Significance of nutritional status in the development of periprosthetic infections
Bibliographic record
Abstract
BACKGROUND: Malnutrition caused by protein and vitamin deficiencies is a significant negative prognostic factor in surgical wound healing disorders and infections. Particularly in elective surgery, preoperative compensation of deficiencies is advisable to avoid negative postoperative consequences. This study examined the nutritional and protein balance of patients with periprosthetic hip and knee joint infections. MATERIAL AND METHODS: Patients with periprosthetic hip or knee joint infections constituted the study group (SG). Control group I (CG I) included patients with primary implants and CG II included patients who required revision surgery because of aseptic loosening. Relevant nutritional and protein parameters were determined via analysis of peripheral venous blood samples. In addition, a questionnaire was used to evaluate the nutritional and eating patterns of all patients. The nutritional risk screening (NRS) 2002 score and body mass index (BMI) were also calculated for all participants. RESULTS: Differences were found in the albumin level (SG: 36.23 ± 7.34, CG I: 44.37 ± 3.32, p < 0.001, CG II: 44.06 ± 4.24, p < 0.001) and total protein in serum (SG: 65.42 ± 8.66, CG I: 70.80 ± 5.33, p = 0.004, CG II: 71.22 ± 5.21, p = 0.004). The number of patients with lowered albumin levels (SG 19/61, CG I 1/78, CG II 2/55) and total protein in serum (SG: 12/61, CG I 5/78, CG II 2/55) also showed considerable variation. The number of patients with a NRS 2002 score ≥3 differed significantly between SG and both CGs (SG: 5/61, CG I 1/78, CG II 0/55); however, these differences could not be confirmed using BMI. CONCLUSION: As expected, lowered albumin and total protein levels were observed in PJI due to the acute phase reaction. The NRS can be performed to exclude nutritional deficiency, which cannot be excluded based on BMI. In cases of periprosthetic joint infection it is reasonable to compensate the nutritional deficiency with dietary supplements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".