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Record W4400650651 · doi:10.2196/54609

Evaluation of the Feasibility of Transfusing Leukocyte Depletion Filter–Processed Intraoperative Cell Salvage Blood in Metastatic Spine Tumor Surgery: Protocol for a Non–Randomized Study

2024· article· en· W4400650651 on OpenAlexvenueno aff
Naresh Kumar, Si Jian Hui, Renick Lee, Sahil Athia, Joel Yong Hao Tan, Jiong Hao Tan

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePreprintProtocol (science)SurgeryRandomized controlled trialBlood lossAlternative medicinePathologyWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Metastatic spine tumor surgery (MSTS) is often complex and extensive leading to significant blood loss. Allogeneic blood transfusion (ABT) is the mainstay of blood replenishment but with immune-mediated postoperative complications. Alternative blood management techniques (salvaged blood transfusion [SBT]) allow us to overcome such complications. Despite widespread use of intraoperative cell salvage (IOCS) in oncological and nononcological surgical procedures, surgeons remain reluctant to use IOCS in MSTS. OBJECTIVE: This study aims to analyze safety of IOCS-leukocyte depletion filter (LDF)-processed blood transfusion for patients undergoing MSTS by assessing clinical outcomes-disease progression: tumor progression and overall survival. This study evaluates whether reinfusion of IOCS-LDF-processed blood reduces ABT rates in patients undergoing MSTS by sorting patients undergoing MSTS who require ABT into patients who consent to receive or not receive SBT. METHODS: We aim to recruit a minimum of 90 patients-30 patients for SBT, 30 patients for ABT, and 30 patients with no blood transfusion. SBT and ABT form the 2 experimental arms, whereas no blood transfusion forms the control cohort. Available patient data will be reviewed to determine tumor burden secondary to metastasis and postoperative survival and disease progression, improvement in pain, and neurological and ambulatory status. Data collected will be studied postoperatively at 3, 6, 12, 24, 36, and 48 months or until demise, whichever occurs first. Outcomes of the experimental groups will be compared with those of the control group. Outcomes will be analyzed using 1-way ANOVA and Fisher exact test. The Kaplan-Meier curve and a log-rank test will be used to study overall survival. A multivariate and competing risk analysis will be used to study the association between blood transfusion type and tumor progression. All statistical analyses will be done using Stata Special Edition 14.0 (StataCorp LP). RESULTS: This is the largest clinical study on use of IOCS in MSTS from various primary malignancies to date. It will provide significant clinical evidence regarding the safety and applicability of IOCS in MSTS. It will help reduce use of ABT, improving overall blood management of patients undergoing MSTS. A limitation of this study is that not all patients undergoing MSTS will survive for the follow-up period (4 years), theoretically leading to underreporting of disease progression. Study commenced in 2016 and patient recruitment continued till 2019. As of September 2019, we have collected operative data on 140 patients. However, the 2-year outcomes of about 40.0% (56/140) of patients are in the process of collection. The study is aimed to be published in the years 2023-2024. CONCLUSIONS: Results will be disseminated via peer-reviewed publications, paving the way for future studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54609.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.029
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.029
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.022
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0220.004

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 head0.386
GPT teacher head0.563
Teacher spread0.177 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreProtocol

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

Citations1
Published2024
Admission routes1
Has abstractyes

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