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Sources & Citations

Every DrPaul health tool is built on peer-reviewed research, published clinical guidelines, and established medical reference standards. Below you'll find detailed citations for 32 of our tools, with citations for the remaining tools available on each individual tool's page.

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Phenotypic Age Calculator MedCheck Rx™ CancerClarity™ TravelGuard™ NutriGuard Rx™ SuppleSafe 360™ DailyDose Rx™ HealthFacts Rx™ Daily Health™ AHA PREVENT Calculator Metabolic Syndrome Analyzer Lipid Profile Analyzer CMP Analyzer Thyroid Panel Analyzer Iron Profile Analyzer Inflammatory Biomarker Analyzer Autoimmune Biomarker Analyzer Kidney Function Analyzer™ Sleep Health Analyzer™ MindScreen™ Depression & Anxiety OvarySpan™ Hormone Analyzer AndroVitality™ Men's Hormone Analyzer MenoVitality™ Women's Menopause Analyzer BoneWise™ Bone Health Risk EnduranceReady™ Analyzer IronReady™ Triathlon Analyzer CardioGuard HF™ Environmental Health Calculator Epigenetic Clock — TruDiagnostic Integrated Biological Profile DoshaBalance™ Constitutional Assessment Mindfulness Rx™ Assessment
🤖 About AI-Powered Tools: Some of our tools use AI to synthesize information from the databases and guidelines listed below. The specific tools that use AI are identified by an AI badge and consent disclosure on each individual tool page. Each AI-generated result includes specific source references within the output itself. See our AI Use Disclosure for full details.
Phenotypic Age Calculator
Biological age from 9 standard blood biomarkers using the Levine et al. Gompertz formula
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  1. 1Levine ME, Lu AT, Quach A, et al. “An epigenetic biomarker of aging for lifespan and healthspan.” Aging (Albany NY). 2018;10(4):573-591. doi:10.18632/aging.101414
  2. 2Liu Z, Kuo PL, Horvath S, Crimmins E, Ferrucci L, Levine M. “A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV.” PLoS One. 2018;13(6):e0197245. doi:10.1371/journal.pone.0197245
  3. 3Belsky DW, Caspi A, Houts R, et al. “Quantification of biological aging in young adults.” Proc Natl Acad Sci USA. 2015;112(30):E4104-E4110. doi:10.1073/pnas.1506264112
  4. 4Reference ranges: ARUP Laboratories (aruplab.com) and Mayo Clinic Laboratories (mayocliniclabs.com)
MedCheck Rx™
AI-powered medication interaction analysis
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  1. 1U.S. Food and Drug Administration. “FDA Adverse Event Reporting System (FAERS).” fda.gov/drugs
  2. 2DrugBank Online. Comprehensive drug interaction and pharmacology database. go.drugbank.com
  3. 3National Library of Medicine. “DailyMed: Drug label information.” dailymed.nlm.nih.gov
  4. 4Lexicomp / UpToDate. Drug interaction analysis methodology. Wolters Kluwer Health. wolterskluwer.com
  5. 5Hansten PD, Horn JR. Drug Interactions Analysis and Management. Wolters Kluwer Health; updated annually.
CancerClarity™
5-year personalized cancer screening timeline
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  1. 1U.S. Preventive Services Task Force. Grade A & B Screening Recommendations. uspreventiveservicestaskforce.org
  2. 2American Cancer Society. “Cancer Screening Guidelines.” cancer.org/screening
  3. 3National Comprehensive Cancer Network. “NCCN Guidelines for Detection, Prevention, & Risk Reduction.” nccn.org/guidelines
  4. 4American Association for the Study of Liver Diseases. “HCC Surveillance Guidelines.” aasld.org
  5. 5U.S. Centers for Disease Control and Prevention. “Cancer Screening Tests.” cdc.gov/cancer
TravelGuard™
Live global outbreak alerts for travelers
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  1. 1U.S. Centers for Disease Control and Prevention. “CDC Travelers’ Health — Destinations.” wwwnc.cdc.gov/travel
  2. 2World Health Organization. “Disease Outbreak News (DONs).” who.int/emergencies
  3. 3CDC. “Yellow Book — Health Information for International Travel.” CDC Yellow Book
  4. 4ProMED — International Society for Infectious Diseases. promedmail.org
NutriGuard Rx™
Condition-based food & beverage avoidance guide
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  1. 1NIH Office of Dietary Supplements. “Dietary Supplement Fact Sheets.” ods.od.nih.gov
  2. 2Academy of Nutrition and Dietetics. “Evidence Analysis Library.” andeal.org
  3. 3U.S. FDA. “Drug Interactions: What You Should Know.” fda.gov/drugs
  4. 4Natural Medicines Comprehensive Database. Therapeutic Research Center. naturalmedicines.therapeuticresearch.com
  5. 5American Diabetes Association. “Standards of Care — Nutrition Therapy.” diabetesjournals.org/care
SuppleSafe 360™
Supplement safety & interaction checker
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  1. 1United States Pharmacopeia. “USP-NF Dietary Supplement Standards.” usp.org
  2. 2NIH Office of Dietary Supplements. “Dietary Supplement Fact Sheets.” ods.od.nih.gov
  3. 3Natural Medicines Comprehensive Database. Therapeutic Research Center. naturalmedicines.therapeuticresearch.com
  4. 4Stargrove MB, Treasure J, McKee DL. Herb, Nutrient, and Drug Interactions. Mosby/Elsevier; 2008.
  5. 5WHO. “Monographs on Selected Medicinal Plants.” who.int/publications
DailyDose Rx™
Personalized daily health tips from research databases
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  1. 1National Library of Medicine. “PubMed.” pubmed.ncbi.nlm.nih.gov
  2. 2U.S. National Library of Medicine. “ClinicalTrials.gov.” clinicaltrials.gov
  3. 3Allen Institute for AI. “Semantic Scholar.” semanticscholar.org
  4. 4U.S. FDA. “Safety Data and Adverse Event Reports.” fda.gov/safety
HealthFacts Rx™
AI-powered health information lookup with citation references
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  1. 1National Library of Medicine. “PubMed.” pubmed.ncbi.nlm.nih.gov
  2. 2Cochrane Library. “Cochrane Systematic Reviews.” cochranelibrary.com
  3. 3World Health Organization. “WHO Fact Sheets.” who.int/fact-sheets
  4. 4U.S. Centers for Disease Control and Prevention. “Health Topics A-Z.” cdc.gov
Daily Health™
AI-powered daily health recommendations
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  1. 1National Library of Medicine. “PubMed.” pubmed.ncbi.nlm.nih.gov
  2. 2U.S. Centers for Disease Control and Prevention. “Health Topics A-Z.” cdc.gov
  3. 3World Health Organization. “Health Topics.” who.int/health-topics
AHA PREVENT CVD Risk Calculator
10 & 30-year cardiovascular disease risk assessment
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  1. 1Khan SS, Matsushita K, Sang Y, et al. “Development and validation of the AHA PREVENT equations.” Circulation. 2024;149(6):e430-e449. doi:10.1161/CIR.0000000000001191
  2. 2American Heart Association. “PREVENT Online Calculator.” professional.heart.org
  3. 3Arnett DK, Blumenthal RS, et al. “2019 ACC/AHA Guideline on Primary Prevention of CVD.” Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
Metabolic Syndrome Analyzer
5-criteria metabolic risk evaluation
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  1. 1Alberti KG, Eckel RH, Grundy SM, et al. “Harmonizing the metabolic syndrome.” Circulation. 2009;120(16):1640-1645. doi:10.1161/CIRCULATIONAHA.109.192644
  2. 2Grundy SM, et al. “Diagnosis and management of the metabolic syndrome: AHA/NHLBI scientific statement.” Circulation. 2005;112(17):2735-2752. doi:10.1161/CIRCULATIONAHA.105.169404
  3. 3National Heart, Lung, and Blood Institute. “Metabolic Syndrome.” nhlbi.nih.gov
Lipid Profile Analyzer
Cholesterol & lipid panel interpretation
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  1. 1Grundy SM, Stone NJ, et al. “2018 AHA/ACC Guideline on Blood Cholesterol Management.” J Am Coll Cardiol. 2019;73(24):e285-e350. doi:10.1016/j.jacc.2018.11.003
  2. 2NHLBI. “Blood Cholesterol.” nhlbi.nih.gov
  3. 3Reference ranges: ARUP Laboratories (aruplab.com) and Mayo Clinic Laboratories (mayocliniclabs.com)
Comprehensive Metabolic Panel Analyzer
Liver, kidney, electrolyte, and metabolic panel interpretation
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  1. 1ARUP Laboratories. “Laboratory Test Directory.” aruplab.com
  2. 2Mayo Clinic Laboratories. “Test Definitions and Reference Ranges.” mayocliniclabs.com
  3. 3National Kidney Foundation. “eGFR Calculator and CKD Staging.” kidney.org
  4. 4American Diabetes Association. “Standards of Care in Diabetes.” diabetesjournals.org/care
Thyroid Panel Analyzer
TSH, T3, T4 result interpretation
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  1. 1Jonklaas J, Bianco AC, et al. “Guidelines for the treatment of hypothyroidism.” Thyroid. 2014;24(12):1670-1751. doi:10.1089/thy.2014.0028
  2. 2Ross DS, Burch HB, et al. “2016 ATA Guidelines for Hyperthyroidism.” Thyroid. 2016;26(10):1343-1421. doi:10.1089/thy.2016.0229
  3. 3American Thyroid Association. “Thyroid Function Tests.” thyroid.org
  4. 4Reference ranges: ARUP Laboratories (aruplab.com) and Mayo Clinic Laboratories (mayocliniclabs.com)
Iron Profile Analyzer
Iron, ferritin, TIBC analysis
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  1. 1Camaschella C. “Iron-deficiency anemia.” N Engl J Med. 2015;372(19):1832-1843. doi:10.1056/NEJMra1401038
  2. 2Bacon BR, Adams PC, et al. “Diagnosis and management of hemochromatosis: 2011 AASLD practice guideline.” Hepatology. 2011;54(1):328-343. doi:10.1002/hep.24330
  3. 3WHO. “Iron Deficiency Anaemia: Assessment, Prevention, and Control.” who.int/publications
  4. 4Reference ranges: ARUP Laboratories (aruplab.com) and Mayo Clinic Laboratories (mayocliniclabs.com)
Inflammatory Biomarker Analyzer
CRP, ESR, and inflammation markers
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  1. 1Ridker PM. “C-reactive protein, inflammation, and cardiovascular disease.” Tex Heart Inst J. 2005;32(3):384-386. PMC1336713
  2. 2Furman D, et al. “Chronic inflammation in the etiology of disease across the life span.” Nat Med. 2019;25(12):1822-1832. doi:10.1038/s41591-019-0675-0
  3. 3Pearson TA, et al. “Markers of inflammation and CVD — AHA/CDC statement.” Circulation. 2003;107(3):499-511. doi:10.1161/01.CIR.0000052939.59093.45
  4. 4Reference ranges: ARUP Laboratories (aruplab.com) and Mayo Clinic Laboratories (mayocliniclabs.com)
Autoimmune Biomarker Analyzer
ANA, RF, and autoimmune markers
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  1. 1Aletaha D, Neogi T, et al. “2010 ACR/EULAR RA classification criteria.” Arthritis Rheum. 2010;62(9):2569-2581. doi:10.1002/art.27584
  2. 2Damoiseaux J, et al. “Clinical relevance of HEp-2 patterns: ICAP consensus.” Ann Rheum Dis. 2019;78(7):879-889. doi:10.1136/annrheumdis-2018-214436
  3. 3American College of Rheumatology. “Clinical Practice Guidelines.” rheumatology.org
  4. 4Reference ranges: ARUP Laboratories (aruplab.com) and Mayo Clinic Laboratories (mayocliniclabs.com)
Kidney Function Analyzer™
CKD-EPI 2021 race-free eGFR with KDIGO 2024 staging and personalized AI interpretation
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  1. 1Inker LA, Eneanya ND, Coresh J, et al. “New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race.” N Engl J Med. 2021;385(19):1737-1749. doi:10.1056/NEJMoa2102953
  2. 2Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. “KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease.” Kidney Int. 2024;105(4S):S117-S314. Full Guideline PDF
  3. 3Delgado C, Baweja M, Crews DC, et al. “A Unifying Approach for GFR Estimation: Recommendations of the NKF-ASN Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease.” Am J Kidney Dis. 2022;79(2):268-288. doi:10.1053/j.ajkd.2021.08.003
  4. 4Tangri N, Stevens LA, Griffith J, et al. “A Predictive Model for Progression of Chronic Kidney Disease to Kidney Failure.” JAMA. 2011;305(15):1553-1559. doi:10.1001/jama.2011.451
  5. 5Tangri N, Grams ME, Levey AS, et al. “Multinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure: A Meta-analysis.” JAMA. 2016;315(2):164-174. doi:10.1001/jama.2015.18202
  6. 6Matsushita K, van der Velde M, Astor BC, et al. (Chronic Kidney Disease Prognosis Consortium). “Association of Estimated Glomerular Filtration Rate and Albuminuria with All-Cause and Cardiovascular Mortality in General Population Cohorts: A Collaborative Meta-analysis.” Lancet. 2010;375(9731):2073-2081. doi:10.1016/S0140-6736(10)60674-5
  7. 7National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). “eGFR Equations for Adults: 2021 CKD-EPI Reference Implementation.” niddk.nih.gov
  8. 8National Kidney Foundation. “CKD-EPI Creatinine Equation (2021).” kidney.org
  9. 9Stevens PE, Ahmed SB, Carrero JJ, et al. “KDOQI US Commentary on the KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of CKD.” Am J Kidney Dis. 2024;84(5):540-561. Full Article
Sleep Health Analyzer™
RU-SATED multidimensional sleep health assessment with optional STOP-BANG (OSA) and ISI (insomnia) screening, plus AI clinical interpretation
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  1. 1Buysse DJ. “Sleep health: can we define it? Does it matter?” Sleep. 2014;37(1):9-17. doi:10.5665/sleep.3298
  2. 2Wallace ML, Buysse DJ, Redline S, et al. “Multidimensional sleep and mortality in older adults: a machine-learning comparison with other risk factors.” Sleep. 2021;44(4):zsaa204. doi:10.1093/sleep/zsaa204
  3. 3Chung F, Abdullah HR, Liao P. “STOP-Bang questionnaire: a practical approach to screen for obstructive sleep apnea.” Chest. 2016;149(3):631-638. doi:10.1378/chest.15-0903
  4. 4Morin CM, Belleville G, Bélanger L, Ivers H. “The Insomnia Severity Index: psychometric indicators to detect insomnia cases and evaluate treatment response.” Sleep. 2011;34(5):601-608. doi:10.1093/sleep/34.5.601
  5. 5Johns MW. “A new method for measuring daytime sleepiness: the Epworth Sleepiness Scale.” Sleep. 1991;14(6):540-545. doi:10.1093/sleep/14.6.540
  6. 6Hirshkowitz M, Whiton K, Albert SM, et al. “National Sleep Foundation’s sleep time duration recommendations: methodology and results summary.” Sleep Health. 2015;1(1):40-43. doi:10.1016/j.sleh.2014.12.010
  7. 7American Academy of Sleep Medicine. “Clinical Practice Guidelines.” aasm.org/practice-guidelines
MindScreen™ Depression & Anxiety Screening
PHQ-9 + GAD-7 dual screening with crisis-resource integration (988 Lifeline, Crisis Text Line)
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  1. 1Kroenke K, Spitzer RL, Williams JBW. “The PHQ-9: validity of a brief depression severity measure.” J Gen Intern Med. 2001;16(9):606-613. doi:10.1046/j.1525-1497.2001.016009606.x
  2. 2Spitzer RL, Kroenke K, Williams JBW, Löwe B. “A brief measure for assessing generalized anxiety disorder: the GAD-7.” Arch Intern Med. 2006;166(10):1092-1097. doi:10.1001/archinte.166.10.1092
  3. 3U.S. Preventive Services Task Force. “Screening for Depression and Suicide Risk in Adults: Recommendation Statement.” JAMA. 2023;329(23):2057-2067. jamanetwork.com
  4. 4U.S. Preventive Services Task Force. “Screening for Anxiety Disorders in Adults: Recommendation Statement.” JAMA. 2023;329(24):2163-2170.
  5. 5988 Suicide & Crisis Lifeline. “Free, confidential 24/7 emotional support.” 988lifeline.org
  6. 6Crisis Text Line. “Text HOME to 741741 for free crisis counseling.” crisistextline.org
OvarySpan™ Hormone Analyzer
AI-powered women's hormone panel analysis with reproductive aging and biological age framework
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  1. 1Levine ME, Lu AT, Quach A, et al. “An epigenetic biomarker of aging for lifespan and healthspan.” Aging (Albany NY). 2018;10(4):573-591. (Establishes the 2-4 year biological age acceleration at menopause.) doi:10.18632/aging.101414
  2. 2Davis SR, Lambrinoudaki I, Lumsden M, et al. “Menopause.” Nat Rev Dis Primers. 2015;1:15004. doi:10.1038/nrdp.2015.4
  3. 3Mosconi L, Berti V, Quinn C, et al. “Sex differences in Alzheimer risk: brain imaging of endocrine vs chronologic aging.” Neurology. 2017;89(13):1382-1390. doi:10.1212/WNL.0000000000004425
  4. 4Manson JE, Aragaki AK, Rossouw JE, et al. “Menopausal hormone therapy and long-term all-cause and cause-specific mortality.” JAMA. 2017;318(10):927-938. doi:10.1001/jama.2017.11217
  5. 5The North American Menopause Society. “2022 Hormone Therapy Position Statement.” Menopause. 2022;29(7):767-794.
  6. 6Speroff L, Fritz MA. Clinical Gynecologic Endocrinology and Infertility. 8th ed. Lippincott Williams & Wilkins; 2011.
  7. 7Reference ranges: ARUP Laboratories (aruplab.com) and Mayo Clinic Laboratories (mayocliniclabs.com)
AndroVitality™ Men's Hormone Panel Analyzer
AI-powered men's hormone panel analysis (14 biomarkers across HPG axis, adrenal output, prostate safety, whole-health context) classifying primary vs central hypogonadism, compensated states, hyperprolactinemia, SHBG-driven free-T deficiency, and aromatization patterns
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  1. 1Bhasin S, Brito JP, Cunningham GR, et al. “Testosterone Therapy in Men With Hypogonadism: An Endocrine Society Clinical Practice Guideline.” J Clin Endocrinol Metab. 2018;103(5):1715-1744. doi:10.1210/jc.2018-00229
  2. 2Mulhall JP, Trost LW, Brannigan RE, et al. “Evaluation and Management of Testosterone Deficiency: AUA Guideline.” J Urol. 2018;200(2):423-432. (Reviewed and amended 2023.) AUA Guideline
  3. 3Snyder PJ, Bhasin S, Cunningham GR, et al. “Effects of Testosterone Treatment in Older Men (The Testosterone Trials).” N Engl J Med. 2016;374(7):611-624. doi:10.1056/NEJMoa1506119
  4. 4Lincoff AM, Bhasin S, Flevaris P, et al. “Cardiovascular Safety of Testosterone-Replacement Therapy (TRAVERSE Study).” N Engl J Med. 2023;389(2):107-117. doi:10.1056/NEJMoa2215025
  5. 5Travison TG, Vesper HW, Orwoll E, et al. “Harmonized Reference Ranges for Circulating Testosterone Levels in Men of Four Cohort Studies in the United States and Europe.” J Clin Endocrinol Metab. 2017;102(4):1161-1173. doi:10.1210/jc.2016-2935
  6. 6Rosner W, Auchus RJ, Azziz R, Sluss PM, Raff H. “Utility, limitations, and pitfalls in measuring testosterone: An Endocrine Society Position Statement.” J Clin Endocrinol Metab. 2007;92(2):405-413. doi:10.1210/jc.2006-1864
  7. 7Vermeulen A, Verdonck L, Kaufman JM. “A critical evaluation of simple methods for the estimation of free testosterone in serum.” J Clin Endocrinol Metab. 1999;84(10):3666-3672. (Vermeulen Free-T formula used as conceptual underpinning of SHBG-adjusted bioavailable estimates.) doi:10.1210/jcem.84.10.6079
  8. 8Melmed S, Casanueva FF, Hoffman AR, et al. “Diagnosis and treatment of hyperprolactinemia: An Endocrine Society Clinical Practice Guideline.” J Clin Endocrinol Metab. 2011;96(2):273-288. doi:10.1210/jc.2010-1692
  9. 9Tajar A, Forti G, O’Neill TW, et al. “Characteristics of secondary, primary, and compensated hypogonadism in aging men: Evidence from the European Male Ageing Study.” J Clin Endocrinol Metab. 2010;95(4):1810-1818. doi:10.1210/jc.2009-1796
  10. 10Pilz S, Frisch S, Koertke H, et al. “Effect of vitamin D supplementation on testosterone levels in men.” Horm Metab Res. 2011;43(3):223-225. doi:10.1055/s-0030-1269854
  11. 11Wittert G, Bracken K, Robledo KP, et al. “Testosterone treatment to prevent or revert type 2 diabetes in men enrolled in a lifestyle programme (T4DM).” Lancet Diabetes Endocrinol. 2021;9(1):32-45. doi:10.1016/S2213-8587(20)30367-3
  12. 12Corona G, Rastrelli G, Monami M, et al. “Body weight loss reverts obesity-associated hypogonadotropic hypogonadism: A systematic review and meta-analysis.” Eur J Endocrinol. 2013;168(6):829-843. doi:10.1530/EJE-12-0955
  13. 13Wei JT, Barocas D, Carlsson S, et al. “Early Detection of Prostate Cancer: AUA/SUO Guideline.” J Urol. 2023;210(1):46-53. AUA/SUO Guideline
  14. 14Leproult R, Van Cauter E. “Effect of 1 week of sleep restriction on testosterone levels in young healthy men.” JAMA. 2011;305(21):2173-2174. doi:10.1001/jama.2011.710
  15. 15Reference ranges: ARUP Laboratories (aruplab.com) and Mayo Clinic Laboratories (mayocliniclabs.com)
MenoVitality™ Women's Menopause Hormone Panel Analyzer
AI-powered analysis of women's hormone panels anchored in the STRAW+10 staging system, with 12-pattern classification and Modified Greene Climacteric Scale symptom integration. For perimenopause, menopause, postmenopause, surgical menopause, POI, and HRT-monitoring scenarios.
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  1. Harlow SD, Gass M, Hall JE, et al. "Executive summary of the Stages of Reproductive Aging Workshop +10: addressing the unfinished agenda of staging reproductive aging." Menopause. 2012;19(4):387-395. doi:10.1097/gme.0b013e31824d8f40
  2. Greene JG. "Constructing a standard climacteric scale." Maturitas. 1998;29(1):25-31. doi:10.1016/s0378-5122(98)00025-5
  3. "The 2022 Hormone Therapy Position Statement of The North American Menopause Society." Menopause. 2022;29(7):767-794. doi:10.1097/GME.0000000000002028
  4. Stuenkel CA, Davis SR, Gompel A, et al. "Treatment of Symptoms of the Menopause: An Endocrine Society Clinical Practice Guideline." J Clin Endocrinol Metab. 2015;100(11):3975-4011. doi:10.1210/jc.2015-2236
  5. Manson JE, Aragaki AK, Rossouw JE, et al. "Menopausal Hormone Therapy and Long-term All-Cause and Cause-Specific Mortality: The Women's Health Initiative Randomized Trials." JAMA. 2017;318(10):927-938. doi:10.1001/jama.2017.11217
  6. "The 2020 Genitourinary Syndrome of Menopause Position Statement of The North American Menopause Society." Menopause. 2020;27(9):976-992. doi:10.1097/GME.0000000000001609
  7. "Management of osteoporosis in postmenopausal women: the 2021 position statement of The North American Menopause Society." Menopause. 2021;28(9):973-997. doi:10.1097/GME.0000000000001831
  8. Matthews KA, Crawford SL, Chae CU, et al. "Are changes in cardiovascular disease risk factors in midlife women due to chronological aging or to the menopausal transition?" J Am Coll Cardiol. 2009;54(25):2366-2373. doi:10.1016/j.jacc.2009.10.009
  9. Karvonen-Gutierrez C, Kim C. "Association of Mid-Life Changes in Body Size, Body Composition and Obesity Status with the Menopausal Transition." Healthcare (Basel). 2016;4(3):42. doi:10.3390/healthcare4030042
  10. Ridker PM, Rifai N, Rose L, Buring JE, Cook NR. "Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events." N Engl J Med. 2002;347(20):1557-1565. doi:10.1056/NEJMoa021993
  11. Rocca WA, Bower JH, Maraganore DM, et al. "Increased risk of cognitive impairment or dementia in women who underwent oophorectomy before menopause." Neurology. 2007;69(11):1074-1083. doi:10.1212/01.wnl.0000276984.19542.e6
  12. Joffe H, Crawford S, Economou N, et al. "A gonadotropin-releasing hormone agonist model demonstrates that nocturnal hot flashes interrupt objective sleep." Sleep. 2013;36(12):1977-1985. doi:10.5665/sleep.3244
  13. Webber L, Davies M, Anderson R, et al. "ESHRE Guideline: management of women with premature ovarian insufficiency." Hum Reprod. 2016;31(5):926-937. doi:10.1093/humrep/dew027
  14. Davis SR, Baber R, Panay N, et al. "Global Consensus Position Statement on the Use of Testosterone Therapy for Women." J Clin Endocrinol Metab. 2019;104(10):4660-4666. doi:10.1210/jc.2019-01603
  15. Melmed S, Casanueva FF, Hoffman AR, et al. "Diagnosis and treatment of hyperprolactinemia: an Endocrine Society clinical practice guideline." J Clin Endocrinol Metab. 2011;96(2):273-288. doi:10.1210/jc.2010-1692
BoneWise™ Bone Health Risk Analyzer
Multi-domain bone health risk assessment for women across the menopause continuum (clinical, hormonal, medication, nutrition, lab/DEXA)
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  1. 1U.S. Preventive Services Task Force. “Screening for Osteoporosis to Prevent Fractures: USPSTF Recommendation Statement.” JAMA. 2025;333(6):498-508.
  2. 2Camacho PM, Petak SM, Binkley N, et al. “AACE/ACE Clinical Practice Guideline for the Diagnosis and Treatment of Postmenopausal Osteoporosis — 2020 Update.” Endocr Pract. 2020;26(Suppl 1):1-46.
  3. 3Eastell R, Rosen CJ, Black DM, et al. “Pharmacological Management of Osteoporosis in Postmenopausal Women: An Endocrine Society Clinical Practice Guideline.” J Clin Endocrinol Metab. 2019;104(5):1595-1622.
  4. 4Wu Q, Jung J. “Racial and genetic disparities in FRAX performance.” J Bone Miner Res. 2026;41(4):424-433.
  5. 5Qin Y, et al. “Personalized reference intervals for bone turnover markers in older adults.” Clin Chem Lab Med. 2026;64(5):1109-1116.
  6. 6Yuan Y, et al. “Probiotic supplementation and bone turnover markers: meta-analysis of 15 RCTs.” Front Cell Infect Microbiol. 2026;15:1738378.
  7. 7Alghadir AH, et al. “HIIT and vitamin D on bone metabolism in women with osteoporosis.” BMC Musculoskelet Disord. 2025;26(1):381.
  8. 8Ali M, Camacho PM. “Workup and Management of Premenopausal Osteoporosis.” Endocrinol Metab Clin N Am. 2024;53(4):597-606.
EnduranceReady™ Analyzer
Endurance athlete readiness, recovery, and overtraining detection across cardiovascular, training-load, and sleep domains
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  1. 1Gabbett TJ. “The training-injury prevention paradox: should athletes be training smarter and harder?” Br J Sports Med. 2016;50(5):273-280. (Acute-to-chronic workload ratio framework.) doi:10.1136/bjsports-2015-095788
  2. 2Plews DJ, Laursen PB, Stanley J, Kilding AE, Buchheit M. “Training adaptation and heart rate variability in elite endurance athletes.” Int J Sports Physiol Perform. 2013;8(6):688-694.
  3. 3Mujika I, Padilla S. “Scientific bases for precompetition tapering strategies.” Med Sci Sports Exerc. 2003;35(7):1182-1187.
  4. 4Bosquet L, Montpetit J, Arvisais D, Mujika I. “Effects of tapering on performance: a meta-analysis.” Med Sci Sports Exerc. 2007;39(8):1358-1365.
  5. 5Banister EW, Calvert TW. “Planning for future performance: implications for long-term training.” Can J Appl Sport Sci. 1980;5(3):170-176.
IronReady™ Triathlon Analyzer
Multi-discipline triathlon readiness assessment across swim, bike, run, brick, and recovery domains
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  1. 1Gabbett TJ. “The training-injury prevention paradox.” Br J Sports Med. 2016;50(5):273-280. doi:10.1136/bjsports-2015-095788
  2. 2Plews DJ, et al. “Training adaptation and heart rate variability in elite endurance athletes.” Int J Sports Physiol Perform. 2013;8(6):688-694.
  3. 3Bentley DJ, Millet GP, Vleck VE, McNaughton LR. “Specific aspects of contemporary triathlon: implications for physiological analysis and performance.” Sports Med. 2002;32(6):345-359.
  4. 4Mujika I, Padilla S. “Scientific bases for precompetition tapering strategies.” Med Sci Sports Exerc. 2003;35(7):1182-1187.
  5. 5Jeukendrup AE. “Nutrition for endurance sports: marathon, triathlon, and road cycling.” J Sports Sci. 2011;29(sup1):S91-S99. doi:10.1080/02640414.2011.610348
  6. 6Banister EW, Calvert TW. “Planning for future performance.” Can J Appl Sport Sci. 1980;5(3):170-176.
CardioGuard HF™ Heart Failure Assessment
MAGGIC risk score with BNP/NT-proBNP biomarker integration for heart failure evaluation
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  1. 1Pocock SJ, Ariti CA, McMurray JJ, et al. “Predicting survival in heart failure: a risk score based on 39,372 patients from 30 studies.” Eur Heart J. 2013;34(19):1404-1413.
  2. 2Sartipy U, Dahlstrom U, Edner M, Lund LH. “Predicting survival in heart failure: validation of the MAGGIC heart failure risk score in 51,043 patients from the Swedish Heart Failure Registry.” Eur J Heart Fail. 2014;16(2):173-179.
  3. 3Freed BH, et al. “MAGGIC Heart Failure Risk Score: Validation for Morbidity and Mortality in HFpEF.” J Am Heart Assoc. 2018;7(20):e009594.
  4. 4Sato T, et al. “Performance of the MAGGIC heart failure risk score and its modification with the addition of discharge natriuretic peptides.” ESC Heart Failure. 2018;5(4):610-619.
  5. 5Kim KJ, et al. “Validation of the MAGGIC heart failure risk score and the effect of adding natriuretic peptide for predicting mortality after discharge.” PLoS One. 2018;13(11):e0206380.
  6. 6Januzzi JL, et al. “NT-proBNP testing for diagnosis and short-term prognosis in acute destabilized heart failure: an international pooled analysis (ICON study).” Eur Heart J. 2006;27(3):330-337.
  7. 7Maisel AS, et al. “Rapid measurement of B-type natriuretic peptide in the emergency diagnosis of heart failure.” N Engl J Med. 2002;347(3):161-167.
  8. 8Mueller C, McDonald K, de Boer RA, et al. “Practical algorithms for early diagnosis of heart failure and heart stress using NT-proBNP.” Eur J Heart Fail. 2023;25(9):1423-1434.
  9. 9McDonagh TA, Metra M, Adamo M, et al. “2023 Focused Update of the 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure.” Eur Heart J. 2023;44(37):3627-3639.
Environmental Health Risk Calculator
Cumulative exposome assessment across 8 domains, with real-time federal data integration (EPA AirNow, NWS, NASA FIRMS, USGS, NIFC)
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  1. 1World Health Organization. “Air Pollution and Health.” who.int/health-topics/air-pollution
  2. 2U.S. Environmental Protection Agency. “Integrated Science Assessment for Particulate Matter.” EPA/600/R-19/188. 2019.
  3. 3U.S. Environmental Protection Agency. “AirNow Real-Time Air Quality Data.” airnow.gov
  4. 4Agency for Toxic Substances and Disease Registry (ATSDR). “Toxicological Profiles for Lead, Mercury, Cadmium, Arsenic.” atsdr.cdc.gov
  5. 5National Academies of Sciences, Engineering, and Medicine. “Guidance on PFAS Exposure, Testing, and Clinical Follow-Up.” 2022. doi:10.17226/26156
  6. 6American Heart Association. “Air Pollution, the Built Environment, and Cardiovascular Health: Scientific Statement.” Circulation. 2020;141(9):e74-e108.
  7. 7NASA Fire Information for Resource Management System (FIRMS). firms.modaps.eosdis.nasa.gov
  8. 8National Weather Service API. api.weather.gov
  9. 9U.S. Geological Survey Earthquake Hazards Program. earthquake.usgs.gov
  10. 10National Interagency Fire Center (NIFC). data-nifc.opendata.arcgis.com
Epigenetic Clock — TruDiagnostic Partnership
Integrative epigenetic age testing in partnership with TruDiagnostic, leveraging TruAge™, TruHealth™, OMICmAge™, SYMPHONYAge™, DunedinPACE™ algorithms
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  1. 1Horvath S. “DNA methylation age of human tissues and cell types.” Genome Biol. 2013;14(10):R115. doi:10.1186/gb-2013-14-10-r115
  2. 2Levine ME, Lu AT, Quach A, et al. “An epigenetic biomarker of aging for lifespan and healthspan.” Aging (Albany NY). 2018;10(4):573-591.
  3. 3Belsky DW, Caspi A, Corcoran DL, et al. “DunedinPACE, a DNA methylation biomarker of the pace of aging.” eLife. 2022;11:e73420. doi:10.7554/eLife.73420
  4. 4Chen BH, Marioni RE, Colicino E, et al. “DNA methylation-based measures of biological age: meta-analysis predicting time to death.” Aging (Albany NY). 2016;8(9):1844-1865.
  5. 5Higgins-Chen AT, Thrush KL, Wang Y, et al. “A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking.” Nat Aging. 2022;2(7):644-661.
  6. 6Zhang Y, Hannum G, Husain Z, et al. “DNAm-CRP and clinical biomarker correlations.” Clin Epigenetics. 2022;14(1):154. PMC8665430.
  7. 7TruDiagnostic Inc. CLIA-certified laboratory partnership. NIH SBIR Grant 2025 (W-Function research). trudiagnostic.com
  8. 8SYMPHONYAge™ (Yale collaboration), DunedinPACE™ (Duke/Columbia collaboration), 1,670+ Epigenetic Biomarker Proxies (Harvard collaboration), OMICmAge™ — proprietary algorithms validated through peer-reviewed publications.
Integrated Biological Profile (IBP)
Multi-omics integrated profiling combining DNA, epigenetics, microbiome, bloodwork, and wearable data into a unified physician-interpreted assessment
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  1. 1Levine ME, Lu AT, Quach A, et al. “An epigenetic biomarker of aging for lifespan and healthspan.” Aging (Albany NY). 2018;10(4):573-591.
  2. 2Belsky DW, Caspi A, Corcoran DL, et al. “DunedinPACE, a DNA methylation biomarker of the pace of aging.” eLife. 2022;11:e73420. doi:10.7554/eLife.73420
  3. 3Higgins-Chen AT, Thrush KL, Wang Y, et al. “A computational solution for bolstering reliability of epigenetic clocks.” Nat Aging. 2022;2(7):644-661.
  4. 4Lloyd-Price J, Mahurkar A, Rahnavard G, et al. “Strains, functions and dynamics in the expanded Human Microbiome Project.” Nature. 2017;550(7674):61-66. doi:10.1038/nature23889
  5. 5Topol EJ. “High-performance medicine: the convergence of human and artificial intelligence.” Nat Med. 2019;25(1):44-56. doi:10.1038/s41591-018-0300-7
  6. 6Fan J, Krautkramer KA, Feldman JL, Denu JM. “Metabolic regulation of histone post-translational modifications.” ACS Chem Biol. 2015;10(1):95-108.
  7. 7NHLBI. “Atherosclerosis Risk in Communities (ARIC) Study and Multi-Ethnic Study of Atherosclerosis (MESA).” (Multi-system biomarker integration framework.) nhlbi.nih.gov
DoshaBalance™ Constitutional Assessment
AI-powered Ayurvedic constitutional assessment integrating modern genomics, metabolomics, microbiome, and immunology research (34+ peer-reviewed studies)
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  1. 1Aggarwal S, Negi S, Jha P, et al. “EGLN1 involvement in high-altitude adaptation revealed through genetic analysis of extreme constitution types defined in Ayurveda.” Proc Natl Acad Sci USA. 2010;107(44):18961-18966. (CSIR-IGIB TRISUTRA Consortium.) doi:10.1073/pnas.1006108107
  2. 2Govindaraj P, Nizamuddin S, Sharath A, et al. “Genome-wide analysis correlates Ayurveda Prakriti.” Sci Rep. 2015;5:15786. doi:10.1038/srep15786
  3. 3Ghodke Y, Joshi K, Patwardhan B. “Traditional medicine to modern pharmacogenomics: Ayurveda Prakriti type and CYP2C19 gene polymorphism.” Evid Based Complement Alternat Med. 2011;2011:249528.
  4. 4Bhushan P, Kalpana J, Arvind C. “Classification of human population based on HLA gene polymorphism and the concept of Prakriti in Ayurveda.” J Altern Complement Med. 2005;11(2):349-353.
  5. 5Prasher B, Gibson G, Mukerji M. “Genomic insights into Ayurvedic and western approaches to personalized medicine.” J Genet. 2016;95(1):209-228.
  6. 6Prasher B, Mukerji M, et al. “Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda.” PLOS ONE. 2017;12(8):e0181677.
  7. 7Shirolkar AR, Yadav N, Joshi PB, Vetal MV, Tillu G. “Plasma metabolomic profiles in extreme Prakriti types: insights from Ayurveda.” J Ayurveda Integr Med. 2018;9(3):216-222.
  8. 8Mobeen F, Sharma V, Tulika P. “Inferring the gut microbial diversity of Indian and Korean Prakriti subtypes.” Front Microbiol. 2018;9:1820.
  9. 9Chauhan NS, Pandey R, Mondal AK, et al. “Western Indian rural gut microbial diversity in extreme Prakriti endo-phenotypes reveals signature microbes.” Front Microbiol. 2018;9:118.
  10. 10Sharma V, Tulika P, Yadav N, Talwar P, Prasher B, Mukerji M. “Gut microbiome dynamics across constitutional types.” 3 Biotech. 2020;10:200.
  11. 11Rotti H, Mallya S, Kabekkodu SP, et al. “DNA methylation analysis of phenotype specific stratified Indian population.” J Ayurveda Integr Med. 2014;5(2):71-79.
  12. 12Dua A, Mahajan R, Awasthi AA, et al. “Constitutional biomarkers in coronary artery disease: an AIIMS-cohort case-control study.” J Ayurveda Integr Med. 2025 (in press).
  13. 13Singh G, Krishna B, Kumar VR, et al. “Prakriti-based diabetes mellitus risk stratification.” Diseases. 2022;10(4):85.
  14. 14Travis FT, Wallace RK. “Dosha brain-types: a neural model of individual differences.” J Ayurveda Integr Med. 2015;6(4):280-285.
  15. 15Chakraborty S, Prasher B, Mukerji M. “Heart rate variability analysis in healthy individuals stratified by constitutional types.” Physiol Rep. 2022;10(3):e15192.
  16. 16Kim JY. “Pharmacogenomics in Sasang constitutional medicine.” Evid Based Complement Alternat Med. 2011;2011:872798. (Cross-cultural validation: Korean Sasang.)
  17. 17Singh A, Kumar A, et al. “Skin hydration and barrier function across Prakriti types.” J Cosmet Dermatol. 2025 (in press). PMC4654913.
  18. 18Venkatesh BT, Kanchanmala HA, Varun P, et al. “Validation of constitutional assessment tools: a critical review of 64 instruments developed 1987–2024.” Front Med. 2025;12.
  19. 19Dunlap C, et al. “39-item self-assessment Prakriti questionnaire reliability (ICC >0.80).” EXPLORE. 2021.
  20. 20Singh M, et al. “Prakriti200: a standardized Prakriti assessment dataset.” IEEE/CIS. 2025. (Frontiers in Natural Products / Integrative Oncology series.)
  21. 21CCRAS-PAS (Central Council for Research in Ayurvedic Sciences, Ministry of AYUSH, Government of India). “91-predictor Prakriti Assessment Scale, validated across 10 centers with 500 volunteers.”
Mindfulness Rx™ Assessment
FFMQ-SF (Five Facet Mindfulness Questionnaire—Short Form) + PSS-10 (Perceived Stress Scale) dual-instrument assessment with AI-generated clinical interpretation, calibrated for meditators vs non-meditators
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  1. 1Bohlmeijer E, ten Klooster PM, Fledderus M, Veehof M, Baer R. “Psychometric properties of the Five Facet Mindfulness Questionnaire in depressed adults and development of a short form.” Assessment. 2011;18(3):308-320. doi:10.1177/1073191111408231
  2. 2Baer RA, Smith GT, Hopkins J, Krietemeyer J, Toney L. “Using self-report assessment methods to explore facets of mindfulness.” Assessment. 2006;13(1):27-45. doi:10.1177/1073191105283504
  3. 3Cohen S, Williamson G. “Perceived stress in a probability sample of the United States.” In: Spacapan S, Oskamp S, eds. The Social Psychology of Health. Sage; 1988:31-67.
  4. 4Cohen S, Kamarck T, Mermelstein R. “A global measure of perceived stress.” J Health Soc Behav. 1983;24(4):385-396. doi:10.2307/2136404
  5. 5Carpenter JK, Conroy K, Gomez AF, Curren LC, Hofmann SG. “The relationship between trait mindfulness and affective symptoms: a meta-analysis of the Five Facet Mindfulness Questionnaire (FFMQ).” Clin Psychol Rev. 2019;74:101785. doi:10.1016/j.cpr.2019.101785
  6. 6Van Dam NT, Earleywine M, Danoff-Burg S. “Differential item function across meditators and non-meditators on the Five Facet Mindfulness Questionnaire.” Pers Individ Dif. 2009;47(5):516-521. doi:10.1016/j.paid.2009.05.005
  7. 7de Bruin EI, Topper M, Muskens JG, Bögels SM, Kamphuis JH. “Psychometric properties of the Five Facets Mindfulness Questionnaire (FFMQ) in a meditating and a non-meditating sample.” Assessment. 2012;19(2):187-197. doi:10.1177/1073191112446654
  8. 8Aguado J, Luciano JV, Cebolla A, Serrano-Blanco A, Soler J, García-Campayo J. “Bifactor analysis and construct validity of the five facet mindfulness questionnaire (FFMQ) in non-clinical Spanish samples.” Front Psychol. 2015;6:404. doi:10.3389/fpsyg.2015.00404
  9. 9Kim S, Crawford MR, Manber R. “Examining the use of the FFMQ-SF in cognitive behavioral therapy for insomnia.” Mindfulness. 2021;12(11):2733-2743.
  10. 10Sanada K, Díez MA, Valero MS, et al. “Effects of mindfulness-based interventions on biomarkers in healthy and cancer populations: a systematic review.” BMC Complement Altern Med. 2017;17(1):125. doi:10.1186/s12906-017-1638-y
  11. 11Rogerson O, Wilding S, Prudenzi A, O’Connor DB. “Effectiveness of stress management interventions to change cortisol levels: a systematic review and meta-analysis.” Psychoneuroendocrinology. 2024;159:106415. doi:10.1016/j.psyneuen.2023.106415
  12. 12Black DS, Slavich GM. “Mindfulness meditation and the immune system: a systematic review of randomized controlled trials.” Ann N Y Acad Sci. 2016;1373(1):13-24. doi:10.1111/nyas.12998
  13. 13Conklin QA, King BG, Zanesco AP, et al. “Insight meditation and telomere biology: the effects of intensive retreat and the moderating role of personality.” Brain Behav Immun. 2018;70:233-245. doi:10.1016/j.bbi.2018.03.003
  14. 14Schutte NS, Malouff JM. “A meta-analytic review of the effects of mindfulness meditation on telomerase activity.” Psychoneuroendocrinology. 2014;42:45-48. doi:10.1016/j.psyneuen.2013.12.017
  15. 15Chaix R, Alvarez-López MJ, Fagny M, et al. “Epigenetic clock analysis in long-term meditators.” Psychoneuroendocrinology. 2017;85:210-214. doi:10.1016/j.psyneuen.2017.08.016
  16. 16Chaix R, Fagny M, Cosin-Tomás M, et al. “Differential DNA methylation in experienced meditators after an intensive day of mindfulness-based practice.” Brain Behav Immun. 2020;84:36-44. doi:10.1016/j.bbi.2019.11.003
  17. 17Rådmark L, Sidorchuk A, Osika W, Niemi M. “A systematic review and meta-analysis of the impact of mindfulness based interventions on heart rate variability and inflammatory markers.” J Clin Med. 2019;8(10):1638. doi:10.3390/jcm8101638
  18. 18Goyal M, Singh S, Sibinga EM, et al. “Meditation programs for psychological stress and well-being: a systematic review and meta-analysis.” JAMA Intern Med. 2014;174(3):357-368. doi:10.1001/jamainternmed.2013.13018
  19. 19Lieberman MD, Eisenberger NI, Crockett MJ, Tom SM, Pfeifer JH, Way BM. “Putting feelings into words: affect labeling disrupts amygdala activity in response to affective stimuli.” Psychol Sci. 2007;18(5):421-428. doi:10.1111/j.1467-9280.2007.01916.x
  20. 20Neff KD. “The development and validation of a scale to measure self-compassion.” Self Identity. 2003;2(3):223-250. doi:10.1080/15298860309027
Dr. Paul Kilgore, MD, MPH, FACP
Board-Certified Internist & Epidemiologist · 36 Years Clinical Experience
drpaulkilgore.com