Evidence map›Paper›PMID 36217080›Full record

ArticleAdvances in experimental medicine and biology2022

Treatment of Cheyne-Stokes Respiration in Heart Failure with Adaptive Servo-Ventilation: An Integrative Model.

Wen-Hsin Hu, Michael C K Khoo

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Advances in experimental medicine and biology, 2022. 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, top 52% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Wen-Hsin HuDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.
Michael C K KhooDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA. khoo@usc.edu.
University of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SERVE-HF (Treatment of Predominant Central Sleep Apnea by Adaptive Servo Ventilation in Patients with Heart Failure) multicenter trial found a small but significant increase in all-cause and cardiovascular mortality in patients assigned to adaptive servo-ventilation (ASV) versus guideline-based medical treatment. To better understand the physiological underpinnings of this clinical outcome, we employ an integrative computer model to simulate congestive heart failure with Cheyne-Stokes respiration (CHF-CSR) in subjects with a broad spectrum of underlying pathogenetic mechanisms, as well as to determine the in silico changes in cardiopulmonary and autonomic physiology resulting from ASV. Our simulation results demonstrate that while the elimination of CSR through ASV can partially restore cardiorespiratory and autonomic physiology toward normality in the vast majority of CHF phenotypes, the degree of restoration can be highly variable, depending on the combination of CHF mechanisms in play. The group with the lowest left ventricular ejection fraction (LVEF) appears to be most vulnerable to the potentially adverse effects of ASV, but the level of pulmonary capillary wedge pressure (PCWP) plays an important role in determining the nature of these effects.

Indexed as

Heart FailureSleep Apnea, CentralCheyne-Stokes RespirationHumansRespiration, ArtificialStroke VolumeTreatment OutcomeVentricular Function, LeftAdaptive Servo-VentilationAutonomic RegulationCheyne-Stokes RespirationComputer SimulationHeart FailureIntegrative PhysiologyMathematical ModelSleep Apnea

Identifiers

PMID36217080
OpenAlexW4304481453

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.