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P50: Heart and Kidney Transplant and Recovery after Left Ventricular Assist Device and Intermittent Hemodialysis: Systematic Review and Individual-Participant-Data Meta-analysis

2023· article· en· W4380319749 on OpenAlexaff
Adrian daSilva‐deAbreu, Austin Tutor, Christian Faaborg‐Andersen, Abdulaziz Joury, Sapna Desai, Clement Eiswirth, Selim R. Krim, James Wever‐Pinzon, Carl J. Lavie, Héctor O. Ventura

Bibliographic record

VenueASAIO Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineDestination therapyMeta-analysisDialysisInternal medicineVentricular assist deviceHeart failureTransplantationRenal replacement therapyHemodialysisSurgeryCardiology

Abstract

fetched live from OpenAlex

Background: Patients with left ventricular assist devices (LVADs) who require chronic intermittent dialysis (iHD) are considered to have poor prognosis despite paucity of supportive evidence, most of which is limited to case reports and very small single-center cohorts. This systematic review and individual-participant-data meta-analysis aims to study the main outcomes of patients receiving iHD during durable LVAD support, including heart, kidney, and heart-kidney transplantation (HT, KT, HKT, respectively) and mortality. Methods: We retrieved citations from ClinicalTrials.gov, Cochrane, Embase, PubMed, and Web of Science through systematic searches. We selected cohort studies (with n ≥5) of patients who were started on iHD at any point during durable LVAD support, excluding patients who exclusively received continuous renal replacement therapy but no actual iHD. We conducted Kaplan-Meier survival estimations and graphs, and compared mortality data between groups using the Gehan-Breslow-Wilcoxon test. P <.05 was considered statistically significant. We did not pursue inputations for missing data. Results: Six studies with a total of 64 patients met selection criteria. Their median age was 57.5 (46-64.5) years, 49 (76.6%) were men, 46 (86.8%) patients had a HeartMate (HM) 2, whereas 5 (9.4%) had a HM3, and 2 (3.8%) had an HVAD. Twenty-eight (66.7%) patients had LVADs as bridge to HT, and 14 (33.3%) as destination therapy. Only 26 (65%) were reported to have a history of CKD. Patients were initiated on iHD at a median of 18 (7-48) days after LVAD implantation, and remained on iHD for 68 (36-185) days. Eleven (17.2%) patients received HT, and at least 1 additional patient achieved myocardial recovery with LVAD explantation. Four (4.3%) patients became recipients of HKT, including one patient who had recovered enough of their renal function as to stop needing iHD prior to transplantation. Twenty-seven (42.2%) experienced renal recovery. Thirty-one (48.4%) patients died at 103 (64-308) days after initiation of iHD. According to Kaplan-Meier survival calculations, median survival was estimated at 153 (SE 217.5; CI 65-835) days (Figure 1). Survival after initiation of iHD was statistically significantly longer for patients who received HT (mortality: 2 [6.4%] vs 16 [11.6%]; p=.0346; median survival: 1972 [SE 98.8; 799-] days vs 93 [SE 10.3; CI 57-404] days), as evidenced in Figure 2. Survival comparisons between groups stratified based on other outcomes (HKT, renal recovery, composite HKT/renal recovery) did not reach statistical significance. Conclusions: The 18.8% of patients who achieved dual heart and kidney recovery and/or transplantation after being supported with LVAD and iHD experienced a significantly longer median survival. Only one patient experienced dual heart-kidney recovery. Larger contemporary multicenter cohort studies are warranted on this topic.Figure 1. Kaplan-Meier Survival Estimate (for the whole sample)Figure 2. Kaplan-Meier Survival Estimate According to Heart Transplant Status

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.096
GPT teacher head0.282
Teacher spread0.186 · 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 designMeta-analysis
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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