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Record W3048518472 · doi:10.1002/ehf2.12930

Prediction of Heart Failure Hospitalizations Based on the Direct Measurement of Intrathoracic Impedance

2020· article· en· W3048518472 on OpenAlexaff
Michael R. Zile, Vinod Sharma, Catalin F. Baicu, Jodi Koehler, Anthony Tang

Bibliographic record

VenueESC Heart Failure · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsWestern University
FundersMedtronic
KeywordsElectrical impedanceMedicineImplantCardiologyInternal medicineBioelectrical impedance analysisBiomedical engineeringSurgeryBody mass indexElectrical engineering

Abstract

fetched live from OpenAlex

AIMS: OptiVol fluid index was developed as a transthoracic impedance-based indicator of short-term risk for heart failure hospitalization (HFH). OptiVol is calculated as the accumulating difference between daily impedance (measured impedance) and long-term average impedance (reference impedance). Measured impedance alone was thought to have limited prognostic utility; however, measured impedance has the advantage of being simple, direct, and possibly additive to OptiVol fluid index in establishing long-term HFH risk. We tested the hypothesis that directly measured impedance has independent prognostic value in predicting long-term HFH risk and that changes in measured impedance result in a change in predicted long-term HFH risk. METHODS AND RESULTS: A retrospective analysis of 1719 patients studied in PARTNERS-HF, FAST, and RAFT studies was performed. Baseline measured impedance was determined using daily values averaged over 1 month, from Month 6 to 7 post implant; change in measured impedance was determined from values averaged over 1 month, from Month 7 to 8 post implant compared with baseline. The predictive value of baseline measured impedance for HFHs was assessed beginning 7 months post implant. The predictive value of a change in measured impedance for a change in HFHs was assessed beginning 8 months post implant. Baseline measured impedance successfully predicted HFHs. For example, 3 year HFH rate for low baseline impedance < 70 Ω was 23%; for high baseline impedance ≥ 70 Ω was 15% (P < 0.001). Changes in measured impedance resulted in changes in predicted HFHs. For example, when a baseline impedance of ≥70 fell during follow-up to <70 Ω, the subsequent HFHs were 15% compared with 4% in patients with measured impedance that remained >70 Ω (P = 0.004). In addition, when baseline measured impedance fell during follow-up by >1%, 2%, or 3%, subsequent HFHs increased to 13%, 17%, or 18%, respectively. Finally, the prognostic value of measured impedance was additive to the prognostic value of the OptiVol fluid index. CONCLUSIONS: Direct measurements of intrathoracic impedance using an implanted device can be used to stratify patients at varying risk of long-term HFH. These direct measurements of impedance have practical clinical appeal because they are simple, continuous, and ambulatory.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.039
GPT teacher head0.265
Teacher spread0.226 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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