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Enregistrement W4206656183 · doi:10.1093/asj/sjab401

The Emperor Has No Platelets: Minimal Effects in an Alopecia Split-Scalp Study Unsurprising as Platelet-Rich Plasma Was Actually Platelet-Poor

2021· article· en· W4206656183 sur OpenAlexaff
Patrick K Yam

Notice bibliographique

RevueAesthetic Surgery Journal · 2021
Typearticle
Langueen
DomaineMedicine
ThématiquePeriodontal Regeneration and Treatments
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMedicinePlateletScalpPlatelet-rich plasmaEmperorSurgeryDermatologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

A recent paper by Dr Gordon Sasaki looked at the effect on alopecia of 2 different platelet concentrations of platelet-rich plasma (PRP) compared to placebo.1 Although improvement was associated with the higher concentration, statistical significance was not reached. As the main variable, and the basis of this study, platelet concentration deserves a closer look. This concentration may be expressed as the platelet increase factor (PIF): PIF = (PRP platelet concentration)/(whole blood platelet concentration). The PIF was reported as 4.5× in this study, obtained from the datasheet provided by the manufacturer of the PRP kits used in Dr Sasaki's study, Eclipse (The Colony, TX), who also sponsored the study. This value is foundational to any conclusions reached. A PIF of 4.5× would equal 1 to 1.5 million platelets/µL, which Dr Sasaki notes is widely believed to be the optimal concentration for favorable results. Indeed, the classic definition of PRP is a minimum of 1 million platelets/µL; conversely, concentrations below whole blood (~200,000 platelets/µL) are termed platelet-poor plasma (PPP).2 Presumably to verify the PRP platelet concentration, Dr Sasaki sent 1 mL from each PRP sample to a local hospital laboratory for Coulter Counter analysis (CCA). He writes, “quantification of platelets … by Coulter Counter in Batches A and B were calculated as 4.5-fold increases over baseline values.” However, a check of this calculation, ie the ratio of CCA PRP platelet concentration to baseline platelet concentrations, shows the PIF was actually only 0.1× to 0.2×, far lower than 4.5× (Table 1). In other words, PPP was used as treatment instead of PRP. Platelet Increase Factor based on Coulter Counter Analysis Values are mean [standard deviation] or number. CCA, Coulter Counter analysis; PIF, platelet increase factor; PRP, platelet-rich plasma. aValues from Table 5 in Sasaki.1 bPIF = (platelet concentration PRP)/(whole blood platelet concentration). Platelet Increase Factor based on Coulter Counter Analysis Values are mean [standard deviation] or number. CCA, Coulter Counter analysis; PIF, platelet increase factor; PRP, platelet-rich plasma. aValues from Table 5 in Sasaki.1 bPIF = (platelet concentration PRP)/(whole blood platelet concentration). For example, according to Table 5 in Dr Sasaki’s paper, CCA showed that the mean number of platelets for males, Batch A PRP (5 mL) was 136,991,250, which equates to 27,398/µL, or only 10% of the baseline platelet concentration of 276,750/µL. Therefore, the PIF is only 0.1× and 27,398/µL is 36.5× lower than the optimal value of 1 million/µL. This level of concentration would not qualify as PRP and it would not be surprising to see poor clinical results. Looking more closely at the study, 2 batches of PRP were used, A and B, representing low and high concentrations, respectively. However, both Batch A and B are described as “4.5 times the baseline platelet concentration of a patient’s whole blood.” Also, 1-mL aliquots of each batch were sent for CCA. Table 5 shows a very precise relationship between the batches; for both mean and standard deviations, the values for Batch B are exactly double the values for Batch A. This would not be expected if separate samples were measured by CCA. A PIF value of 4.5× still appears on Eclipse’s current website, based on “An average of several independent, verified tests” and “Whole Blood Platelets counts of 209 (106/mL)” (Table 2). Eclipse HC PRP3 PIF, platelet increase factor; PRP, platelet-rich plasma. The 44-mL kit consists of two 22-mL tubes.4 Eclipse HC PRP3 PIF, platelet increase factor; PRP, platelet-rich plasma. The 44-mL kit consists of two 22-mL tubes.4 Important questions arise from the manufacturer’s claims. How does the PIF improve from 3.5× to 4.5× simply by using 2 identical tubes, with no other change in protocol? How can the total number of platelets claimed be more than the starting number in whole blood multiplied by the claimed yield (~85%). For the 44-mL kit (2 × 22 mL): total platelets = 0.85 × (44 mL × 209 million/mL) = 7.8 billion < 10 billion claimed; for the 22-mL kit: total platelets = 0.85 × (22 mL × 209 million/mL) = 3.9 billion < 5 billion claimed. To obtain 5 and 10 billion platelets from the 22- and 44-mL kits would require yields of 93% and 123%, respectively. Where do the extra platelets come from? There is an extremely wide variety of PRP being produced by different systems available today. A recent comprehensive review of 34 different systems showed a 28× difference between the lowest and highest PIF, with platelet concentrations ranging from 79,000/µL (Eclipse) to 2.3 million/µL (Arthrex).5 The same review showed single-spin systems had an average PIF of 1.25×. Eclipse HC PRP consists of a single-spin system using a setting of 10 minutes × 1500g. Other researchers studying the effects of force and time on PRP preparation have concluded that maximum platelet yield is obtained at much lower settings,6-8 eg, 900g × 5 minutes7 or 160g × 10 minutes.7 As time and force increase, yield decreases, leading to a more “platelet pure” sample with fewer erythrocytes and leukocytes, but also lower platelet yield. These studies have demonstrated that a relatively high setting of 1500g × 10 minutes would lead to maximum volumes of plasma, but lower concentrations of all cell lines, including platelets, similar to the results of other independent studies of the Eclipse PRP system.9 Taking such a high value of 4.5× for PIF on a single-spin system, at face value, without independent verification, and contrary to other known research, can lead to unfounded conclusions. The only independent testing of concentration in this study, CCA, showed very low PIFs and platelet concentrations. It seems this study looked at the effects of PPP rather than PRP. Dr Yam has used PRP for regenerative and aesthetic purposes and has been an invited speaker on the preparation and use of PRP in clinical practice for international organizations (eg, IMCAS, FATS). The speaking engagements were unpaid, although one organization offered an honorarium after the fact that has not yet been received. Dr Yam has also used a hematology analyzer to test PRP and blood samples in clinical practice. The author has no financial relationships with any company related to PRP. The author received no financial support for the research, authorship, and publication of this article.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,999
Score d'incertitude au seuil0,021

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,028
Tête enseignante GPT0,285
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
DomaineMéthodes
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2021
Routes d'admission1
Résumé présentnon

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