Supplementary Online Content
Supplementary Appendix 1. Supplementary Methods Supplementary Appendix 2. Supplementary Results Supplementary Appendix 3. Supplementary Discussion Supplementary References.
Supplementary Appendix 1. Supplementary Methods Study population –selection flow
A total of 50, 912 individuals participated in the NHANES 2003-2012 in-home interview and the medical evaluation at the mobile examination center. The participation rate was 75.2 %. For this study, we initially restricted the analysis to diabetic participants 20 years and older who were receiving anti-diabetic agents (n= 2,961) and further excluded 377 participants who had missing serum creatinine, bicarbonate, albumin, or electrolyte levels (sodium, potassium, and chloride), 6 pregnant participants, and 254 participants with missing covariates of interest (e.g., body mass index, blood pressure or alcohol status). Participants with end stage renal disease (ESRD) as defined by a positive response to the question, “In the past 12 months, have you received dialysis (either hemodialysis or peritoneal dialysis)?”, were also excluded (n=27). The final sample size for analyses was 2,297 participants.
Methods of measuring serum creatinine
Serum creatinine was measured at Collaborative Laboratory Services at Ottumwa, Iowa, using a Beckman Synchron LX20 in 2003-2007 and a Beckman Coulter UniCel DxC800 Synchron in 2008-2012. Both instruments use the Jaffe rate method (kinetic alkaline picrate) to determine creatinine concentrations.1 The method on the DxC800 is isotope dilution mass spectrometry (IDMS) standardized. For the concentration of serum creatinine before 2008, we followed the NHANES analytic recommendations. In NHNAES 2003-2004, there is no need to adjust serum creatinine.2 In NHANES 2005-2006, serum creatinine values were adjusted using the following formula:3
Standard creatinine (mg/dL) = -0.016 + 0.978 (NHANES 05-06 uncalibrated serum creatinine, mg/dL)
For NHANES 2007, the concentration of serum creatinine has been adjusted by a Deming regression and no need for further correction.4
No difference was noted between the two instruments in the reference ranges but there is a significant downward trend across the five NHANES cycles (2003- 2004, 2005-2006, 2007-2008, 2009-2010, and 2011-2012). However, the decrease in the mean value was small (the estimated cycler change in the serum creatinine from one cycle to the following cycle was 0.011 mg/dL) and the trend effect turned out to be insignificant if renal function was modeled by eGFR.
Methods of measuring serum sodium, potassium, chloride, and albumin
Sodium, potassium, chloride were also measured by ISE methods. Albumin was measured using the bichromatic digital endpoint method with a Bromcresol Purple (BCP) reagent.5 The reference ranges and interassay coefficients of variation of these relevant biochemical markers were consistent across five NHANES cycles in the 2003-2012.
Data collection of dietary intake
The NHANES 2003-2012 cycle included two 24-hour dietary recalls and appropriate recall quality was observed in about 92% of total interviewed study participants. Participants were asked to list the types and amounts of all food and beverages consumed during the 24-hour period prior to the exam (midnight to midnight) by NHANES trained dietary interviewers at the mobile examination center following standardized protocols aiming to obtain data representative of usual dietary intake for the US population.6
Data collection of prescription medications
Information on prescription medications was collected during the household interview by trained interviewers using a Computer-Assisted Personal Interviewing (CAPI) system to record the exact product name from the medication container label.7 In NHANES 2003-2012, an average of 80% of all reported drugs was automatically matched to the data collection drug database. Medications that may interfere acid-base status were also obtained including diuretics, angiotensin converting enzyme inhibitors (ACEIs), Angiotensin II receptor blockers (ARBs), nonsteroidal anti-inflammatory drugs(NSAIDs)/cyclooxygenase-2 (COX-2) inhibitor, mineralocorticoids, and drugs that convert to bicarbonate in the liver (e.g., citrate or acetate).
Other variables
Sociodemographic variables collected during the interview included age, race/ethnicity, gender, education, cigarette smoking, and alcohol consumption.
Smoking was categorized as current and non-current (including former or never smoking) by self-report. Alcohol consumption was categorized as never (< 12 drinks in any 1 year in life), former (≥ 12 drinks in any 1 year in life and not drinking now), and current (≥12 drinks in any 1 year in life and drinking now) drinking.
Body mass index was calculated as measured weight in kilograms divided by measured height in meters squared. Hypertension was defined as a self-reported physician diagnosis, use of antihypertensive medication, mean systolic blood pressure > 140 mmHg or mean diastolic blood pressure > 90 mmHg. Chronic lung diseases are defined as an affirmative response to the questions “Do you still have asthma?” or “Has a doctor or other health professional ever told you that you had emphysema?”.
Statistical modeling
Both linear and logistic regression models were adjusted for sociodemographic and lifestyle variables including age(continuous), education (less than high school/high school/higher than high school), race/ethnicity (Non-Hispanic white/ Non-Hispanic black /Mexican-American/Others ), smoking
status(never/former/current), alcohol consumption (never/former/current) , NEAP(continuous), BMI(continuous), serum albumin(continuous) and estimated GFR(continuous). Medication use (binary) including diuretics, ACEI, and ARB were also adjusted.
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Supplementary Appendix 2. Supplementary Results
Prescription pattern of metformin by CKD stages across NHANES survey cycles (2003-2012)
Across five NHANES cycles, the prevalence of metformin use was consistently decreased with the advancing stages of CKD. Only in NHANES cycle 2007- 2008 and 2009-2010, few participants with advanced CKD (stage 4 & 5) were given metformin. This observation supported that the consensus within current practice in US is not to prescribe metformin in diabetes patients with CKD Stage 4 & 5 (Supplementary Figure S1).
Supplementary Appendix 3. Supplementary Discussion
In figure 4, we proposed a risk management model of metformin use in CKD population and focused on risk minimization and characterization. To minimize potential harm, two particular interventions are essential. The first is enhancing physician awareness of the need to vigilantly monitor the renal function following metformin prescription in CKD population. The follow-up scheme regarding kidney function must take comorbidity factors and concomitantly prescribed drugs into account. The metformin dose may need to reduced or discontinued, for example, if the patient also receives drugs predisposing to acute kidney injury, such as NSAID, ACEI/ARB, or radiocontrast. Inzucchi et al. proposed a dosing scheme based mainly on renal function measured by eGFR and this approach actually accord well with current practice in US shown in our analyses.8 From the prevention perspective, evidence gap to be addressed include studies to 1) determine maximal tolerated dose by renal function; 2) evaluate the impact of interactions among metformin, aging, co-morbidities, and other nephrotoxic drugs on metformin toxicity; and 3) define an appropriate renal function follow up frequency specifically for metformin users. The other equally important dimension is patient education and involvement. The priority gaps to be filled include identifying meaningful prodromes related to MALA and diseases that may incline to develop acute kidney deterioration in diabetic patients such as severe dehydration (e.g.,gastroenteritis) and decompensated heart failure. With above information available, patients should be able to self-titrate or even discontinue metformin before seeking professional counseling. A more fundamental issue is that the effectiveness of metformin in diabetics with CKD has not been formally evaluated in terms of clinical outcomes, such as mortality, cardiovascular events, and renal disease progression. If the contraindication for the use of metformin in CKD patients could be removed by FDA, more research is warranted to better inform the assessment of risk-benefit balance.
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Supplementary References:
1. National Center for Health Statistics (NCHS). National Health and Nutrition Examination Survey Data. Laboratory Procedure Manual for Serum Creatinine. In: U.S. Department of Health and Human Services CfDCaP, ed. Hyattsville, MD2012.
2. Collaboration) C-ECKDE. Calibration of NHANES Assays2014.
3. National Health and Nutrition Examination Survey. 2005 - 2006 Data Documentation, Codebook, and Frequencies: Standard Biochemistry Profile (BIOPRO_D). U.S. Department of Health and Human Services, Centers for Disease Control and Prevention,; 2008.
4. National Health and Nutrition Examination Survey. 2007 - 2008 Data Documentation, Codebook, and Frequencies: Standard Biochemistry Profile (BIOPRO_E). U.S. Department of Health and Human Services, Centers for Disease Control and Prevention,; 2010.
5. National Center for Health Statistics (NCHS). National Health and Nutrition Examination Survey Data. Laboratory Procedure Manual for Albumin. In:
U.S. Department of Health and Human Services CfDCaP, ed. Hyattsville, MD2012.
6. Dwyer J, Picciano MF, Raiten DJ, Members of the Steering C, National H, Nutrition Examination S. Collection of food and dietary supplement intake data: What We Eat in America-NHANES. The Journal of nutrition. 2003;133:590S-600S.
7. National Health and Nutrition Examination Survey Data. 2011 - 2012 Data Documentation, Codebook, and Frequencies:Prescription Medications (RXQ_RX_G). 2012. http://wwwn.cdc.gov/nchs/nhanes/2011-2012/RXQ_RX_G.htm.
8. Inzucchi SE, Lipska KJ, Mayo H, Bailey CJ, McGuire DK. Metformin in patients with type 2 diabetes and kidney disease: a systematic review. Jama.
2014;312:2668-75.
Supplementary Figure S1. The trend of prevalence of the metformin use in diabetic participants by CKD stages across NHANES survey cycles (2003- 2012). Abbreviation: eGFR, estimated glomerular filtration rate (ml/min/1.73m2).
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Supplementary Figure S2. Beta coefficients of multiple linear regressions for metformin and other independent variables with serum levels of bicarbonate and anion gap as dependent factors in diabetic participants in NHANES 2003-2012. Abbreviations: ACEI, angiotensin-converting-enzyme inhibitor; ARB, angiotensin receptor blockers; eGFR, estimated glomerular filtration rate; NEAP, net endogenous acid production.
Supplementary Figure S3. Proposed risk management algorithms and research gaps for metformin use in diabetic CKD population. Abbreviations:
ACEI, angiotensin-converting-enzyme inhibitor; AKI, acute kidney injury; ARB, angiotensin receptor blockers; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; NSAID, nonsteroidal anti-inflammatory drugs.
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Supplementary Table S1. Beta coefficients of multiple linear regressions for metformin and other independent variables with serum levels of
bicarbonate and anion gap as dependent factors in diabetic participants in NHANES 2003-2012. Abbreviations: ACEI, angiotensin-converting-enzyme inhibitor; ARB, angiotensin receptor blockers; eGFR, estimated glomerular filtration rate; NEAP, net endogenous acid production.
Bicarbonate Anion gap
Multiple linear repression
coefficient
Multiple linear repression
coefficient Metformin use – 0.45 (-0.73, -0.17) 0.40 (0.19, 0.61) Age (per 10 years) 0.34 (0.22, 0.47) -0.15 (-0.27, -0.03) Sex (reference: male) –0.16 (-0.49, 0.16) 0.19(0.002, 0.39) Race
Non-Hispanic whites Reference Reference
Non-Hispanic blacks 0.20 (-0.13, 0.53) -0.54 (-0.81, -0.27) Mexican Americans – 0.35 (-0.71, 0.002) - 0.17 (-0.55, 0.21)
Others 0.20 (-0.12, 0.52) -0.18 (-0.48, 0.12)
Education
< High school Reference Reference
= High school – 0.09 (-0.41, 0.23) -0.07 (-0.35, 0.21)
>High school – 0.07 (-0.41, 0.26) - 0.05 (-0.36, 0.27) Smoke
Never Reference Reference
Former – 0.27 (-0.56, 0.02) 0.32 (0.06, 0.59)
Current 0.09 (-0.24, 0.42) 0.47 (0.20, 0.75)
NEAP (per 10 mEq/day) – 0.05 (-0.10, 0.003) -0.04 (-0.08, -0.004) Body mass index (per 5
kg/m²)
– 0.12 (-0.21, -0.03) 0.12 (0.04, 0.21) eGFR (per 10 ml/min/1.73m2) 0.20 (0.13, 0.27) - 0.15 (-0.21, -0.09) Albumin (g/dL) 0.40 (-0.04, 0.84) 1.25 (0.91, 1.60) ACEI (reference: no use) – 0.18 (-0.47, 0.11) 0.03 (-0.15, 0.22) ARB (reference: no use) 0.12 (-0.20, 0.44) - 0.06 (-0.37, 0.25) Diuretics (reference: no use) 0.76 (0.50, 1.02) 0.50 (0.26, 0.74)
Supplementary Table S2. Prevalence of metabolic acidosis, high anion gap metabolic acidosis, and severe metabolic acidosis in each CKD stage of the study population. Abbreviation: eGFR, estimated glomerular filtration rate (ml/min/1.73m2). P-value for trend was adjusted for age, sex, race, education, smoke, net endogenous acid production (NEAP), and body mass index (BMI).
Metabolic acidosis (venous bicarbonate
<23 mEq/L)
High anion gap metabolic acidosis (venous bicarbonate
<23 mEq/L & anion gap >16 mEq/L)
Severe acidosis (venous bicarbonate
<20 mEq/L)
n=295 n=144 n=33
eGFR90 (%) 15.0 6.8 1.6
90>eGFR60 (%) 9.8 5.6 0.6
60>eGFR45 (%) 18.6 11.6 2.0
45>eGFR30 (%) 17.9 9.9 0.6
eGFR<30 (%) 27.4 14.8 6.3
Adjusted p-value for trend <0.01 0.04 0.14
Overall prevalence (%) 14.0 7.4 1.3
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Supplementary Table S3. Odds ratios of multiple logistic regression for metformin and other independent variables with metabolic acidosis (venous bicarbonate< 23 mEq/L), high anion gap (venous bicarbonate< 23 mEq/L and anion gap >16 mEq/L), and severe metabolic acidosis (venous
bicarbonate< 20 mEq/L) as dependent factors in diabetic participants in NHANES 2003-2012. Abbreviations: ACEI, angiotensin-converting-enzyme inhibitor; ARB, angiotensin receptor blockers; eGFR, estimated glomerular filtration rate; NEAP, net endogenous acid production.
Metabolic acidosis High anion gap metabolic acidosis
Severe metabolic acidosis Bicarbonate<23
mEq/L
Bicarbonate<23 mEq/L
&
Anion gap >16 mEq/L
Bicarbonate<20 mEq/L
Case/non-case 295 / 2,002 144 / 2,153 33 / 2,264
Multiple logistic regression Odds Ratio
Multiple logistic regression Odds Ratio
Multiple logistic regression Odds Ratio Metformin use 1.38 (1.02, 1.88) 1.68 (1.11, 2.55) 1.31 (0.49, 3.47) Age (per 10 years) 0.85 (0.73, 1.00) 0.89 (0.71, 1.10) 0.71 (0.42, 1.19) Sex (reference: male) 1.10 (0.72, 1.67) 1.00 (0.58, 1.71) 1.52 (0.53, 4.33) Race
Non-Hispanic whites Reference Reference Reference
Non-Hispanic blacks 0.85 (0.57, 1.28) 0.53 (0.28, 0.99) 0.53 (0.19, 1.46) Mexican Americans 1.15 (0.72, 1.83) 0.63 (0.33, 1.21) 0.83 (0.25, 2.78)
Others 1.01 (0.61, 1.69) 0.47 (0.26, 0.86) 1.18 (0.27, 5.19)
Education
< High school Reference Reference Reference
= High school 1.43 (0.86, 2.39) 1.38 (0.82, 2.32) 1.13 (0.34, 3.76) >High school 1.62 (0.93, 2.82) 1.48 (0.83, 2.63) 0.93 (0.21, 4.17) Smoke
Never Reference Reference Reference
Former 1.60 (1.07, 2.40) 1.65 (1.11, 2.45) 1.22 (0.41, 3.63)
Current 1.08 (0.62, 1.88) 0.88 (0.43, 1.79) 1.52 (0.44, 5.28)
NEAP (per 10 mEq/day) 1.02 (0.97, 1.08) 0.96 (0.87, 1.05) 0.85 (0.68, 1.05) Body mass index (per 5
kg/m²)
1.18 (1.07, 1.31) 1.34 (1.17, 1.55) 1.08 (0.79, 1.47) eGFR (per 10
ml/min/1.73m2)
0.88 (0.80, 0.97) 0.86 (0.75, 0.97) 0.90 (0.67, 1.22) Albumin (g/dL) 0.78 (0.42, 1.43) 1.12 (0.54, 2.34) 0.12 (0.02, 0.86) ACEI (reference: no use) 0.97 (0.63, 1.50) 1.31 (0.80, 2.16) 1.02 (0.27, 3.85) ARB (reference: no use) 0.83 (0.55, 1.24) 1.02 (0.63, 1.64) 0.70 (0.26, 1.93)
Diuretics (reference: no use)
0.70 (0.45, 1.09) 0.90 (0.52, 1.55) 0.70 (0.26, 1.89)
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