Recruitment

Recruitment Status
Completed

Summary

Conditions
Hip Fracture
Type
Observational
Design
Observational Model: CohortTime Perspective: Prospective

Participation Requirements

Age
Between 18 years and 125 years
Gender
Both males and females

Description

Patients with hip fractures admitted to Kongsberg hospital and o Oslo University Hospital between 2008 and 2013 were invited to participate in the study. Hemodynamically unstable patients, patients where it was impossible to obtain a 5 or 10-minute ECG signal (e.g. due to delirium), patients having ...

Patients with hip fractures admitted to Kongsberg hospital and o Oslo University Hospital between 2008 and 2013 were invited to participate in the study. Hemodynamically unstable patients, patients where it was impossible to obtain a 5 or 10-minute ECG signal (e.g. due to delirium), patients having undergone surgery the last month, cancer patients, patients with hip fractures due to high energy trauma, and patients considered moribund at admission, were excluded. A 5-10-minute ECG signal was recorded within 24 hours after arrival preoperatively and digitalized. Heart rate was obtained by a Biocom 3000 ECG recorder (Kongsberg) and a Biocom 4000 ECG recorder (Oslo). The Biocom 3000 and 4000 ECG interface units use dry silver/ silver chloride ECG electrodes attached to the index fingers of the right and the left hand, respectively. Participants were asked to relax for 5 minutes. Afterwards, they were connected to the ECG, and a continuous ECG signal was obtained over 10 minutes (Kongsberg) or 5 minutes (Oslo). Linear parameters (time domain: SDNN, rMSSD; frequency domain: HF, LF, VLF, LF/HF) were calculated by a Heart Rhythm Scanner - Version 2.0 - (Biocom Technologies - U.S.A). Both signal measurement and processing was done according to international recommendations. The investigators analysed HRV both in time domain and frequency domain. Time domain analysis measures the intervals between successive normal cardiac cycles. SDNN (the standard deviation of the NN intervals) reflects all the cyclic components responsible for variability in the period of recording and correlates strongly with total power (TP) of the frequency domain. rMSSD (root mean square successive difference) is calculated by drawing the square root of the mean value of the squared NN intervals. In healthy persons, the rMSSD value is 27 ± 12 ms. It estimates high-frequency variations in heart rate and correlates accordingly mostly with HF in the frequency domain. Changes in this parameter might show a decreased parasympathetic tone and discordance in sympathovagal activity. Frequency domain (power spectral density) analysis describes the periodic oscillations of the heart rate signal, decomposed at different frequencies and amplitudes, and provides information on the amount of their relative intensity (termed variance of power) in the sinus rhythm of the heart. It is calculated with help of power spectral density by the fast Fourier transformation. Frequently reported indices are TP (total power), VLF (very low frequency power, < 0.003 -0.04 Hz), LF (low-frequency power, 0.04-0.15 Hz), HF (high-frequency power, 0.15-0.4 Hz), and the LF/HF ratio. It is recommended not to calculate VLF values from recordings lasting five minutes or less because VLF has a cycle period of 20 seconds to 5 minutes The measurement period should be at least twice as long as the cycle duration. The investigators therefore used only time series of 10 minutes (from the Kongsberg group) for calculation of VLF. All ECGs were manually edited according to the Task force of the European Society of cardiology. If containing more than 30% pathological QRS-complexes, the patients' data were excluded. The sample size was estimated according to reference values reported earlier. The calculation was based on mortality as the most important outcome. Assuming very conservatively a 6-months mortality between 3 and 8%, 150 patients would be sufficient to test the hypothesis that there is a significant association between linear HRV-measurements and mortality. However, the investigators also addressed other incidents than mortality, most of which occur more frequently. In the statistical analysis, the investigators used the independent samples T test for univariate analysis and ANOVA for multivariate analysis. For nominal data, the Chi-Square test or Fisher's exact test were used, as appropriate. In case of very different group sizes (in the case of postoperative pneumonia) the investigators used the nonparametric Mann-Whitney-U-test. Statistical analyses were run by the Statistical Package for Social Sciences (SPSS), release 18.0.3 (September 2010). Values are given in mean +/- SEM if not otherwise stated. Every person in Norway is identified by a unique number in the Central Personal Register. Deceased patients were identified by the Norwegian central address register which provides exact data for the time of death. In addition, patients, close relatives of patients and in some cases their general physicians or nursing home physicians were interviewed six months postoperatively in the Kongsberg group regarding pneumonia, cardiac events and stroke. In the Oslo group patients, close relatives of patients and in some cases their general physicians or nursing home physicians were interviewed regarding pneumonia, cardiac events and stroke within the first six months postoperatively. In both groups the results of the interviews were cross-validated by the hospital journals and - if relevant - nursery home journals regarding new hospital admissions within six months after the operation date. The study protocol was reviewed and approved of the Regional Committee for Medical and Health Research Ethics of Southern Norway (11.1.2008, S-07307b) and the Data Protection Officer of Oslo University Hospital.

Tracking Information

NCT #
NCT03426501
Collaborators
Oslo University Hospital
Investigators
Not Provided