, and to limit shock therapy only to those arrhythmias that definitely need to be treated by a shock. A disadvantage of these multiple algorithms is the complexity of annotated tracings that makes it sometimes difficult to understand why the ICD did what it did. If a tachycardia classification was wrong, it may be thus difficult to find the best way to reprogram the device to avoid another misclassification. This review explains in detail the algorithms used for tachycardia detection, discrimination, and prevention of inappropriate therapy in single- and dual-chamber ICDs manufactured by St. Jude Medical. Knowledge of these features may help to optimize ICD treatment in patients fitted with these devices.

Indexed as

AlgorithmsDefibrillators, ImplantableArtifactsDiagnosis, Computer-AssistedDiscriminant AnalysisElectrocardiographyEquipment DesignEquipment Failure AnalysisEvidence-Based MedicineHumansMedical ErrorsReproducibility of ResultsSensitivity and SpecificityTachycardia, VentricularTherapy, Computer-AssistedTreatment OutcomeImplantable cardioverter-defibrillatorSudden cardiac deathTachyarrhythmia, ventricularTachycardia, supraventricularVentricular fibrillation

Identifiers

PMID27605236
OpenAlexW2519082295

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.