Can A Prediction Formula Accurately Predict Cardiorespiratory Fitness In Fibromyalgia Patients?
Bibliographic record
Abstract
Cardiorespiratory fitness (CRF) is often estimated using prediction formulas when clinicians do not have access to a metabolic cart. Unfortunately, using prediction formulas could potentially over or under estimate the CRF of patients with a chronic disease. Improving the accuracy of CRF in fibromyalgia (FM) patients is important considering that it has been reported that they have a lower CRF when compared to match controlled healthy participants. PURPOSE: To assess if a commonly used formula is accurate to predict CRF (VO2peak or METs) in women living with FM. METHODS: Twelve FM women (age: 50.5±7.9 years; weight: 69.3±16.0 kg; BMI: 26.4±7.1) were submitted twice to a maximal exercise test (BSU/Bruce ramp), with a 24 hours’ interval, until participants achieved volitional exhaustion. Gas exchange (Ergogard, Medisoft) and ECG (Quinton) was continuously monitored throughout the test. VO2peak was considered as the highest O2 uptake averaged over a 30 second period during the test and the highest value obtained between the first test (T1) and second (T2). Predicted VO2peak was determined by the formula integrated in the Quinton ECG system and the highest value between T1 and T2. The Metabolic equivalent of task (METs) was determined by using VO2peak values divided by 3.5 ml O2·kg−1·min−1. RESULTS: No significant differences were found between both VO2peak (T1; 25.5±5.3 vs. T2; 26.5±5.3 ml O2·kg−1·min−1, p>0.05) tests. However, measured VO2peak (27.2±5.6 ml O2·kg−1·min−1) was significantly lower than predicted VO2peak (32.4±5.6 ml O2·kg−1·min−1, p<0.05). In fact, the prediction formula overestimated the CRF by 1.5±1.1 METs or 19,1%. When participants were divided by the severity of their disease, CRF was overestimated by 1.2±0.8 METs in the mild (n=5) and by 1.6±1.3 METs in the moderately-to-severely (n=7) affected FM participants, but did not attain statistical difference between groups. CONCLUSION: Our results show that system based prediction formula commonly used in the clinical setting overestimate cardiorespiratory fitness in women with fibromyalgia and should be used with precaution.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".