Study On The Effect Of Job Burnout On The Prognosis Of Acute Coronary Syndrome In Working Population

Objective:It was a prospective study based on the hospital.Working population with the first episode of acute coronary syndrome(ACS)was taken as study object.Their burnout and work stress levels were assessed before discharge.Then they were followed up by physical condition,quality of life(QoL),and heart rate variability(HRV)during half a year after discharge.The aim of the study was to estimate the effect of burnout on the prognosis of ACS in working population.Methods:1.Subjects were patients with first episode of ACS,who had a fixed occupation or have retired:5?2 years.ACS included unstable angina,non-ST-segment elevation myocardial infarction,and ST-segment elevation myocardial infarction,which was verified by coronary angiography.2.Demographic and clinical data,such as work situation,age,sex,education level,family information,and ACS type,Killip class,medical history,family history,smoking,alcohol,serum biochemicals,etc.,were collected from interviews and medical records.3.The Copenhagen Burnout Inventory(CBI)was used to evaluate the burnout level of the subject during the hospitalization period after the condition is stabilized,and the Job Content Questionnaire(JCQ)and Effort-Reward Imbalance Questionnaire(ERI)were used to evaluate the work stress level of the subject.The Anxiety and Depression levels of the subjects were assessed by the Hospital Anxiety and Depression Scale(HADS).HRV was measured by 24-hour ambulatory electrocardiography and analyzed in time and frequency domains.4.The subjects were followed up 1 month and 6 months after discharge.HRV,QoL,and physical condition were assessed repeatedly during the follow-up.QoL was evaluated using the universal Outcomes Study 8-item Short Form(sf-8)and the CHD specificity scale Seattle Angina Questionnaire(SAQ).Short Physical Performance Battery(SPPB)was used to evaluate the Physical recovery of the subjects.5.Data were analyzed by Stata 10.0 statistical software packages.Continuous variables were presented as mean values,and discrete variables were presented as frequencies and percentages.The Student's t-test was applied to compare the differences of job burnout between the high work stress group and low work stress group.Generalized estimating equations(GEE)for repeat measurement were developed to determine the association between job burnout and physical condition,QoL,and HRV parameters,respectively.A p<0.05(two-sided)was considered statistically significant.Results:1.57 subjects were included in this study.There are 50 males and 7 females with an average age of 46.456±7.755 years old.2.High work stress group and low work stress group was based on JCQ and ERI respectively.The t-test showed that:JCQ:the burnout score was49.55±2.62inhigh work stress group vs.36.60±2.66 in low work stress group.The difference was significant(t=-3.4652,P=0.001).ERI:the burnout score in high work stress group and low work stress group respectively was 51.200±2.77 vs.37.36±2.47.The difference was statistically significant(t=?3.701,p=0.0005).3.After adjustment for potential confounding factors,the GEE coefficient of baseline burnout score by SPPB was-0.014.The 95%confidence interval(Cl)were-0.027 to-0.000.The difference was statistically significant(Z=-2.06,P=0.040).4.The GEE coefficient of baseline burnout score by SF-8 physical function score during half a year follow-up period was-0.114(95%CI-0.200,-0.028).The difference was statistically significant after adjustment for confounding factors(Z=-2.60,P=0.009).The GEE coef:ficient of burnout by SF-8 psychological function score was-0.070(95%CI-0.145,0.006).The difference was not significant(Z=-1.79,P=0.073).5.After adjustment for confounding factors,the GEE coefficients of baseline burnout by five dimensions of SAQ were:PL[coefficient=0.008,95%CI(-0.1 55,0.17),Z=0.10,P=0.921],AS[coefficient=0.092,95%CI(-0.137,0.320),Z=0.79,P=0.431],AF[coefficient=-0.218,95%CI(-0.373,-0.052),Z=-2.60,P=0.009],TS[coefficient=-0.266,95%CI(-0.446,-0.087),Z=-2.90,P=0.004].6.After adjustment for confounding factors,the GEE coefficients of baseline burnout by HRV parameters were:Ln(SDNN)[coefficient=-0.009,95%CI(-0.016,-0.0.002),Z=-2.43,P=0.015],Ln(RMSSD)[coefficient=-0.014,95%CI(-0.026,-0.002),Z=-2.31,P=0.021],Ln(SDANN)[coefficient=-0.005,95%CI(-0:011,0.002),Z=-1.43,P=0.153],Ln(TP)[coefficient=-0.023,95%CI(-0.040,-0.005),Z=2.49,P=0.013],Ln(ULF)[coefficient=-0.016,95%CI(-0.031,-0.001),Z=-2.04.p=0.042],Ln(VLF)[coefficient=-0.016,95%CI(-0.030,-0.002),Z=-2.24,P=0.025](HF),Ln(LF)[coefficient=-0.011,95%CI(-0.033,0.010),Z=-1.04,P=0.297],Ln(HF)[coefficient=-0.017,95%CI(-0.043,0.008),Z=-1.32,P=0.188).Conclusion(s):The following conclusions were drawn through this half a year follow-up:1.Burnout can reflect job stress.The high the burnout indicates the high work stress.2.Job burnout is negatively correlated with ACS physical recovery in the working population.The higher the burnout score,the lower the physical activity;3.Job burnout affects working population's quality of life negatively after ACS,including physical function reducing,angina frequency increasing,and treatment satisfaction decreasing.The higher the job burnout,the lower the quality of life;4.Job burnout affects the heart rate variability of the working population negatively after ACS,including time-domain indexes SDNN and RMSSD,as well as frequency-domain indexes TP,ULF and VLF.