Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis
Abstract
:1. Introduction
2. Materials and Methods
Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Overall, N = 815 | Injured, N = 30 | Not Injured, N = 785 | |
---|---|---|---|
ACWR | 1 (0.76, 1.16) | 1.2 (0.93, 1.35) | 0.99 (0.76, 1.35) |
ACWRr | 0.98 (0.67, 1.46) | 1.29 (1.02, 2.01) | 0.97 (0.67, 2.01) |
Acute Load | 1800 (1400, 2308) | 2138 (1820, 2880) | 1780 (1400, 2880) |
Cumulative Load (2 weeks) | 3640 (3000, 4362) | 3891 (3325, 4745) | 3625 (2990, 4745) |
Cumulative Load (3 weeks) | 5331 (4513, 6271) | 5458 (4582, 5899) | 5327 (4511, 5899) |
Cumulative Load (4 weeks) | 7174 (5826, 8347) | 7065 (5951, 8621) | 7185 (5825, 8621) |
Chronic Load (4 weeks) | 1900 (1620, 2244) | 1870 (1598, 2141) | 1900 (1620, 2254) |
Variables | Overall, N = 815 | Injured, N = 30 | Not Injured, N = 785 |
---|---|---|---|
Acute Load Quantiles | |||
First | 205 (25%) | 3 (10%) | 202 (26%) |
Second | 206 (25%) | 5 (17%) | 201 (26%) |
Third | 200 (25%) | 8 (27%) | 192 (24%) |
Fourth | 204 (25%) | 14 (47%) | 190 (24%) |
ACWR Quantiles | |||
First | 205 (25%) | 3 (25%) | 202 (26%) |
Second | 219 (27%) | 6 (20%) | 213 (27%) |
Third | 187 (23%) | 5 (17%) | 182 (23%) |
Fourth | 204 (25%) | 16 (53%) | 188 (24%) |
ACWRr Quantiles | |||
First | 204 (25%) | 205 (25%) | 201 (26%) |
Second | 204 (25%) | 206 (25%) | 200 (25%) |
Third | 203 (25%) | 200 (25%) | 194 (25%) |
Fourth | 204 (25%) | 204 (25%) | 190 (24%) |
Mean | HDI 2.5% | HDI 97.5% | ESS | |
---|---|---|---|---|
Injured | ||||
Mu | 2296.28 | 2000.21 | 2592.58 | 8196.6 |
Sigma | 756.34 | 560.5 | 1023.57 | 3394.13 |
Not Injured | ||||
Mu | 1847.62 | 1792.49 | 1903.53 | 22,465.81 |
Sigma | 654.33 | 590.28 | 720.85 | 14,753.83 |
Group Diff. | ||||
Nu | 12.46 | 5.23 | 38.46 | 4233.86 |
Effect Size | 0.64 | 0.20 | 1.09 | |
Mean Diff | 448.66 | 146.36 | 748.07 |
Mean | HDI 2.5% | HDI 97.5% | ESS | |
---|---|---|---|---|
Injured | ||||
Mu | 1.18 | 1.03 | 1.32 | 19,033 |
Sigma | 0.38 | 0.28 | 0.51 | 6421 |
Not Injured | ||||
Mu | 0.96 | 0.94 | 0.98 | 17,854 |
Sigma | 0.28 | 0.26 | 0.30 | 12,787 |
Group Diff. | ||||
Nu | 23.26 | 8.64 | 64.66 | 6155.5 |
Effect Size | 0.64 | 0.2 | 1.08 | |
Mean Diff | 0.21 | 0.07 | 0.36 |
Mean | HDI 2.5% | HDI 97.5% | ESS | |
---|---|---|---|---|
ACWR | ||||
β0 | −3.45 | −3.92 | −3.04 | 11,557 |
β1 | −0.62 | −1.55 | 0.11 | 9272 |
β2 | −0.13 | −0.81 | 0.51 | 15,042 |
β3 | −0.15 | −0.87 | 0.53 | 15,573 |
β4 | 0.90 | 0.28 | 1.51 | 6059 |
P(Inj | ACWR > 1.15) | 0.07 | 0.04 | 0.11 | |
Random ACWR | ||||
β0 | −3.43 | −3.90 | −3.03 | 10,439 |
β1 | −0.62 | −1.56 | 0.09 | 8005 |
β2 | −0.41 | −1.22 | 0.28 | 11,619 |
β3 | 0.30 | −0.30 | 0.92 | 10,790 |
β4 | 0.73 | 0.12 | 1.34 | 5809 |
P(Inj | ACWRr > 1.45) | 0.06 | 0.04 | 0.10 |
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Carbone, L.; Sampietro, M.; Cicognini, A.; García-Sillero, M.; Vargas-Molina, S. Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis. J. Clin. Med. 2022, 11, 5945. https://doi.org/10.3390/jcm11195945
Carbone L, Sampietro M, Cicognini A, García-Sillero M, Vargas-Molina S. Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis. Journal of Clinical Medicine. 2022; 11(19):5945. https://doi.org/10.3390/jcm11195945
Chicago/Turabian StyleCarbone, Leandro, Matias Sampietro, Agustin Cicognini, Manuel García-Sillero, and Salvador Vargas-Molina. 2022. "Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis" Journal of Clinical Medicine 11, no. 19: 5945. https://doi.org/10.3390/jcm11195945