The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Non-HDL-cholesterol shows improved accuracy for cardiovascular risk score classification compared to direct or calculated LDL cholesterol in a dyslipidemic population
Open accessAbstract
BACKGROUND: Our objective was to evaluate the accuracy of cardiovascular disease (CVD) risk score classification by direct LDL cholesterol (dLDL-C), calculated LDL cholesterol (cLDL-C), and non–HDL cholesterol (non–HDL-C) compared to classification by reference measurement procedures (RMPs) performed at the CDC. METHODS: We examined 175 individuals, including 138 with CVD or conditions that may affect LDL-C measurement. dLDL-C measurements were performed using Denka, Kyowa, Sekisui, Serotec, Sysmex, UMA, and Wako reagents. cLDL-C was calculated by the Friedewald equation, using each manufacturer's direct HDL-C assay measurements, and total cholesterol and triglyceride measurements by Roche and Siemens (Advia) assays, respectively. RESULTS: For participants with triglycerides <2.26 mmol/L (<200 mg/dL), the overall misclassification rate for the CVD risk score ranged from 5% to 17% for cLDL-C methods and 8% to 26% for dLDL-C methods when compared to the RMP. Only Wako dLDL-C had fewer misclassifications than its corresponding cLDL-C method (8% vs 17%; P < 0.05). Non–HDL-C assays misclassified fewer patients than dLDL-C for 4 of 8 methods (P < 0.05). For participants with triglycerides ≥2.26 mmol/L (≥200 mg/dL) and <4.52 mmol/L (<400 mg/dL), dLDL-C methods, in general, performed better than cLDL-C methods, and non–HDL-C methods showed better correspondence to the RMP for CVD risk score than either dLDL-C or cLDL-C methods. CONCLUSIONS: Except for hypertriglyceridemic individuals, 7 of 8 dLDL-C methods failed to show improved CVD risk score classification over the corresponding cLDL-C methods. Non–HDL-C showed overall the best concordance with the RMP for CVD risk score classification of both normal and hypertriglyceridemic individuals.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“As a result, under most circumstances, they provide very similar information about ASCVD risk [45,105-108].”
From 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk (2019) · cites this paper as [107]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Despite this limitation, non-HDLC yields more accurate cardiovascular risk classification than either Friedewald cLDLC or dLDLC, and also more consistent risk scores using different manufacturers' assays for dHDLC in the calculation [58].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [58]
In the citing paper
“In general, LDL-C, non-HDL-C, and ApoB concentrations are very highly correlated.”
From 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk (2019) · cites this paper as [107]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Friedewald, W. T., Levy, R. I., & Fredrickson, D. S. (1972) · Clinical Chemistry · doi:10.1093/clinchem/18.6.499 · Cited by 32,423
Grundy, S. M., Bilheimer, D. W., Chait, A., Clark, L. T., Denke, M. A., Havel, R. J., Hazzard, W. R., Hulley, S. B., Hunninghake, D. B., Kreisberg, R. A., et al. (1993) · JAMA · doi:10.1001/jama.269.23.3015 · Cited by 27,944
Expert Panel on Detection, E. (2001) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.285.19.2486 · Cited by 26,011
Major lipids, apolipoproteins, and risk of vascular disease
The Emerging Risk Factors Collaboration* (2009) · JAMA · doi:10.1001/jama.2009.1619 · Cited by 2,731
Castelli, W. P., Doyle, J. T., Gordon, T., Hames, C. G., Hjortland, M. C., Hulley, S. B., Kagan, A., & Zukel, W. J. (1977) · Circulation · doi:10.1161/01.cir.55.5.767 · Cited by 1,492
Current databases on biological variation: pros, cons and progress
C. Ricós, V. A. (1999) · Scandinavian Journal of Clinical and Laboratory Investigation · doi:10.1080/00365519950185229 · Cited by 987
Ridker, P. M., Rifai, N., Cook, N. R., Bradwin, G., & Buring, J. E. (2005) · JAMA · doi:10.1001/jama.294.3.326 · Cited by 744
Lipoprotein Management in Patients With Cardiometabolic Risk
Brunzell, J. D., Davidson, M. H., Furberg, C. D., Goldberg, R. B., Howard, B. V., Stein, J. H., & Witztum, J. L. (2008) · Diabetes Care · doi:10.2337/dc08-9018 · Cited by 716
Non–High-Density Lipoprotein Cholesterol Level as a Predictor of Cardiovascular Disease Mortality
Cui, Y. A., Blumenthal, R. S., Flaws, J. A., Whiteman, M. K., LANGENBERG, P. W., Bachorik, P. S., & Bush, T. L. (2001) · Archives of Internal Medicine · doi:10.1001/archinte.161.11.1413 · Cited by 657
Ingelsson, E., Schaefer, E. J., Contois, J. H., McNamara, J. R., Sullivan, L., Keyes, M. J., Pencina, M. J., Schoonmaker, C., Wilson, P. W. F., D’Agostino, R. B., et al. (2007) · JAMA · doi:10.1001/jama.298.7.776 · Cited by 608
Research works printed but not linked: 1
- Nauck, 2000, Measurement of high-density-lipoprotein cholesterol, 227
Cited by
Sorted by citations
Mach, F., Baigent, C., Catapano, A. L., Koskinas, K. C., Casula, M., Badimon, L., Chapman, M. J., De Backer, G. G., Delgado, V., Ference, B. A., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehz455 · Cited by 8,961
Mach, F., Baigent, C., Catapano, A. L., Koskinas, K. C., Casula, M., Badimon, L., Chapman, M. J., De Backer, G. G., Delgado, V., Ference, B. A., et al. (2019) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2019.08.014 · Cited by 4,854
Sampson, M. L., Ling, C., Sun, Q., Harb, R., Ashmaig, M., Warnick, R., Sethi, A. A., Fleming, J. K., Otvos, J. D., Meeusen, J. W., et al. (2020) · JAMA Cardiology · doi:10.1001/jamacardio.2020.0013 · Cited by 593
Self-citationLanglois, M. R., Chapman, M. J., Cobbaert, C., Mora, S., Remaley, A. T., Ros, E., Watts, G. F., Borén, J., Baum, H., Bruckert, E., et al. (2018) · Clinical Chemistry · doi:10.1373/clinchem.2018.287037 · Cited by 260
Self-citationNordestgaard, B. G., Langlois, M. R., Langsted, A., Chapman, M. J., Aakre, K. M., Baum, H., Borén, J., Bruckert, E., Catapano, A., Cobbaert, C., et al. (2020) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2019.12.005 · Cited by 246
Self-citationLanglois, M. R., Nordestgaard, B. G., Langsted, A., Chapman, M. J., Aakre, K. M., Baum, H., Borén, J., Bruckert, E., Catapano, A., Cobbaert, C., et al. (2020) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2019-1253 · Cited by 211
Self-citationCole, T. G., Contois, J. H., Csako, G., McConnell, J. P., Remaley, A. T., Devaraj, S., Hoefner, D. M., Mallory, T., Sethi, A. A., & Warnick, G. R. (2013) · Clinical Chemistry · doi:10.1373/clinchem.2012.196733 · Cited by 122
Self-citationFasting versus nonfasting and low-density lipoprotein cholesterol accuracy
Sathiyakumar, V., Park, J., Golozar, A., Lazo, M., Quispe, R., Guallar, E., Blumenthal, R. S., Jones, S. R., & Martin, S. S. (2018) · Circulation · doi:10.1161/circulationaha.117.030677 · Cited by 122
Cerbone, M., Capalbo, D., Wasniewska, M. G., Raso, G. M., Alfano, S., Meli, R., Luca, F. D., & Salerno, M. (2014) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2014-1761 · Cited by 94
APOE2 is associated with longevity independent of Alzheimer’s disease
Shinohara, M., Kanekiyo, T., Tachibana, M., Kurti, A., Shinohara, M., Fu, Y., Zhao, J., Han, X., Sullivan, P. M., Rebeck, G. W., et al. (2020) · eLife · doi:10.7554/elife.62199 · Cited by 82
Miida, T., Nishimura, K., Okamura, T., Hirayama, S., Ohmura, H., Yoshida, H., Miyashita, Y., Ai, M., Tanaka, A., Sumino, H., et al. (2012) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2012.08.022 · Cited by 74
Self-citationLanglois, M. R., Descamps, O. S., van der Laarse, A., Weykamp, C., Baum, H., Pulkki, K., von Eckardstein, A., De Bacquer, D., Borén, J., Wiklund, O., et al. (2014) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2013.12.016 · Cited by 72
Oliveira, M. J. A., van Deventer, H. E., Bachmann, L. M., Warnick, G. R., Nakajima, K., Nakamura, M., Sakurabayashi, I., Kimberly, M. M., Shamburek, R. D., Korzun, W. J., et al. (2013) · Clinica Chimica Acta · doi:10.1016/j.cca.2013.04.009 · Cited by 64
Self-citationCerbone, M., Capalbo, D., Wasniewska, M. G., Alfano, S., Raso, G. M., Oliviero, U., Cittadini, A., Luca, F. D., & Salerno, M. (2016) · European Journal of Endocrinology · doi:10.1530/eje-15-0833 · Cited by 59
Sathiyakumar, V., Park, J., Quispe, R., Elshazly, M. B., Michos, E. D., Banach, M., Toth, P. P., Whelton, S. P., Blumenthal, R. S., Jones, S. R., et al. (2018) · Circulation · doi:10.1161/circulationaha.117.032463 · Cited by 58
Standardization of Apolipoprotein B, LDL‐Cholesterol, and Non‐HDL‐Cholesterol
Contois, J. H., Langlois, M. R., Cobbaert, C. M., & Sniderman, A. D. (2023) · Journal of the American Heart Association · doi:10.1161/jaha.123.030405 · Cited by 57
Homogeneous Assays for LDL-C and HDL-C are Reliable in Both the Postprandial and Fasting State
Miida, T., Nishimura, K., Hirayama, S., Miyamoto, Y., Nakamura, M., Masuda, D., Yamashita, S., Ushiyama, M., Komori, T., Fujita, N., et al. (2017) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.40006 · Cited by 55
Self-citationComparison of equations for the calculation of LDL-cholesterol in hospitalized patients
Martins, J., Olorunju, S. A. S., Murray, L., & Pillay, T. S. (2015) · Clinica Chimica Acta · doi:10.1016/j.cca.2015.01.037 · Cited by 51
Hou, Q., Li, S., Gao, Y., & Tian, H. (2018) · Lipids in Health and Disease · doi:10.1186/s12944-018-0758-9 · Cited by 48
SHAH, A. S., Maahs, D. M., Stafford, J. M., Dolan, L. M., Lang, W., Imperatore, G., Bell, R. A., Liese, A. D., Reynolds, K., Pihoker, C., et al. (2017) · Diabetes Care · doi:10.2337/dc16-2193 · Cited by 47
Dysmetabolic signals in “metabolically healthy” obesity
Manu, P., Ionescu-Tirgoviste, C., Tsang, J. C., Napolitano, B. A., LESSER, M. L., & Correll, C. U. (2011) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2011.04.003 · Cited by 43
My Approach to the Patient With Familial Hypercholesterolemia
Safarova, M. S., & Kullo, I. J. (2016) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2016.04.013 · Cited by 42
Bendžala, M., Sabaka, P., Čaprnda, M., Komorníková, A., Bisahova, M., Baneszova, R., Petrovič, D., Prosecký, R., Rodrigo, L., Kružliak, P., et al. (2017) · Wiener klinische Wochenschrift · doi:10.1007/s00508-017-1264-1 · Cited by 42
Huang, F., Yang, Z., Xu, B., Bi, Y., Xu, M., Xu, Y. H., Lu, J., Liu, Y., Dai, M., Zhou, W., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0054628 · Cited by 40
Desgagné, V., Guay, S., Guérin, R., Corbin, F., Couture, P., Lamarche, B., & Bouchard, L. (2016) · Epigenetics · doi:10.1080/15592294.2016.1176816 · Cited by 39
Work, sleep, and cholesterol levels of U.S. long-haul truck drivers
Lemke, M. K., Apostolopoulos, Y., Hege, A., Wideman, L., & Sönmez, S. (2016) · Industrial Health · doi:10.2486/indhealth.2016-0127 · Cited by 44
The apoB/apoA-I Ratio is a Strong Predictor of Cardiovascular Risk
Walldius, G. (2012) · InTech eBooks · doi:10.5772/47869 · Cited by 36
Dyslipidemia in Children With Arterial Ischemic Stroke: Prevalence and Risk Factors
Sultan, S. M., Dowling, M. M., Kirton, A., deVeber, G., Linds, A. B., Elkind, M. S. V., Bernard, T., Dowling, M. M., Hernández, M., Rivkin, M. J., et al. (2017) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2017.09.019 · Cited by 30
Luo, Y., & Peng, D. (2023) · Journal of Cardiovascular Pharmacology and Therapeutics · doi:10.1177/10742484231189597 · Cited by 30
Vesper, H. W., Wilson, P. W. F., & Rifai, N. (2012) · Clinical Chemistry · doi:10.1373/clinchem.2011.178202 · Cited by 27
Chiu, H., Wu, P.-Y., Huang, J.-C., Tu, H., Lin, M.-Y., Chen, S.-C., & Chang, J.-M. (2020) · Scientific Reports · doi:10.1038/s41598-020-69794-2 · Cited by 26
Use of Apolipoprotein B in the Era of Precision Medicine: Time for a Paradigm Change?
Cole, J., Zubirán, R., Wolska, A. T., Jialal, I., & Remaley, A. T. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12175737 · Cited by 23
Self-citationIkezaki, H., Fisher, V. A., Lim, E., Ai, M., Liu, C., Cupples, L. A., Nakajima, K., Asztalos, B. F., Furusyo, N., & Schaefer, E. J. (2019) · Clinical Chemistry · doi:10.1373/clinchem.2019.304600 · Cited by 23
Self-citationBlood Atherogenicity as a Target for Anti-atherosclerotic Therapy
Sobenin, I. A., Chistiakov, D. A., Bobryshev, Y. V., Postnov, A. Y., & Orekhov, A. N. (2013) · Current Pharmaceutical Design · doi:10.2174/1381612811319330014 · Cited by 23
Kwon, Y., Lee, H., Baik, S. J., Chang, H., & Lee, J. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.824574 · Cited by 20
Langlois, M. R., & Nordestgaard, B. G. (2018) · Current Cardiology Reports · doi:10.1007/s11886-018-1036-1 · Cited by 19
Masana, L., Ibarretxe, D., Heras, M., Cabré, A., Ferré, R., Merino, J., Plana, N., & Girona, J. (2013) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2012.12.001 · Cited by 19
Chung, S. (2017) · Medical Principles and Practice · doi:10.1159/000485977 · Cited by 19
Toprak, K., Kaplangöray, M., Akyol, S., İnanır, M., Memioğlu, T., Taşcanov, M. B., Altıparmak, İ. H., Biçer, A., & Demirbağ, R. (2024) · Acta cardiologica. Supplementum · doi:10.1080/00015385.2023.2299102 · Cited by 18
Low LDL cholesterol—Friend or foe?
Hartz, J. C., Hegele, R. A., & Wilson, D. P. (2019) · Journal of clinical lipidology · doi:10.1016/j.jacl.2019.05.006 · Cited by 17
Huang, Y., Yan, M. Q., Zhou, D., Chen, C. L., & Feng, Y. (2023) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2023.1065750 · Cited by 17
Donato, L. J., Deobald, G. R., Wockenfus, A. M., Hornseth, J. M., Saenger, A. K., & Karon, B. S. (2014) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2014.11.003 · Cited by 17
Enkhmaa, B., Prakash, N., & Berglund, L. (2018) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2018.05.010 · Cited by 17
Yano, M., Matsunaga, A., Harada, S., Zhang, B., Kawachi, E., Tadera, M., & Saku, K. (2019) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.47191 · Cited by 15
Langlois, M. R. (2012) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2011-0636 · Cited by 15
Nakamura, M., Yokoyama, S., Kayamori, Y., Iso, H., Kitamura, A., Okamura, T., Kiyama, M., Noda, H., Nishimura, K., Nakai, M., et al. (2014) · Clinica Chimica Acta · doi:10.1016/j.cca.2014.10.039 · Cited by 15
Self-citationLipoprotein Assessment in the twenty-first Century
Lucero, D., Wolska, A. T., Aligabi, Z., Turecamo, S. E., & Remaley, A. T. (2022) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2022.02.009 · Cited by 16
Self-citationTimón-Zapata, J., Mendieta, E. J. L., Tenor, D. P., Agudo-Macazaga, M., Narros-Cecilia, C., Rocha-Bogas, M. J., Ruíz, G., & Gómez-Serranillos, M. (2011) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2011.09.009 · Cited by 14
Witczak-Sawczuk, K., Ostrowska, L., Cwalina, U., Leszczyńska, J., Jastrzębska-Mierzyńska, M., & Hładuński, M. (2024) · Nutrients · doi:10.3390/nu16091301 · Cited by 17
Nakamura, M., Kiyama, M., Kitamura, A., Ishikawa, Y., Sato, S., Noda, H., & Yoshiike, N. (2012) · Journal of Epidemiology · doi:10.2188/jea.je20120032 · Cited by 13
Self-citationThe evolution of selective analyses of HDL and LDL cholesterol in clinical and point of care testing
Ahmadraji, T., & Killard, A. J. (2013) · Analytical Methods · doi:10.1039/c3ay40715b · Cited by 13
Langlois, M. R., Nordestgaard, B. G., Langsted, A., Chapman, M. J., Aakre, K. M., Baum, H. H. E., Borén, J., Bruckert, É., Catapano, A. L., Cobbaert, C. M., et al. (2021) · Laboratory Service · doi:10.17116/labs20211001145 · Cited by 13
Self-citationComparison of cardiovascular disease risk associated with 3 lipid measures in Japanese adults
Takeuchi, T., Nemoto, K.-I., Takahashi, O., Urayama, K. Y., Deshpande, G. A., & Izumo, H. (2014) · Journal of Clinical Lipidology · doi:10.1016/j.jacl.2014.06.005 · Cited by 12
Mizuno, K., Nakaya, N., Teramoto, T., Yokoyama, S., Ohashi, Y., Ueki, A., Takahashi, S., Kubota, Y., & Nakamura, H. (2011) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.9183 · Cited by 12
Colivicchi, F., Fusco, S. A. D., Arca, M., Leggio, M., Caldarola, P., Murrone, A., Valente, S., Urbinati, S., Roncon, L., Amodeo, V., et al. (2021) · Journal of Cardiovascular Medicine · doi:10.2459/jcm.0000000000001175 · Cited by 13
Lipid changes 8 years post gastric bypass in adolescents with severe obesity (FABS-5+ study)
Shah, A. S., Jenkins, T. M., Gao, Z., Daniels, S. R., Urbina, E. M., Kirk, S., Siegel, R., & Inge, T. H. (2017) · International Journal of Obesity · doi:10.1038/ijo.2017.141 · Cited by 12
Guan, X., Shi, H.-P., Xu, S., Chen, Y., Zhang, R.-F., Dong, Y., Gao, L., Wu, S., & Xia, Y. (2023) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2023.1105342 · Cited by 12
How good is the evidence base for test selection in clinical guidelines?
Misra, S., & Barth, J. H. (2014) · Clinica Chimica Acta · doi:10.1016/j.cca.2014.01.040 · Cited by 11
Fumisawa, Y., Funase, Y., Yamashita, K., Yamauchi, K., Miyamoto, T., Tsunemoto, H., Sakurai, S., & Aizawa, T. (2012) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.13334 · Cited by 11
Zhang, B., Kawachi, E., Matsunaga, A., Imaizumi, S., Noda, K., Uehara, Y., Miura, S.-I., Yoshinaga, K., Kuroki, M., & Saku, K. (2012) · Circulation Journal · doi:10.1253/circj.cj-12-0381 · Cited by 10
Huang, A., Qi, X., Wei, L., Zhang, M., & Zhou, S. (2019) · Cardiology Research and Practice · doi:10.1155/2019/5931975 · Cited by 10
Bilgic, S., & Sniderman, A. D. (2023) · Current Opinion in Cardiology · doi:10.1097/hco.0000000000001100 · Cited by 9
The Importance of Non High Density Lipoprotein Cholesterol in Dyslipidaemia Management
Chowdhury, S., & Chowdhury, J. R. (2015) · Journal of Diabetes & Metabolism · doi:10.4172/2155-6156.1000623 · Cited by 9
Giannakopoulou, S., Antonopoulou, S., Barkas, F., Liberopoulos, E. N., Chrysohoou, C. A., Sfikakis, P. P., Pitsavos, C., Tsioufis, C., & Panagiotakos, D. B. (2025) · European Journal of Clinical Investigation · doi:10.1111/eci.70077 · Cited by 8
Estrategia para el diagnóstico de las dislipidemias. Recomendación 2018
Estébanez, B. C., Mieras, M. P., Romero, C., Ramírez, J. C. V., Salán, M. E., Castro, M. J. C., García, E. R., Velilla, T. A., Calmarza, P., & Puzo, J. (2019) · Revista del Laboratorio Clínico · doi:10.1016/j.labcli.2019.03.001 · Cited by 8
Cardiovascular disease lipids and lipoproteins biomarker standardization
Lyle, A. N., Danilenko, U., Sugahara, O., & Vesper, H. W. (2025) · Critical Reviews in Clinical Laboratory Sciences · doi:10.1080/10408363.2025.2462817 · Cited by 7
Delgado-Alarcón, J. M., Morante, J. J. H., Avilés, F., Albaladejo-Otón, M. D., & Morillas-Ruiz, J. M. (2020) · Nutrients · doi:10.3390/nu12061695 · Cited by 7
Shin, J. H., Cheong, J. I., Cheuh, H. W., & Yoo, J. H. (2020) · Annals of Pediatric Endocrinology & Metabolism · doi:10.6065/apem.2040098.049 · Cited by 7
Bolat, S., Zararsız, G. E., Doğan, K., Koçhan, N., Yerlitaş, S. İ., Cephe, A., Zararsız, G., & Cicero, A. F. G. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12103570 · Cited by 8
Non‐high‐density lipoprotein cholesterol as a cardiovascular risk screening tool in children
Miyazaki, A., Oguri, A., & Ichida, F. (2015) · Pediatrics International · doi:10.1111/ped.12891 · Cited by 7
Non-HDL as a Valid Surrogate Marker of Small Dense LDL in a Young Indian Population
Manocha, A., Bhargava, S., Jain, R., Kankra, M., Singla, P., & Chugh, P. (2018) · Indian Journal of Clinical Biochemistry · doi:10.1007/s12291-018-0758-6 · Cited by 6
Kim, N. H., Lee, J., Chon, S., Yu, J. M., Jeong, I., Lim, S. K., Kim, W. J., Song, K., Cho, H., Yu, H. M., et al. (2024) · Endocrinology and Metabolism · doi:10.3803/enm.2024.1995 · Cited by 6
Second-line treatments for dyslipidemia in patients at risk of cardiovascular disease
Kondo, Y., Hamai, J., Nezu, U., Shigematsu, E., Kamiko, K., Yamazaki, S., Yoshii, T., Takahashi, M. M., Takano, T., Kawasaki, S., et al. (2014) · Endocrine Journal · doi:10.1507/endocrj.ej13-0404 · Cited by 6
Brito, F. A., Pedrosa, W., Maluf, C. B., dos Reis, R. C. P., Fedeli, L., de Castilhos, C. D., Barreto, S. M., & Vidigal, P. G. (2018) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2018.04.007 · Cited by 6
Simultaneous evaluation of fatty acid and triglycerides after percutaneous coronary intervention
Matsumoto, I., Moriya, S., Kurozumi, M., Namba, T., & Takagi, Y. (2022) · Journal of Cardiology · doi:10.1016/j.jjcc.2022.02.011 · Cited by 6
Alarcón, G., Valoy, A., Alzogaray, F. M., Medina, A., Nieuwenhove, C. P. V., Medina, M., & Jerez, S. J. (2024) · Plant Foods for Human Nutrition · doi:10.1007/s11130-024-01193-8 · Cited by 5
Determination of cholesterol in blood. Part 3
Buzanovskii, V. A. (2016) · Review Journal of Chemistry · doi:10.1134/s2079978016030018 · Cited by 5
Levinson, S. S. (2017) · Clinica Chimica Acta · doi:10.1016/j.cca.2017.11.001 · Cited by 5
New joint consensus initiative on quantifying atherogenic lipoproteins
Stock, J. K. (2018) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2018.08.037 · Cited by 4
Nomikos, T., Georgoulis, M., Chrysohoou, C. A., Damigou, E., Barkas, F., Skoumas, I., Liberopoulos, E. N., Pitsavos, C. S., Tsioufis, C. P., Sfikakis, P. P., et al. (2023) · Lipids · doi:10.1002/lipd.12371 · Cited by 4
Performance of HDL-C measurements assessed by a 4-year trueness-based EQA/PT program in China
Zhou, W., Luo, W., Yu, S., Li, H., Wang, D., Zhang, J., Wang, S., Zeng, J., Zhang, C., Zhao, H., et al. (2022) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2020-0658 · Cited by 4
Kidokoro, T., & Miyashita, M. (2020) · The Journal of Physical Fitness and Sports Medicine · doi:10.7600/jpfsm.9.135 · Cited by 4
Yoshida, H. (2017) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.ed076 · Cited by 4
Integrated Measure for Atherogenic Lipoproteins in the Modern Era
Rosenson, R. S., Hegele, R. A., & Gotto, A. M. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.10.059 · Cited by 4
Correlation of C-Peptide and HbA1c in Type II Diabetes Mellitus
Aruna, V. (2021) · International Journal of Research and Review · doi:10.52403/ijrr.20210637 · Cited by 3
Patti, G., Cumitini, L., Bosco, M., Marengo, A., D’Amario, D., Mennuni, M. G., Solli, M., & Grisafi, L. (2025) · International Journal of Cardiology · doi:10.1016/j.ijcard.2025.133327 · Cited by 3
Nasution, M. A. F., Riyanto, H. G., Saepudin, E., & Ivandini, T. A. (2020) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/902/1/012017 · Cited by 3
Risk of misclassification with a non-fasting lipid profile in secondary cardiovascular prevention
Klop, B., Hartong, S. C. C., Vermeer, H. J., Schoofs, M. W. C. J., & Kofflard, M. J. M. (2017) · Clinica Chimica Acta · doi:10.1016/j.cca.2017.07.005 · Cited by 3
Gerique, J. A. G., Ballesteros, B. M., Sardina, R. G., Salán, M. E., Romero, F. F., Puzo, J., Doreste, J. Á. A., Calmarza, P., Vázquez, M. D., & Romero, C. (2011) · Revista del Laboratorio Clínico · doi:10.1016/j.labcli.2011.09.005 · Cited by 3
Pallazola, V. A., Quispe, R., Elshazly, M. B., Vakil, R. M., Sathiyakumar, V., Jones, S. R., & Martin, S. S. (2018) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-018-0590-9 · Cited by 3
Chai, B. K., LAU, Y. S., Loong, B. J., RAIS, M. M., Ting, K., DHARMANI, D. M., & Mohankumar, S. K. (2018) · Physiological Research · doi:10.33549/physiolres.933706 · Cited by 3
Kathariya, G., Aggarwal, J., Nandal, R., & Reddy, S. (2025) · Heart India · doi:10.4103/heartindia.heartindia_77_25 · Cited by 2
Yu, S., Sun, H. Y., & Yoo, B. W. (2023) · Journal of Yeungnam Medical Science · doi:10.12701/jyms.2023.00528 · Cited by 2
Nuwaylati, D. A., & Awan, Z. A. (2024) · Scientific Reports · doi:10.1038/s41598-024-55921-w · Cited by 2
Impact of risk factors on intervened and non-intervened coronary lesions
Sheng, X. (2024) · American Journal of Cardiovascular Disease · doi:10.62347/xtbg3549 · Cited by 2
Altuwalah, A. S., Alfehaid, L., Alhmoud, H., Alrasheedy, A. A., & Alhomoud, I. S. (2025) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s560362 · Cited by 3
Wang, Y., Meng, X., Zhang, X., Li, M., Wang, T., Zhao, Z., Lu, J., Xu, M., Zheng, J., Wang, W., et al. (2026) · Diabetes Obesity and Metabolism · doi:10.1111/dom.70498 · Cited by 1
Importance and Management of Non–High-Density Lipoprotein Cholesterol in Dyslipidemia Treatment
O’Brien, R. C., Santos, L. E. G., Tomlinson, B., Hussein, Z. B., Lim, S., Nawawi, H. M., Ong, H. Y., Silki, S., Soegondo, S., Su, T., et al. (2026) · JACC Asia · doi:10.1016/j.jacasi.2025.12.024 · Cited by 2
Emerging approaches to the examination of lipoproteins for cardio-metabolic risk stratification.
Shokrani, M. (2014) · PubMed · Cited by 1
Laying, egg quality and blood profile of native hens
Zita, L. (2022) · Acta fytotechnica et zootechnica/Acta fytotechnica et zootechnica · doi:10.15414/afz.2022.25.02.109-116 · Cited by 1
Metadata
- Authors
- van Deventer, H. E., Miller, W. G., Myers, G. L., Sakurabayashi, I., Bachmann, L. M., Caudill, S. P., Dziekonski, A., Edwards, S., Kimberly, M. M., Korzun, W. J., Leary, E. T., Nakajima, K., Nakamura, M., Shamburek, R. D., Vetrovec, G. W., Warnick, G. R., & Remaley, A. T.
- Affiliations
- National Institutes of Health, Bethesda, MD
- Virginia Commonwealth University (US)
- Centers for Disease Control and Prevention (US)
- Jichi Medical University (JP)
- Virginia Commonwealth University, Richmond, VA
- Pacific Biomarkers (United States) (US)
- Otsuka (Japan) (JP)
- Osaka Medical Center for Health Science and Promotion, Osaka, Japan
- National Institutes of Health (US)
- Health Diagnostics Laboratory, Richmond, VA
- Corresponding author
- Remaley, Alan T
- ORCID
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-03-01
- Volume
- 57
- Issue
- 3
- Pages
- 490-501
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- PMC
- PMC4684263
- OpenAlex
- W2158071129
- Cited by
- 112
- References
- 39
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 6 · 2023: 10 · 2022: 5 · 2021: 3 · 2020: 9 · 2019: 8 · 2018: 12 · 2017: 10 · 2016: 6 · 2015: 6 · 2014: 9 · 2013: 6 · 2012: 9
- FWCI
- 9.50
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Clinical Chemistry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Genzyme
- Pointe Scientific
- Pacific Biometrics Research Foundation provided
- Virginia Commonwealth University
- National Institutes of Health
- Warren Grant Magnuson Clinical Center
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Health Sciences › Health Professions › Medical Laboratory Technology › Clinical Laboratory Practices and Quality Control
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- non-HDL cholesterol, LDL cholesterol, cardiovascular risk score, dyslipidemia, Friedewald formula, hypertriglyceridemia, assay comparison, reference measurement procedure, misclassification rate
- MeSH terms
- Blood Chemical Analysis, Cardiovascular Diseases, Data Interpretation, Statistical, Fasting, Humans, Cholesterol, HDL, Cholesterol, LDL, Risk Factors, Sensitivity and Specificity, Triglycerides, Ultracentrifugation, Reproducibility of Results, Case-Control Studies, Risk Assessment, Dyslipidemias
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review