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C a r d i o v a s c u l a r a n d M e t a b o l i c R i s k
O R I G I N A L
Prediction of Mortality Using Measures of
Cardiac Autonomic Dysfunction in the
Diabetic and Nondiabetic Population
The MONICA/KORA Augsburg Cohort Study
AN ZIEGLER, MD, FRCPE
BURKHARD HAASTERT, PHD
HRISTIAN P. ZENTAI, MD
ANGELA D ¨ORING, MD
Cardiovascular autonomic neuropa-
IEGFRIED PERZ, MSC
CHRISTA MEISINGER, MD
OLFGANG RATHMANN, MD, MSPH
FOR THE KORA STUDY GROUP
postural hypotension, exercise intoler-ance, enhanced intraoperative instability,and, presumably, increased incidence of OBJECTIVES — To evaluate whether reduced heart rate variability (HRV), prolonged cor-
silent myocardial infarction and ischemia rected QT (QTc) interval, or increased QT dispersion (QTD) are predictors of mortality in the (1). A number of prospective studies have general diabetic and nondiabetic population.
RESEARCH DESIGN AND METHODS — Nondiabetic (n ϭ 1,560) and diabetic (n ϭ
160) subjects aged 55–74 years were assessed to determine whether reduced HRV, prolonged reduced heart rate variability (HRV) (2).
QTc interval, and increased QTD may predict all-cause mortality. Lowest quartiles for the maximum-minimum R-R interval difference (max-min, as measured at baseline from a 20-s pooled relative risk of mortality in studies standard 12-lead resting electrocardiogram without controlling for depth and rate of respira- tion), QTc Ͼ440 ms and QTD Ͼ60 ms, were used as cutpoints.
or more abnormalities was 3.45 (95% CI2.66 – 4.47) and, in studies that used RESULTS — During a 9-year follow-up, 10.5% of the nondiabetic and 30.6% of the diabetic
more than one measure, 1.20 (1.02–1.41) population deceased. In the nondiabetic individuals, multivariate Cox proportional hazard models adjusted for cardiovascular risk factors and demographic variables showed that pro-longed QTc interval (hazard ratio 2.02 [95% CI 1.29 –3.17]; P ϭ 0.002) but not low max-min studies (3,4) and, hence, subject to refer- (0.93 [0.65–1.34]; P ϭ 0.700), and increased QTD (0.98 [0.60 –1.60]; P ϭ 0.939) were asso- ciated with increased mortality. In the diabetic subjects, prolonged QTc was also a predictor of studies no appropriate adjustment for im- mortality (3.00 [1.34 – 6.71]; P ϭ 0.007), while a trend for an increased risk was noted in those with low max-min (1.74 [0.95–3.18]; P ϭ 0.075), whereas increased QTD did not predict mortality (0.42 [0.06 –3.16]; P ϭ 0.402).
be found in the absence of diabetes as aconsequence of cardiac diseases and is an CONCLUSIONS — Prolonged QTc interval, but not increased QTD, is an independent
predictor of a twofold and threefold increased risk of mortality in the nondiabetic and diabetic elderly general population, respectively. Low HRV during spontaneous breathing tends to beassociated with excess mortality in the diabetic but not nondiabetic population.
lead to increased mortality remain a mat- Diabetes Care 31:556–561, 2008
ter of debate. A meta-analysis revealed a2.3-fold increased risk of CAN in diabeticpatients showing a prolonged QT interval(6), leading to the speculation that CANmight also predispose to malignant ven-tricular arrhythmias and sudden death (7).
● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● From the 1Institute for Clinical Diabetes Research, German Diabetes Center, Leibniz Institute at the Heinrich Heine University, Du¨sseldorf, Germany; the 2Institute of Medical Informatics, Helmholtz ZentrumMu¨nchen - German Research Center for Environmental Health, Neuherberg, Germany; the 3Institute of the longest and shortest QT intervals on a Biometrics and Epidemiology, German Diabetes Center, Leibniz Institute at the Heinrich Heine University, Du¨sseldorf, Germany; and the 4Institute of Epidemiology, Helmholtz Zentrum Mu¨nchen - German Research Center for Environmental Health, Neuherberg, Germany.
variation in ventricular recovery times.
Address correspondence and reprint requests to Dr. Dan Ziegler, FRCPE, Institut fu¨r Klinische Diabe- tologie, Deutsches Diabetes-Zentrum, Leibniz-Zentrum an der Heinrich-Heine-Universita¨t Du¨sseldorf, This spatial dispersion of repolarization Auf’m Hennekamp 65, 40225 Du¨sseldorf, Germany. E-mail: dan.ziegler@ddz.uni-duesseldorf.de.
Received for publication 15 August 2007 and accepted in revised form 11 December 2007.
strate for malignant ventricular arrhyth- Published ahead of print at http://care.diabetesjournals.org on 17 December 2007. DOI: 10.2337/dc07- Abbreviations: ARIC, Atherosclerosis Risk in Communities; CAN, cardiovascular autonomic neuropa-
thy; CVD, cardiovascular disease; ECG, electrocardiogram; HRV, heart rate variability; KORA, Cooperative Health Research in the Region of Augsburg; max-min, maximum-minimum R-R interval difference; MONICA, Monitoring of Trends and Determinants in Cardiovascular Disease; SDNN, SD of R-R intervals.
2008 by the American Diabetes Association.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. tion level. Therefore, these indexes of car- DIABETES CARE, VOLUME 31, NUMBER 3, MARCH 2008 Ziegler and Associates
Table 1—MONICA Survey 1989 –1990 (S2): baseline characteristics
ECG-based variablesECG examination was performed in astandardized manner as described previ- ously (14,15). In brief, a 12-lead resting cient of variation (CV) of R-R intervals, proach was limited by not controlling for respiration and not using an index of HRV determined from the 12-lead ECG strips.
resentative QT interval for further analy- sis. Measurable QT intervals in eight leads Data are means Ϯ SD or percentages unless otherwise indcated. *P Ͻ 0.05; †P ϭ 0.072. CAD, coronary for this definition. QTc interval correction artery disease; MI, myocardial infarction.
formulas for heart rate included the ap-proaches by Bazett (17), the Framingham by the local authorities, and all partici- Heart Study (18), and Fridericia (19).
pants gave written informed consent.
scribed elsewhere in detail (11–13).
graphic variables, smoking habits, physi- RESEARCH DESIGN AND
to atrial fibrillation or flutter (n ϭ 37), left subject who regularly smoked at least one METHODS — The MONICA survey
(n ϭ 38) and right (n ϭ 63) bundle- atrioventricular or sinoatrial block (n ϭ 12), treatment with antiarrhythmic agents, aged 25–74 years (n ϭ 4,940) was se- lected from an original population of n ϭ long the QT interval (n ϭ 48) (multiple sidered physically active if he or she par- tional 47/8 nondiabetic/diabetic subjects 55–74 years were included in the present analysis, of whom n ϭ 160 were classified spectively, and 64/9 nondiabetic/diabetic as having diabetes if they reported a diag- disease (CVD) was defined as the need for val analyses because of multiple supraven- antidiabetes medication, while n ϭ 1,560 tion or stroke (13). Obesity was defined as they did not meet these criteria. All par- subjects were included in the multiple lo- lipidemia was defined as a total–to–HDL DIABETES CARE, VOLUME 31, NUMBER 3, MARCH 2008 Cardiac autonomic dysfunction and mortality
nondiabetic and 140 diabetic subjects as aresulut of incomplete 12 leads.
Statistical methodsAll continuous variables were describedas means Ϯ SD, and differences betweengroups were evaluated by t tests. Categor-ical variables were described by frequencytables and compared between groups us-ing Fisher’s exact test. All tests were per-formed two sided, and the level ofsignificance was set at ␣ ϭ 0.05. Survivalcurves were estimated by the Kaplan-Meier method. The log-rank test was usedto compare different survival curves. Mul-tiple Cox regression models were fitted toanalyze risk factors of mortality and po-tential confounders. Different models us-ing fixed sets of independent variableswere estimated and stratified for diabeticand nondiabetic subjects. The SAS statis-tical software package (version 8.2)TS2M0 was used for statistical analyses.
Figure 1—Kaplan-Meier survival probability for the max-min R-R interval difference (1st quar- tile [broken line] vs. 2nd– 4th quartiles [continuous line]) in the diabetic (A) and nondiabetic (C)cohorts and QTc interval (Ͼ440 ms [broken line] vs. Յ440 ms [continuous line]) in the diabetic diabetic subjects were significantly older, (B) and nondiabetic (D) cohorts. had a higher BMI, faster resting heart rate,higher systolic blood pressure, lower 0.4227)(Fig. 1C). The corresponding mortality rates were 30 of 79 (38.0%) vs.
19 of 80 (23.8%) in diabetic subjects and levels as well as significantly higher pro- interval, male sex, age, regular smoking, infarction or stroke (all P Ͻ 0.05) (Table spectively. In subjects who had a QTc in- (all P Ͻ 0.05) were significant predictors terval Ͼ440 vs. those with a QTc interval of mortality, while CVD tended to predict Յ440 ms, survival probability was signif- mortality (P ϭ 0.076) (Table 2). Among icantly lower in both the diabetic (P Ͻ 0.0001) (Fig. 1B) and nondiabetic (P ϭ terval, male sex, age, and low physical ac- nificantly lower in the diabetic compared mortality (all P Ͻ 0.05), while a trend to with the nondiabetic group (all P Ͻ 0.05).
The use of ␤-blocking agents tended to be smoking and dislipidemia (P ϭ 0.087, to higher in diabetic subjects (P ϭ 0.072).
P ϭ 0.081). The increase in relative risk of and hypertension (all P Ͻ 0.05), but not cholesterol, or the percentage of regular spectively. The results were similar when tended to predict mortality (P ϭ 0.06)(Table 2). Among diabetic individuals, only low physical activity and dyslipide- In the diabetic group, survival probability mia were significant predictors of mortal- ity (both P Ͻ 0.05), while low max-min the max-min R-R interval difference “as age, high alcohol intake, regular smoking, smoking tended to predict mortality (P ϭ 0.067 to P ϭ 0.089). The increase in rel- (all P Ͻ 0.05), but not increased QTD, rate of respiration” (see RESEARCH DESIGN ative risk of mortality for the 1st quartile AND METHODS) at the 1st quartile vs. 2nd– of max-min was 73% in diabetic persons.
(Table 2C). In the diabetic group, age and 4th quartiles (P ϭ 0.0447)(Fig. 1A), low physical activity (both P Ͻ 0.05), but noted in the nondiabetic group (P ϭ DIABETES CARE, VOLUME 31, NUMBER 3, MARCH 2008 Ziegler and Associates
Table 2—Relative risk (RR) (95% CI) for the associations of reduced HRV (max-min), prolonged QTc interval, QTD, cardiovascular risk
factors, and demographic variables with 9-year all-cause mortality in nondiabetic and diabetic individuals

*HRV: nondiabetic group, n ϭ 1,513; nondiabetic group, n ϭ 152. †Prolonged QTc interval: nondiabetic group, n ϭ 1,496; diabetic group, n ϭ 151. ‡QTD:nondiabetic group, n ϭ 1,433; diabetic group, n ϭ 140.
tality over 9 years in the nondiabetic and difference and QTc interval and their pos- sible interaction into the model, QTc in- vascular mortality in the entire cohort and terval prolongation remained a significant 2.14 –7.14]) P Ͻ 0.001, and 4.47 [2.44 – increased risk of mortality. In contrast, risk ratio 2.23 (95% CI 1.32–3.75), P ϭ 9.22], P Ͻ 0.001, respectively) but not in mortality in nondiabetic or diabetic sub- (1.80 –27.94), P ϭ 0.005, in the diabetic P ϭ 0.698). The max-min difference and group, respectively. In contrast, low max- increased risk of mortality by 73% in the tality in either of the groups studied, pos- 1.42]; P ϭ 0.829) but tended to in the diabetic group (1.96 [0.99 –3.89]; P ϭ prognostic index independent of the pres- CONCLUSIONS — The results of
these two variables in predicting mortality this study suggest that prolonged QTc in- be a more specific marker only in the con- terval is an independent predictor of mor- DIABETES CARE, VOLUME 31, NUMBER 3, MARCH 2008 Cardiac autonomic dysfunction and mortality
middle-aged men and 1.4 (0.9 –2.2) in el- Program (35) or 15–30 s in the Zutphen- predicts the risk of mortality in the elderly does not necessarily contradict ours, since tic value of low HRV may therefore differ mortality at the population level (22,23).
activity, hypertension, obesity, dyslipide- and, to a lesser degree, without control- creased QTD in diabetic patients have re- ling for respiration as a result of the re- tion Multinational Study of Vascular Dis- population aged 50 –75 years over 9 years pendent predictors of 9-year mortality in ease in Diabetes, QTc was associated with similar to our cohort aged 55–74 years.
the diabetic elderly general population. In long-term mortality in subjects with type contrast, increased QT dispersion did not diabetes (24). In contrast, in the Strong strating that diminished HRV is a predic- tor of mortality in the diabetic as opposed trend of borderline significance toward an increased risk of mortality by 73% in the cause mortality after a mean follow-up of trast, in the ARIC study (32), low HRV did diabetic population but was not a predic- not predict fatal coronary artery disease or tor of mortality in the nondiabetic elderly of the UK Prospective Diabetes Study, in- non– coronary artery disease mortality in cohort the age range of 45– 64 years was associated with a high risk of excess mor- considerably lower than in our cohort.
tality particularly in diabetic subjects. Re- identified as an independent predictor for c e n t s t u d i e s i n d i c a t e t h a t s o m e total cardiovascular events and for cardiac ours indicate that after adjustment for the deaths among type 2 diabetic patients with various confounding factors, the value of low HRV in predicting excess mortality is only moderate. In line with the borderline was an independent predictor of all-cause independent effect of low max-min differ- nosis in selected patient populations.
and cardiovascular mortality in type 2 di- abetic patients (28). However, these were clinic-based studies and, hence, not rep- resentative of any certain population. We confirm at the population level that pro- measured (31). This risk level may be un- are being used for risk stratification in sion is a predictor of all-cause mortality in majority of the clinic-based studies. In- given that it is simple to do and may rep- analysis that the pooled relative risk of mortality in clinic-based studies that used study results are difficulties in determin- Acknowledgments — The KORA and the
ing the end of the T-wave, the absence of higher than that observed in studies that MONICA Augsburg studies were initiated and financed by the Helmholtz Zentrum Mu¨nchen - rhythm, and the lack of normative data.
atively short period (20 s) of ECG record- Health, which is funded by the German Fed- ing without control for respiration.
eral Ministry of Education, Science, Research and Technology and by the state of Bavaria.
2002–2003 were also supported by grants tality in the nondiabetic population. This dexes from these recordings is relatively from the Federal Ministry of Education, Sci- ence, Research and Technology (01 ER9701/4) and the German Research Founda- study (31) and the Atherosclerosis Risk in ECG leads have been reliably used in sev- tion (DFG) (TH 784/2-1), respectively.
eral other epidemiological studies, e.g., We thank all members of the GSF Institute other hand, in the Zutphen study (33) the of Epidemiology and the field staff in Augs- 5-year age-adjusted relative rate of total burg involved in the planning and conduct of DIABETES CARE, VOLUME 31, NUMBER 3, MARCH 2008 Ziegler and Associates
ter predictors of cardiac death than ankle References
cardiovascular risk factors to cardiac au- 1. Vinik AI, Ziegler D: Diabetic cardiovascu- function tests. Heart 91:44 –50, 2005 lar autonomic neuropathy. Circulation ulation. Exp Clin Endocrinol Diabetes 114: 27. Salles GF, Deccache W, Cardoso CR: Use- fulness of QT-interval parameters for car- 2. Ziegler D: Cardiovascular autonomic neu- 15. Perz S, Po¨ppl SJ, Stieber J: ECG data man- diovascular risk stratification in type 2 ropathy: clinical manifestations and mea- diabetic patients with arterial hyperten- surement. Diabetes Rev 7:342–357, 1999 Survey Augsburg. In Lecture Notes in Med- sion. J Hum Hypertens 19:241–249, 2005 3. Maser RE, Mitchell BD, Vinik AI, Freeman ical Informatics 25, Medical Informatics Eu- 28. Christensen PK, Gall MA, Major-Pedersen rope 1985. Reichertz PL, Lindberg DAB, in individuals with diabetes: a meta-anal- length and QT dispersion as predictors of ysis. Diabetes Care 26:1895–1901, 2003 16. Task Force of the European Society of mortality in patients with non-insulin-de- 4. Astrup AS, Tarnow L, Rossing P, Hansen pendent diabetes. Scand J Clin Lab Invest Heart rate variability: standards of mea- 29. Coumel P, Maison-Blanche P, Badilini F: Dispersion of ventricular repolarization: diabetic patients with diabetic nephropa- and clinical use. Circulation 93:1043– reality? Illusion? Significance? Circulation thy. Diabetes Care 29:334 –339, 2006 5. Suarez GA, Clark VM, Norell JE, Kottke 17. Bazett HC: An analysis of the time-rela- 30. Rautaharju PM: A farewell to QT disper- tions of electrocardiograms. Heart 7:353– Dyck PJ: Sudden cardiac death in diabetes sion: are the alternatives any better? J Elec- mellitus: risk factors in the Rochester di- 18. Sagie A, Larson MG, Goldberg RJ, Bengt- abetic neuropathy study. J Neurol Neuro- 31. Gerritsen J, Dekker JM, TenVoorde BJ, surg Psychiatry 76:240 –245, 2005 6. Whitsel EA, Boyko EJ, Siscovick DS: Re- (the Framingham Heart Study). Am J Car- assessing the role of QTc in the diagnosis autonomic function is associated with in- creased mortality, especially in subjects 19. Fridericia LS: Die Systolendauer im Elek- diabetes: a meta-analysis. Diabetes Care with diabetes, hypertension, or a history und bei Herzkranken. Acta Med Scand 53: 7. Veglio M, Sivieri R, Chinaglia A, Scaglione Study. Diabetes Care 24:1793–1798, 2001 L, Cavallo-Perin P: QT interval prolonga- 32. Liao D, Carnethon M, Evans GW, Cascio 20. de Bruyne MC, Hoes AW, Kors JA, Hofman tion and mortality in type 1 diabetic pa- WE, Heiss G: Lower heart rate variability tients: a 5-year cohort prospective study.
is associated with the development of cor- QT interval predicts cardiac and all-cause Diabetes Care 23:1381–1383, 2000 diabetes: the atherosclerosis risk in com- Study. Eur Heart J 20:278 –284, 1999 much ado about something? Chest 125: munities (ARIC) study. Diabetes 51: 21. Karjalainen J, Reunanen A, Ristola P, Vi- 9. Manttari M, Oikarinen L, Manninen V, Vi- factor in a middle aged population. Heart itasalo M: QT dispersion as a risk factor rate variability from short electrocardio- cardial infarction in a coronary risk pop- ulation. Heart 78:268 –272, 1997 from all causes in middle-aged and elderly 10. WHO MONICA Project Principal Investi- the elderly: the Rotterdam Study. Circula- men: the Zutphen Study. Am J Epidemiol 23. Okin PM, Devereux RB, Howard BV, Fab- 34. Deyneli O, Ersoz HO, Yavuz D, Fak AS, Akalin S: QT dispersion in type 2 diabetic ease): a major international collaboration.
QT interval and QT dispersion for predic- patients with altered diurnal blood pres- J Clin Epidemiol 34:105–114, 1988 tion of all-cause and cardiovascular mor- sure rhythm. Diabetes Obes Metab 7:136 – 11. Keil U, Cairns V, Do¨ring A: MONICA- Heart Study. Circulation 101:61– 66, 2000 35. Carnethon MR, Prineas RJ, Temprosa M, Operations, Survey. In GSF-Bericht 20.
24. Stettler C, Bearth A, Allemann S, Zwahlen 12. Hense HW, Filipiak B, Do¨ring A: Ten- resting heart rate as long-term predictors year trends of cardiovascular risk factors of mortality in type 1 and type 2 diabetes tes, and intervention arm in the Diabetes mellitus: a 23-year follow-up. Diabetolo- Prevention Program. Diabetes Care 29: 1989/90 and 1994/1995 surveys. Cardio- 25. Okin PM, Devereux RB, Lee ET, Galloway 36. Aronson D: Pharmacologic modulation of autonomic tone: implications for the dia- betic patient. Diabetologia 40:476 – 481, Stieber J, Doring A, Lo¨wel H: Sex differ- predict all-cause and cardiovascular mor- ences in risk factors for incident type 2 tality in diabetes: the Strong Heart Study.
37. Ebbehøj E, Arildsen H, Hansen KW, Mo- cohort study. Arch Intern Med 162:82– 89, fects of metoprolol on QT interval and QT dispersion in type 1 diabetic patients with 14. Ziegler D, Zentai C, Perz S, Rathmann W, ers AD: QT interval abnormalities are often abnormal albuminuria. Diabetologia 47: Haastert B, Meisinger C, Lo¨wel H: Selec- present at diagnosis in diabetes and are bet- DIABETES CARE, VOLUME 31, NUMBER 3, MARCH 2008

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49fluidcomp.p65

CHAPTER 49 Fluid complications Frederic W. Grannis, Jr., MD, Lily Lai, MD, James T. Kakuda, MD, and Carey A. Cullinane, MD MALIGNANT PLEURAL EFFUSION Pleural effusion is usually caused by a disturbance of the normal Starling forcesregulating reabsorption of fluid in the pleural space, secondary to obstructionof mediastinal lymph nodes draining the parietal pleura. Tumors that metasta-size

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