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Record W2066397089 · doi:10.1177/0267659107080826

Point of care hematocrit and hemoglobin in cardiac surgery: a review

2007· review· en· W2066397089 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerfusion · 2007
Typereview
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsSt. John’s Health Sciences CentreNova Scotia Health Authority
Fundersnot available
KeywordsHematocritMedicinePoint-of-care testingCardiac surgeryHemoglobinPoint of careIntensive care medicineIntensive careAnesthesiaEmergency medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

The use of point-of-care blood gas analyzers in cardiac surgery has been on the increase over the past decade. The availability of these analyzers in the operating room and post-operative intensive care units eliminates the time delays to transport samples to the main laboratory and reduces the amount of blood sampled to measure such parameters as electrolytes, blood gases, lactates, glucose and hemoglobin/hematocrit. Point-of-care analyzers also lead to faster and more reliable clinical decisions while the patient is still on the heart lung machine. Point-of-care devices were designed to provide safe, appropriate and consistent care of those patients in need of rapid acid/base balance and electrolyte management in the clinical setting. As a result, clinicians rely on their values to make decisions regarding ventilation, acid/base management, transfusion and glucose management. Therefore, accuracy and reliability are an absolute must for these bedside analyzers in both the cardiac operating room and the post-op intensive care units. Clinicians have a choice of two types of technology to measure hemoglobin/hematocrit during bypass, which subsequently determines their patient's level of hemodilution, as well as their transfusion threshold. All modern point-of-care blood gas analyzers measure hematocrit using a technology called conductivity, while other similar devices measure hemoglobin using a technology called co-oximetry. The two methods are analyzed and compared in this review. The literature indicates that using conductivity to measure hematocrit during and after cardiac surgery could produce inaccurate results when hematocrits are less than 30%, and, therefore, result in unnecessary homologous red cell transfusions in some patients. These inaccuracies are influenced by several factors that are common and unique to cardiopulmonary bypass, and will also be reviewed here. It appears that the only accurate, consistent and reliable method to determine hemodilution and establish transfusion thresholds based on nadir hematocrits during cardiopulmonary bypass, and immediately post cardiac surgery, is with the use of co-oximetry.

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.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.756
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
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 head0.353
Teacher spread0.313 · 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