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Biometric Health Screening (PNOĒ): Clinical Evidence

The CDC defines biometric screening as the measurement of physical characteristics such as height, weight, BMI, blood pressure, blood cholesterol, blood glucose, and aerobic fitness used to benchmark and evaluate health status over time.

Biometric Health Screening (Cardiometabolic Risk Assessment)

The CDC defines biometric screening as the measurement of physical characteristics such as height, weight, BMI, blood pressure, blood cholesterol, blood glucose, and aerobic fitness used to benchmark and evaluate health status over time. The AHA policy statement identifies 7 traditional biometric measures — blood pressure, glucose, cholesterol, physical activity, diet, body habitus (BMI), and tobacco use — as the foundation for cardiovascular risk stratification. Adding waist circumference to BMI improves identification of cardiometabolic risk, particularly in overweight and grade I obesity, as abdominal adiposity provides a more refined indicator of cardiovascular death risk than BMI alone. However, a Cochrane review of 15 trials found that general health checks (broad biometric screening) did not reduce all-cause mortality, cardiovascular mortality, or cancer mortality in the general population, though they did increase the number of new diagnoses made.

Body Composition and Nutritional Assessment

Body composition analysis has particular value in surgical populations:

  • ​ In spine surgery, reliance on BMI alone is insufficient — central adiposity and sarcopenic obesity are independent predictors of wound complications, mechanical failure, and delayed recovery. Radiographic abdominal circumference outperformed BMI for predicting diabetes (Cohen's d = -0.84) and hypertension in orthopedic patients.
  • ​ A validated nutritional and metabolic burden score (ASD-NMBS) incorporating age, BMI, diabetes status, anemia, vitamin D, hypertension, peripheral vascular disease, and smoking achieved an AUC of 92.9% for predicting postoperative complications in adult spinal deformity surgery, with scores >175 correlating with ≥1 complication.
  • ​ Malnutrition is present in 40–50% of older surgical patients and is a modifiable risk factor associated with increased complications, length of stay, and costs. Preoperative nutritional optimization (protein 1.2–1.5 g/kg/day, vitamin D, micronutrients) reduces postoperative complications and mortality.

Cardiorespiratory Fitness Testing (CPET/VO2 Max)

The 2024 AHA/ACC Perioperative Guidelines recognize cardiopulmonary exercise testing (CPET) as the gold-standard assessment of functional capacity, beneficial for risk stratification in high-risk patients undergoing elevated-risk procedures. Reduced cardiorespiratory fitness increases the risk of postoperative complications, and CPET can diagnose the etiology of exercise intolerance, guide preoperative optimization, and inform prehabilitation. Adults in the best quartile of cardiorespiratory fitness have as low as one-fourth the risk of developing common chronic metabolic and cardiovascular diseases compared to those in the poorest quartile.

Biometric-Guided Prehabilitation

The strongest evidence for biometric testing's clinical impact comes from its role in guiding preoperative prehabilitation programs. A 2026 meta-analysis of 23 RCTs (2,182 participants) found that exercise- or nutrition-based prehabilitation — guided by baseline biometric assessment — reduced postoperative complications by 48% (OR 0.52, p < 0.002) and length of stay by 0.44 days. The PREHAB trial demonstrated that multimodal prehabilitation improved functional capacity before surgery and resulted in faster postoperative recovery across cardiorespiratory fitness and strength measures.

Myotonometry and Tissue Biomechanics

Myotonometry — a biometric tool quantifying musculotendinous stiffness, compliance, tone, and elasticity — has demonstrated strong correlations with force production and muscle activation. Optimal stiffness levels may promote athletic performance, while extremes increase injury risk, suggesting utility in guiding rehabilitation programs and return-to-activity decisions.

References

  • Alzahrani, A., Aljohany, M., & Alsirhani, H. (2026). Real-time wearable biomechanics framework for sports injury prevention and rehabilitation optimization. Scientific reports, 16(1), 4436. https://doi.org/10.1038/s41598-025-34551-w
  • Biometric Health Screening for Employers: Consensus Statement of the Health Enhancement Research Organization, American College of Occupational and Environmental Medicine, and Care Continuum Alliance (2013). Journal of
  • Occupational & Environmental Medicine, 55(10), 1244–1251. https://doi.org/10.1097/JOM.0b013e3182a7e975
  • Cascavita, C. T., Hall, A. E., Shariati, K., Chevalier, J. M., Argame, A. A., Nguyen, N. H., Tseng, C. H., Hidalgo, M. A., Lee, J. C., & Craniofacial Outcomes Research Team (2026). Exercise- and Nutrition-Based Prehabilitation Programs in Surgery: A Systematic Review and Meta-Analysis. Journal of the American College of Surgeons, 243(1), 168–181. https://doi.org/10.1097/XCS.0000000000001891
  • Daniels, A. H., Kim, J., Nassar, J. E., & Diebo, B. G. (2026). Impact of Obesity, Sarcopenia, and Nutritional Status on Spine Surgery Patients. The Journal of the American Academy of Orthopaedic Surgeons, 10.5435/JAAOS-D-25-01362. Advance online publication. https://doi.org/10.5435/JAAOS-D-25-01362
  • Davergne, T., Pallot, A., Dechartres, A., Fautrel, B., & Gossec, L. (2019). Use of Wearable Activity Trackers to Improve Physical Activity Behavior in Patients With Rheumatic and Musculoskeletal Diseases: A Systematic Review and Meta-Analysis. Arthritis care & research, 71(6), 758–767. https://doi.org/10.1002/acr.23752
  • de Abreu-Silva, E. O., El Khouri, F. J., Sanchez, J. G., Bersch-Ferreira, A. C., Biasi, A., Siepmann, T., & Marcadenti, A. (2026). Cardiovascular health among employees of a Brazilian tertiary hospital assessed by the Life's Essential 8 score: A cross-sectional pilot study. Journal of Clinical Medicine, 15(8), 3134. https://doi.org/10.3390/jcm15083134
  • Eboreime, K. O., Hughes, J. G., Lee, R., & Luo, J. (2025). Can Wearable Device Promote Physical Activity and Reduce Pain in People with Chronic Musculoskeletal Conditions?. Journal of clinical medicine, 14(3), 1003. https://doi.org/10.3390/jcm14031003
  • Farrell, M. S., Bongiovanni, T., Cuschieri, J., Egodage, T., Elkbuli, A., Gelbard, R., Jawa, R., Mitha, S., Nassar, A. K., Pathak, A., Peralta, R., Putnam, T., & Stein, D. M. (2025). Geriatric nutrition in the surgical patient: an American Association for the Surgery of Trauma Critical Care and Geriatric Trauma Committees clinical consensus document. Trauma surgery & acute care open, 10(1), e001602. https://doi.org/10.1136/tsaco-2024-001602
  • Gallo-Villegas, J. A., & Calderón, J. C. (2023). Epidemiological, mechanistic, and practical bases for assessment of cardiorespiratory fitness and muscle status in adults
  • in healthcare settings. European journal of applied physiology, 123(5), 945–964. https://doi.org/10.1007/s00421-022-05114-y
  • Krogsbøll LT, Jørgensen KJ, Gøtzsche PC. General health checks in adults for reducing morbidity and mortality from disease. Cochrane Database of Systematic Reviews 2019, Issue 1. Art. No.: CD009009. DOI: 10.1002/14651858.CD009009.pub3. Accessed 09 July 2026.
  • Manriquez, A. H., Singh, M., Gonzalez, G., Kim, J., Carayannopoulos, N., Chisango, Z. M., Hurley, C., Nassar, J. E., Daniels, A. H., & Diebo, B. G. (2026). Preoperative Risk Stratification Using Radiographic Measures of Central Obesity. Spine, 51(8), 577–581. https://doi.org/10.1097/BRS.0000000000005513
  • McGowen, J. M., Hoppes, C. W., Forsse, J. S., Albin, S. R., Abt, J., & Koppenhaver, S. L. (2023). The Utility of Myotonometry in Musculoskeletal Rehabilitation and Human Performance Programming. Journal of athletic training, 58(4), 305–318. https://doi.org/10.4085/616.21
  • Molenaar, C. J. L., Minnella, E. M., Coca-Martinez, M., ten Cate, D. W. G., Regis, M., Awasthi, R., Martínez-Palli, G., López-Baamonde, M., Sebio-Garcia, R., Feo, C. V., van Rooijen, S. J., Schreinemakers, J. M. J., Bojesen, R. D., Gögenur, I., van den Heuvel, E. R., Carli, F., Slooter, G. D., & PREHAB Study Group. (2023). Effect of multimodal prehabilitation on reducing postoperative complications and enhancing functional capacity following colorectal cancer surgery: The PREHAB randomized clinical trial. JAMA Surgery, 158(6), 572–581. https://doi.org/10.1001/jamasurg.2023.0198
  • Ng, M. K., Mastrokostas, L. E., Mastrokostas, P. G., Razi, A., Monas, A., Bou Monsef, J., Razi, A. E., & Jazayeri, R. (2026). Nutritional Optimization in Spine Surgery: A Review of Its Implications for Postoperative Recovery and Outcomes. The Journal of the American Academy of Orthopaedic Surgeons, 10.5435/JAAOS-D-25-00757. Advance online publication. https://doi.org/10.5435/JAAOS-D-25-00757
  • Thompson, A., Fleischmann, K. E., Smilowitz, N. R., Aggarwal, N. R., Ahmad, F. S., Allen, R. B., Altin, S. E., Auerbach, A., Berger, J. S., Chow, B., Dakik, H. A., de las Fuentes, L., Eisenstein, E. L., Gerhard-Herman, M., Ghadimi, K., Kachulis, B., Leclerc, J., Lee, C. S., Macaulay, T. E., ... Williams, K. A., Sr. (2024). 2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM guideline for perioperative cardiovascular management for noncardiac surgery: A report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation, 150(19), e351–e442. https://doi.org/10.1161/CIR.0000000000001285
  • Tretiakov, P. S., Thomas, Z., Krol, O., Joujon-Roche, R., Williamson, T., Imbo, B., Dave, P., McFarland, K., Mir, J., Vira, S., Diebo, B., Schoenfeld, A. J., & Passias, P. G. (2024). The Predictive Potential of Nutritional and Metabolic Burden: Development of a Novel Validated Metric Predicting Increased Postoperative Complications in Adult Spinal Deformity Surgery. Spine, 49(9), 609–614. https://doi.org/10.1097/BRS.0000000000004797

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