@article {7915, title = {Relationship of Estimated GFR and Albuminuria to Concurrent Laboratory Abnormalities: An Individual Participant Data Meta-analysis in a Global Consortium.}, journal = {Am J Kidney Dis}, year = {2018}, month = {2018 Oct 19}, abstract = {

RATIONALE \& OBJECTIVE: Chronic kidney disease (CKD) is complicated by abnormalities that reflect disruption in filtration, tubular, and endocrine functions of the kidney. Our aim was to explore the relationship of specific laboratory result abnormalities and hypertension with the estimated glomerular filtration rate (eGFR) and albuminuria CKD staging framework.

STUDY DESIGN: Cross-sectional individual participant-level analyses in a global consortium.

SETTING \& STUDY POPULATIONS: 17 CKD and 38 general population and high-risk cohorts.

SELECTION CRITERIA FOR STUDIES: Cohorts in the CKD Prognosis Consortium with data for eGFR and albuminuria, as well as a measurement of hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, or calcium, or hypertension.

DATA EXTRACTION: Data were obtained and analyzed between July 2015 and January~2018.

ANALYTICAL APPROACH: We modeled the association of eGFR and albuminuria with hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, and calcium values using linear regression and with hypertension and categorical definitions of each abnormality using logistic regression. Results were pooled using random-effects meta-analyses.

RESULTS: The CKD cohorts (n=254,666 participants) were 27\% women and 10\% black, with a mean age of 69 (SD, 12) years. The general population/high-risk cohorts (n=1,758,334) were 50\% women and 2\% black, with a mean age of 50 (16) years. There was a strong graded association between lower eGFR and all laboratory result abnormalities (ORs ranging from 3.27 [95\% CI, 2.68-3.97] to 8.91 [95\% CI, 7.22-10.99] comparing eGFRs of 15 to 29 with eGFRs of 45 to 59mL/min/1.73m), whereas albuminuria had equivocal or weak associations with abnormalities (ORs ranging from 0.77 [95\% CI, 0.60-0.99] to 1.92 [95\% CI, 1.65-2.24] comparing urinary albumin-creatinine ratio > 300 vs~< 30mg/g).

LIMITATIONS: Variations in study era, health care delivery system, typical diet, and laboratory assays.

CONCLUSIONS: Lower eGFR was strongly associated with higher odds of multiple laboratory result abnormalities. Knowledge of risk associations might help guide management in the heterogeneous group of patients with CKD.

}, issn = {1523-6838}, doi = {10.1053/j.ajkd.2018.08.013}, author = {Inker, Lesley A and Grams, Morgan E and Levey, Andrew S and Coresh, Josef and Cirillo, Massimo and Collins, John F and Gansevoort, Ron T and Gutierrez, Orlando M and Hamano, Takayuki and Heine, Gunnar H and Ishikawa, Shizukiyo and Jee, Sun Ha and Kronenberg, Florian and Landray, Martin J and Miura, Katsuyuki and Nadkarni, Girish N and Peralta, Carmen A and Rothenbacher, Dietrich and Schaeffner, Elke and Sedaghat, Sanaz and Shlipak, Michael G and Zhang, Luxia and van Zuilen, Arjan D and Hallan, Stein I and Kovesdy, Csaba P and Woodward, Mark and Levin, Adeera} } @article {9637, title = {Development and Validation of the American Heart Association{\textquoteright}s PREVENT Equations.}, journal = {Circulation}, volume = {149}, year = {2024}, month = {2024 Feb 06}, pages = {430-449}, abstract = {

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD.

METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets.

RESULTS: Among 6 612 004 adults included, mean{\textpm}SD age was 53{\textpm}12 years, and 56\% were women. Over a mean{\textpm}SD follow-up of 4.8{\textpm}3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; =0.01).

CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

}, keywords = {Adult, Aged, Albumins, American Heart Association, Atherosclerosis, Cardiovascular Diseases, Creatinine, Female, Glycated Hemoglobin, Heart Failure, Humans, Male, Middle Aged, Risk Assessment, Risk Factors}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.123.067626}, author = {Khan, Sadiya S and Matsushita, Kunihiro and Sang, Yingying and Ballew, Shoshana H and Grams, Morgan E and Surapaneni, Aditya and Blaha, Michael J and Carson, April P and Chang, Alexander R and Ciemins, Elizabeth and Go, Alan S and Gutierrez, Orlando M and Hwang, Shih-Jen and Jassal, Simerjot K and Kovesdy, Csaba P and Lloyd-Jones, Donald M and Shlipak, Michael G and Palaniappan, Latha P and Sperling, Laurence and Virani, Salim S and Tuttle, Katherine and Neeland, Ian J and Chow, Sheryl L and Rangaswami, Janani and Pencina, Michael J and Ndumele, Chiadi E and Coresh, Josef} }