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Record W2266812270 · doi:10.1186/s40634-016-0043-7

White blood cell concentration correlates with increased concentrations of IL‐1ra and improvement in WOMAC pain scores in an open‐label safety study of autologous protein solution

2016· article· en· W2266812270 on OpenAlexaboutno aff
William J. King, Walter van der Weegen, R. van Drumpt, Hans Soons, Krista Toler, Jennifer Woodell‐May

Bibliographic record

VenueJournal of Experimental Orthopaedics · 2016
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersBiomet
KeywordsWOMACOsteoarthritisMedicineWhite blood cellInternal medicineSynovial fluidCytokineWhole bloodUrologyImmunologySurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: There has been debate on which blood components should be included in autologous therapies. Autologous Protein Solution (APS) is a unique blood-derived therapy composed of concentrated white blood cells, platelets, and plasma to contain high concentrations of anti-inflammatory cytokines and anabolic growth factors to potentially address osteoarthritis. The primary aim of the exploratory secondary analysis was to identify characteristics of an Autologous Protein Solution (APS) that may correlate with improved Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores and OMERACT-OARSI responder status after treatment of subjects with an intra-articular injection of APS. METHODS: Eleven subjects were enrolled in a pilot study of a single intra-articular injection of APS in subjects with knee osteoarthritis. Two APS kits were processed per patient. The output of the first APS kit was injected intra-articularly. White blood cell (WBC) and cytokine concentrations were measured from the output of the second APS kit. WOMAC surveys were completed at baseline and at follow up visits. Linear regression analyses were performed on the blood components of APS with subject outcomes. Anderson-Darling analysis was used to determine whether the cytokine concentrations in whole blood and APS had a normal distribution. Either paired t-test analyses or Wilcoxon signed-rank analyses were performed for normal and non-parametrically distributed data, respectively. RESULTS: The WBC concentration in APS was significantly (p < 0.05) and strongly (R(2) > 0.7) correlated with IL-1ra in APS but not significantly correlated with IL-1β. The ratio of IL-1ra to IL-1β in APS was significantly correlated with improved WOMAC pain scores one week and six months post-injection. 85.7 % of subjects whose APS had a IL-1ra:IL-1β ratio greater than 1000 or a WBC count greater than 30 k/μl were OMERACT-OARSI responders six months post-injection. CONCLUSIONS: The correlations between the IL-1ra:IL-1β ratio and WBC concentration in a subject's APS and their WOMAC pain scores and classification as OMERACT-OARSI responders suggest the potential utility of these characteristics as diagnostic markers. Additional studies are ongoing to determine whether APS is safe and effective and to further evaluate the relationship between APS composition and clinical outcomes. TRIAL REGISTRATION: ( NCT01773226 ).

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.268
Teacher spread0.254 · 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 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

Citations42
Published2016
Admission routes1
Has abstractyes

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