Magnetic resonance imaging, image analysis:visual scoring of white matter

Transcription

1 Supplemental method ULSAM Magnetic resonance imaging, image analysis:visual scoring of white matter hyperintensities (WMHI) was performed by a neuroradiologist using a PACS system blinded of baseline data. All scans were assessed with the modified Fazekas scale (1). The scoring of WHMI was divided in categories with increasing severity: grade 0 (no WMHI), grade 1 (mild changes): single lesions <10 mm and/or areas of grouped lesions <20 mm, grade 2 (moderate changes): single lesions mm or grouped areas with no more than connecting bridges >20 mm, grade 3 (severe changes): both single and confluent hyperintense areas of 20 mm in any diameter (Figure 1). The distinction between white matter changes and calcifications were based on the typical appearance of WMHI on MRI with high signal intensity on PD- and T2-weighted images whereas calcifications have a low signal intensity or iso-intensity on T2-weighted images. The likelihood for misclassification when interpreting the changes characterizing WMHI from tissue or vessel calcifications, usually present at different locations, is very low. Outcomes: All medical records from Uppsala University Hospital, Uppsala general practitioners and nursing homes until 1 January 2010 were reviewed, and the diagnoses of dementia were independently assigned by two geriatricians blinded from the baseline data (2). Practically all medical care for the participants had been provided in these settings. In case of disagreement, a third experienced geriatrician reviewed the case and the diagnosis was determined by majority decision. A post-stroke status with major motor sequelae and/or aphasia precluding neuropsychological testing and/or inferring a major impact on daily functions was not classified as dementia (2). 1

2 Supplemental Tables Supplemental Table 1. PIVUS: P-PTH levels according to WMHI category Category N (%) PTH level* (pmol/l) 0 5 (1.2) 4.09 ± (53) 4.90 ± (33) 5.09 ± (9.1) 5.55 ± 2.38 *Values are means (± SD). Non-parametric regression test for trend: coefficient: 3.2 (95% CI, ), p=0.04 2

3 Supplemental Table 2. ULSAM and PIVUS: Relations of plasma PTH to mineral metabolism variables Cohort Variable Rho P-value ULSAM S-Phosphate S-Calcium < P-25-OH vitamin D PIVUS S-Phosphate < S-Calcium P-25-OH vitamin D < Data are Spearman rank correlation coefficients (rho) of the variables on the normal scale. 3

4 Supplemental Table 3. Univariate associations between different covariates to vascular dementia in ULSAM and WMHI in PIVUS. Cohort Variable HR* CI P-value ULSAM PIVUS Log S-phosphate (mmol/l) Log P-PTH (pmol/l) Educational level S-Calcium (mmol/l) P-25-OH vitamin D (nmol/l) Hypertension Diabetes mellitus Smoking BMI (kg/m 2 ) Hypercholesterolemia S-Albumin (g/l) Glomerular filtration rate (ml/min/1.73 m 2 ) Blood draw season rho** S-phosphate (mmol/l) P-PTH (pmol/l) S-Calcium (mmol/l) P-25-OH vitamin D (nmol/l) Hypertension Diabetes mellitus Smoking BMI (kg/m 2 ) Hypercholesterolemia S-Albumin (g/l) Glomerular filtration rate (ml/min/1.73 m 2 ) Blood draw season *Data are unadjusted univariate Cox proportional hazards ratios (95% CI) for a 1 SD log increase of exposure or presence of riskfactors. ** Data are unadjusted univariate Spearman rank correlation coefficients for a 1 SD increase of exposure or presence of risk factor. 4

5 Supplemental Table 4. ULSAM: Relations of plasma PTH to Alzheimer s disease Model Continuous models A Unadjusted B CVD risk factors Model C Mineral metabolism D CVD risk factors + mineral metabolism 1 SD increase 0.87 ( ) 0.88 ( ) 0.88 ( ) 0.90 ( ) Multi-category models T1 (<3.54 pmol/l) Referent Referent Referent Referent T2 ( pmol/l) 0.94 ( ) 0.96 ( ) 0.91 ( ) 1.17 ( ) T3 (>5.96 pmol/l) 0.66 ( ) 0.68 ( ) 0.64 ( ) 0.74 ( ) Threshold models T3 vs. T1-2 (>4.7 pmol/l) 0.68 ( ) 0.70 ( ) 0.67 ( ) 0.67 ( ) T=tertile. Data are Cox proportional hazards ratios (95% CI) for a 1 SD log PTH increase in the following models: A, unadjusted; B, educational level and established risk factors for vascular disease [hypertension, diabetes mellitus, smoking, BMI, hypercholesterolemia]; C, educational level and factors associated with mineral metabolism [S-calcium, S-phosphate, S-albumin, P-25-OH vitamin D <37.5 nmol/l, glomerular filtration rate, blood draw season (winter, summer)]; model D, educational level and models B and C. 5

6 Supplemental Table 5. ULSAM: Population attributable risk proportions for vascular dementia and for risk factors Risk factor PAR (%) Highest tertile of PTH 18.5 Education -11 Obesity 5.0 Hypertension 11 Diabetes mellitus 9.4 Hypercholesterolemia 7.6 Highest tertile of parathyroid hormone: > 4.7 pmol/l. Education: elementary school, secondary school or university studies. Diabetes mellitus: fasting P-glucose 7.0 mmol/l, 2 h post-load glucose 11.1 mmol/l, or the use of oral hypoglycemic agents or insulin. Obesity: body mass index 30 kg/m 2 (weight (kg)/height 2 (m)). Hypertension: systolic blood pressure 140 mmhg and/or diastolic blood pressure 90 mmhg and/or use of antihypertensive medication. Hypercholesterolemia: total serum cholesterol 5 mmol/l, LDL-cholesterol 3 mmol/l or the use of pharmacological treatment for dyslipidemia. Smoking status: current smoking versus no smoking. 6

7 Supplemental Figure 1. Nelson-Aalen plot of cumulative incidence rate of Alzheimer s disease in the whole sample, by two groups (PTH tertiles 1-2 [solid line] vs. tertile 3 [dashed line]). 7

8 References 1. Inzitari D, Pracucci G, Poggesi A et al. Changes in white matter as determinant of global functional decline in older independent outpatients: three year follow-up of LADIS (leukoaraiosis and disability) study cohort. BMJ 2009;339:b Ronnemaa E, Zethelius B, Lannfelt L, Kilander L. Vascular risk factors and dementia: 40-year follow-up of a population-based cohort. Dementia and geriatric cognitive disorders 2011;31: