COMPUTATION OF MODEL-DEPENDENT TOLERANCE BANDS FOR AMBULATORILY MONITORED BLOOD PRESSURE

REFERENCES

• Association for the Advancement of Medical Instrumentation. American National Standard for Electronic or Automated Sphygmomanometers. AAMI, Washington, DC 1987
   Google Scholar
• Bingham C, Arbogast B, Cornélissen G, et al. Inferential statistical methods for estimating and comparing cosinor parameters. Chronobiologia 1982; 9: 397–439
   PubMedGoogle Scholar
• Cornélissen G. Instrumentation and data analyis methods needed for blood pressure monitoring in chronobiology. Chronobiotechnology and chronobiological engineering, L E Scheving, F Halberg, C F Ehret. NATO ASI Series No 120, Martinus Niijhoff, DordrechtThe Netherlands 1987; 241–61
   Google Scholar
• Cornélissen G, Haus E, Halberg F. Chronobiologic blood pressure assessment from womb to tomb. Biologic rhythms in clinical and laboratory medicine, Y Touitou, E Haus. Springer-Verlag, Berlin 1992; 428–52
   Google Scholar
• Efron B. The jacknife, the bootstrap and other resampling plans. SIAM, Philadelphia, Pennsylvania 1982; 92
   Google Scholar
• Efron E, Tibshirani R J. An introduction to bootstrap. Chapman and Hall, New York 1993
   Google Scholar
• Fernández J R. Estimación de límites de tolerancia en series temporales híbridas no equidistantes. Ph.D. dissertation, Universidad de Santiago, Spain 1992
   Google Scholar
• Fernández J R. Nonparametric method for comparison of parameters from rhythmometrics models with multiple components. Biol Rhythm Res 1995; 26: 387
   Google Scholar
• Fernández J R, Hermida R C. Inferential statistical method for analysis of nonsinusoidal hybrid time series with unequidistant observations. Chronobiol Int. 1998; 15: 191–204
   PubMed Web of Science ®Google Scholar
• Halberg F, Lee J K, Nelson W L. Time-qualified reference intervals-chronodesms. Experientia 1978; 34: 713–16
   PubMedGoogle Scholar
• Hermida R C. Time-qualified reference values for 24 h ambulatory blood pressure monitoring. Blood Press Monit 1999; 4: 137–47
   PubMedGoogle Scholar
• Hermida R C, Ayala D E. Diagnosing gestational hypertension and preeclampsia with the 24-hour mean of blood pressure. Hypertension 1997; 30: 1531–37
   PubMed Web of Science ®Google Scholar
• Hermida R C, Ayala D E, Fernández J R, et al. Time-specified reference limits for ambulatorily monitored blood pressure in clinical health. Biomed Instrum Technol. 1993; 27: 235–43
   PubMedGoogle Scholar
• Hermida R C, Ayala D E, Mojón A, et al. High sensitivity test for the early diagnosis of gestational hypertension and preeclampsia. IV. Early detection of gestational hypertension and preeclampsia by the computation of a hyperbaric index. J Perinat Med. 1997; 25: 254–73
   PubMed Web of Science ®Google Scholar
• Hermida R C, Ayala D E, Mojón A, et al. Blood pressure excess for the early identification of gestational hypertension and preeclampsia. Hypertension 1998; 31: 83–89
   PubMed Web of Science ®Google Scholar
• Hermida R C, Fernández J R. Computation of time-specified tolerance intervals for ambulatorily monitored blood pressure. Biomed Instrum Technol. 1996; 30: 257–66
   PubMedGoogle Scholar
• Hermida R C, Fernández J R, Alonso I, et al. Computation of time-specified tolerance intervals for hybrid time series with nonequidistant sampling, illustrated for plasma growth hormone. Chronobiol Int. 1997; 14: 409–25
   PubMed Web of Science ®Google Scholar
• Hermida R C, Fernández J R, Mojón A. High sensitivity test for the early diagnosis of gestational hypertension and preeclampsia. III. Computation of time-specified tolerance intervals as reference for blood pressure excess in the diagnosis of gestational hypertension. J Perinat Med. 1997; 25: 237–53
   PubMed Web of Science ®Google Scholar
• Hermida R C, Fernández J R, Mojón A, et al. Reproducibility of the hyperbaric index as a measure of blood pressure excess. Hypertension 1999; 35: 118–25
   Web of Science ®Google Scholar
• Hermida R C, Mojón A, Fernández J R, et al. Computer-based medical system for the computation of blood pressure excess in the diagnosis of hypertension. Biomed Instrum Technol. 1996; 30: 267–83
   PubMedGoogle Scholar
• Lemmer B. Cardiovascular chronobiology and chronopharmacology. Biologic rhythms in clinical and laboratory medicine, Y Touitou, E Haus. Springer-Verlag, Berlin 1992; 418–27
   Google Scholar
• Millar-Craig M W, Bishop C N, Raftery E B. Circadian variation of blood pressure. Lancet 1978; 1: 795–97
   PubMed Web of Science ®Google Scholar
• Mojón A, Fernández J R, Hermida R C. Chronolab: an interactive software package for chronobiologic time series analysis written for the Macintosh™ computer. Chronobiol Int. 1992; 9: 403–12
   PubMed Web of Science ®Google Scholar
• Nelson W, Cornélissen G, Hinkley D, et al. Construction of rhythm-specified reference intervals and regions, with emphasis on “hybrid” data, illustrated for plasma cortisol. Chronobiologia 1983; 10: 179–93
   PubMedGoogle Scholar
• Nelson W, Tong Y L, Lee J K, et al. Methods for cosinor rhythmometry. Chronobiologia 1979; 6: 305–23
   PubMedGoogle Scholar
• Staessen J, Fagard R, Lijnen P, et al. Ambulatory blood pressure monitoring in clinical trials. J Hypertens 1991; 9(1)s13–s19
   Google Scholar
• Whelton A, Miller W E, Dunne B, et al. Once-daily lisinopril compared with twice-daily captopril in the treatment of mild to moderate hypertension: assessment of office and ambulatory blood pressures. J Clin Pharmacol 1990; 30: 1074–80
   PubMed Web of Science ®Google Scholar
• White W B, Lund-Johansen P, McCabe E J. Clinical evaluation of the Colin ABPM 630 at rest and during exercise: an ambulatory blood pressure monitor with gas-powered cuff inflation. J Hypertens. 1989; 7: 477–83
   PubMed Web of Science ®Google Scholar
• World Health Organization. 1986 guidelines for study of mild hypertension. Bull WHO 1986; 64: 31–35
   PubMed Web of Science ®Google Scholar
• World Health Organization—International Society of Hypertension. WHO-ISH guidelines for the management of mild hypertension. Clin Exp Hypertens 1989; A-11: 1203–16
   Web of Science ®Google Scholar
• Zachariah P K, Sheps S G, Ilstrup D M, et al. Blood pressure load—a better determinant of hypertension. Mayo Clin Proc. 1988; 63: 1085–91
   PubMed Web of Science ®Google Scholar
• Zachariah P K, Sheps S G, Schwartz G L, et al. Antihypertensive efficacy of lisinopril: ambulatory blood pressure monitoring. Am J Hypertens 1988; 1: 274S–79S
   Web of Science ®Google Scholar