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Central venous oxygen saturation and thoracic admittance during dialysis: New approaches to hemodynamic monitoring

2008· article· en· W2110086471 on OpenAlexvenueno aff
Joakim Cordtz, Bo Olde, Kristian Solem, S. Ladefoged

Bibliographic record

VenueHemodialysis International · 2008
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsnot available
FundersLEO PharmaAugustinus FondenFondation pour la Recherche Médicale
KeywordsMedicineHemodialysisBlood volumeCardiologyHemodynamicsCardiac outputCentral venous pressurePathophysiologyDialysisInternal medicineAnesthesiaOxygen saturationBlood pressureOxygenHeart rate

Abstract

fetched live from OpenAlex

Intradialytic hypotension (IDH) is one of the most important short-term complications to hemodialysis (HD). Inadequate cardiac filling due to a reduction in the central blood volume is believed to be a major etiological factor. The aim of this study was to evaluate whether these pathophysiologic events are reflected in the central venous oxygen saturation (ScO(2)) and thoracic admittance (TA) during dialysis. Twenty ambulatory HD patients, 11 hypotension prone (HP) and 9 hypotension resistant, with central vascular access, were monitored during 3 HD sessions each. ScO(2), TA, finger blood pressure (BP), and relative change in blood volume (DeltaBV) were measured and sampled continuously. The relative TA decrease and DeltaBV were both largest in the HP group (p<0.05 for both), whereas ScO(2) decreased only in HP patients (p<0.001). Baseline TA was lower in the HP group (p<0.01). Changes in ScO(2) and TA correlated much closer than did changes in ScO(2) and DeltaBV (r=0.43 and 0.18, respectively). Our results suggest that an intradialytic decrease in cardiac output, as reflected by a fall in ScO(2), is a common feature to HD patients prone to IDH. In patients using a central vascular access, ScO(2) and TA measurements may be more specific to the pathophysiologic events preceding IDH than DeltaBV-the current standard monitoring method.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.063
GPT teacher head0.282
Teacher spread0.219 · 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 designObservational
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

Citations23
Published2008
Admission routes1
Has abstractyes

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