TY - GEN
T1 - Holter registers and metabolic syndrome
AU - Munõz-Diosdado, A.
AU - Ramírez-Hernández, L.
AU - Aguilar-Molina, A. M.
AU - Zamora-Justo, J. A.
AU - Gutiérrez-Calleja, R. A.
AU - Virgilio-González, C. D.
N1 - Publisher Copyright:
© 2014 AIP Publishing LLC.
PY - 2014
Y1 - 2014
N2 - There is a relationship between the state of the cardiovascular system and metabolic syndrome (MS). A way to diagnose the heart state of a person is to monitor the electrical activity of the heart using a 24 hours Holter monitor. Scanned ECG signal can be analyzed beat-by-beat by algorithms that separate normal of abnormal heartbeats. If the percentage of abnormal heartbeats is too high it could be argued that the patient has heart problems. We have algorithms that can not only identify the abnormal heartbeats, but they can also classify them, so we classified and counted abnormal heartbeats in patients with MS and subjects without MS. Most of our patients have large waist circumference, high triglycerides and high levels of LDL (high-density lipoprotein) cholesterol although some of them have high blood pressure. We enrolled adult patients with MS free of diabetes in a four month lifestyle intervention program including diet and physical aerobic exercise, and compared with healthy controls. We made an initial registration with a Holter, and 24 hours ECG signal is analyzed to identify and classify the different types of heartbeats. The patients then begin with diet or exercise (at least half an hour daily). Periodically Holter records were taken up and we describe the evolution in time of the number and type of abnormal heartbeats. Results show that the percentage of abnormal heartbeats decreases over time, in some cases the decline is very significant, and almost a reduction to half or less of abnormal heartbeats after several months since the patients changed their eating or physical activity habits.
AB - There is a relationship between the state of the cardiovascular system and metabolic syndrome (MS). A way to diagnose the heart state of a person is to monitor the electrical activity of the heart using a 24 hours Holter monitor. Scanned ECG signal can be analyzed beat-by-beat by algorithms that separate normal of abnormal heartbeats. If the percentage of abnormal heartbeats is too high it could be argued that the patient has heart problems. We have algorithms that can not only identify the abnormal heartbeats, but they can also classify them, so we classified and counted abnormal heartbeats in patients with MS and subjects without MS. Most of our patients have large waist circumference, high triglycerides and high levels of LDL (high-density lipoprotein) cholesterol although some of them have high blood pressure. We enrolled adult patients with MS free of diabetes in a four month lifestyle intervention program including diet and physical aerobic exercise, and compared with healthy controls. We made an initial registration with a Holter, and 24 hours ECG signal is analyzed to identify and classify the different types of heartbeats. The patients then begin with diet or exercise (at least half an hour daily). Periodically Holter records were taken up and we describe the evolution in time of the number and type of abnormal heartbeats. Results show that the percentage of abnormal heartbeats decreases over time, in some cases the decline is very significant, and almost a reduction to half or less of abnormal heartbeats after several months since the patients changed their eating or physical activity habits.
UR - http://www.scopus.com/inward/record.url?scp=84911459503&partnerID=8YFLogxK
U2 - 10.1063/1.4901381
DO - 10.1063/1.4901381
M3 - Contribución a la conferencia
AN - SCOPUS:84911459503
T3 - AIP Conference Proceedings
SP - 151
EP - 154
BT - AIP Conference Proceedings
A2 - Guzman-Cabrera, Rafael
A2 - Bernal-Alvarado, Jose de Jesus
A2 - Brandan, Maria-Ester
PB - American Institute of Physics Inc.
T2 - 13th Mexican Symposium on Medical Physics
Y2 - 15 March 2014 through 16 March 2014
ER -