Linear mixed models for longitudinal data. Textstream; 2000. 28. Allison PD. Missing
data. Thousand Oaks: SAGE Publications; 2001. 29. Little RJA, Rubin DB. Statistical analysis with missing data: New York: Wiley; 2002. 30. Bozdogan H. Model selection and Akaike’s Information Criterion (AIC): the general theory and its analytical extensions. Psychometrika. 1987;52(3):345–70.CrossRef 31. Freitas S, Simoes MR, Alves L, Santana I. Montreal cognitive assessment: validation study for mild cognitive impairment and Alzheimer SAR302503 cost disease. Alzheimer Dis Assoc Disord. 2013;27(1):37–43.selleck chemicals PubMedCrossRef 32. Suh GH, Ju YS, Yeon BK, Shah A. A longitudinal study of Alzheimer’s disease: rates of cognitive and functional decline. Int J Geriatr Psychiatry. 2004;19(9):817–24.PubMedCrossRef 33. Birks J. Cholinesterase inhibitors for Alzheimer’s disease. Cochrane Database Syst Rev. 2006(1):CD005593. 34. de Leeuw FE, de Groot JC,
Oudkerk M, Witteman JC, Hofman A, van Gijn J, et al. Hypertension and cerebral white matter lesions in a prospective cohort study. Brain J Neurol. 2002;125(Pt 4):765–72.CrossRef 35. Warsch JR, Wright CB. Stroke: hyperlipidemia and cerebral small-vessel disease. Nat Rev Neurol. 2010;6(6):307–8.PubMedCrossRef 36. Swartz RH, Sahlas DJ, Black SE. Strategic involvement of cholinergic pathways and executive dysfunction: Does location of white matter signal hyperintensities matter? J Stroke Cerebrovasc Dis. Entinostat 2003;12(1):29–36.PubMedCrossRef 37. Bohnen NI, Muller ML, Kuwabara H, Constantine
GM, Studenski SA. Age-associated leukoaraiosis and cortical cholinergic deafferentation. Neurology. 2009;72(16):1411–6.PubMedCentralPubMedCrossRef”
“Key Points Switching α-glucosidase inhibitors to miglitol reduced glucose fluctuations and circulating cardiovascular disease (CVD) risk factors in type 2 diabetic Japanese patients Reducing glucose fluctuations may reduce the development of CVD in type 2 diabetic patients 1 Introduction Large-scale cohort studies such as Diabetes Epidemiology: Collaborative else analysis of Diagnostic criteria in Europe (DECODE) and FUNAGATA have shown that impaired glucose tolerance (IGT) is strongly associated with subsequent incidence of cardiovascular disease (CVD) [1–3]. The Study TO Prevent Non-insulin-dependent diabetes mellitus (STOP-NIDDM) and Meta-analysis of Risk Improvement under Acarbose (MeRIA7) trials have demonstrated that inhibition of postprandial hyperglycemia by the α-glucosidase inhibitor (α-GI) acarbose reduces pronounced CVD events in subjects with IGT and type 2 diabetes [4, 5]. These results suggest that inhibition of postprandial hyperglycemia, rather than the total rise of glucose throughout the day, in type 2 diabetic patients is important for preventing CVD development.