Refining the Parameters for Diagnosis of Periprosthetic Infection
Notice bibliographique
Résumé
Commentary The diagnosis of periprosthetic infection in hip and knee replacement surgery is often difficult1. Although overt signs of infection are readily apparent and easily interpreted, the diagnosis of infection in the absence of such overt signs may be problematic2. A number of indirect indicators of infection have been studied, including bone scintigraphy, systemic inflammatory markers, and synovial fluid analysis. None of these methods will yield a result that, in and of itself, is diagnostic of periprosthetic infection; however, taken together, multiple indicators may reasonably lead to an appropriate diagnostic conclusion3. The authors have undertaken a complex research study in an attempt to determine the natural course of the synovial fluid white blood-cell (WBC) count as a function of time, from the date of the index operation up to the time of arthrocentesis and synovial fluid analysis. The study involved 571 primary total knee arthroplasties that required arthrocentesis within the first two postoperative years; the times between surgery and aspiration were then segmented as outlined in the paper. The synovial fluid WBC count, the percentage of polymorphonuclear leukocytes (PMNs), and the total neutrophil count were determined. In the body of the paper, the authors clearly outline the rate of progression in these three parameters with time elapsed from surgery. The interpretation of these results has to be approached with some caution for a number of reasons. First and foremost, the knees from which the samples were derived were all knees with a problem. The patients obviously exhibited signs and/or symptoms that led the treating surgeon to suspect periprosthetic infection. Even though the included synovial fluid analyses were restricted to those patients without evidence of periprosthetic infection on final evaluation, they still reflect the patient with an abnormal postoperative course. Second, it is my practice not to aspirate a painful knee in the presence of normal systemic inflammatory markers. It is not clear from the data presented in this paper what percentage of patients had abnormal inflammatory markers prior to the decision to carry out arthrocentesis. The value of this paper, however, is the clear demonstration that there will be a change in the WBC count and the PMN percentage during the first six postoperative weeks. The rate of change varies with time and it will therefore be important, when relying upon these results, to be aware of the time elapsed between the index surgery and arthrocentesis. The authors also suggest that the total neutrophil count may be a more sensitive indicator of infection than either the synovial WBC count or the PMN percentage is, and they have appropriately suggested that further investigation of this particular laboratory value be conducted. I support their statement that “because these markers change at different rates over time, the use of specific thresholds for the synovial fluid WBC count and differential would probably represent an oversimplification of a complex phenomenon.” Their recommendations regarding criteria development seem appropriate, and I will look forward to further research conducted in this area in order to better define these important laboratory values.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,004 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».