Associations of mood symptoms with NYHA functional classes in angina pectoris patients: a cross-sectional study

This is a cross-sectional study for investigating the discrepancies of mood symptoms of Chinese patients in different coronary condition and CHD subtypes and the determinants for depression and anxiety. 705 consecutive inpatients with primary diagnosis of CHD at admission in Guangdong Provincial People’s Hospital were surveyed between October 2017 and January 2018. Results of clinical tests and coronary angiography (CAG) as well as discharge diagnosis were acquired from medical records to ensure the correct patient categorization (Fig. 1). Chinese version of PHQ-9, GAD-7 and a self-designed short questionnaire about valuable information were applied. All participants were surveyed in comparatively stable condition and under supervision of one well-trained psycho-cardiologist, who was responsible for elucidating the PHQ-9 and GAD-7 questionnaires, assisting patients with failing eyesight or low literacy and conducting a concise review to guarantee data accuracy.

The current paper concerns a cross-sectional analysis of the baseline status of the angina pectoris inpatients. Inpatients with main discharge diagnosis of angina pectoris and a history of coronary artery bypass grafting or coronary stent implantation or with at least one narrow epicardial coronary artery (≥50%) confirmed by CAG during this hospitalization were included. Participants with severe valvular heart disease, or severe cardiomyopathy unlikely caused by coronary stenosis, or other complications that might interfere the mechanism that symptoms were primarily resulted from the narrowed coronary were excluded, leaving a sample of 443 subjects (187 SAP and 256 UAP according to Braunwald criteria [23]) into analysis (Fig. 1). The study was approved by the Medical Ethics Committee of Guangdong Provincial People's Hospital. Written informed consent were obtained from all participants.

NYHA classification [11] is a widely used clinical tool that measures the cardiac functional capacity. The assessment of NYHA class was mainly based on the medical records at admission. However, for the missing data, two cardiologists separately estimated the NYHA class and discussed with a third doctor if inconsistence appeared. To unify the criteria, we defined that conditions triggering fatigue, palpitation, dyspnea, or anginal pain of NYHA class III patients were walking 20–100 m or climbing one flight of stairs at normal pace.

The PHQ-9 is a valid screening tool for depression in accordance with DSM-IV criteria for major depressive disorder (MDD) [24, 25]. The 9 items which evaluate the depression symptoms are rated on a 0–3 Likert-type scale with higher score on each item representing more frequently being bothered by the symptom in the last 2 weeks. It has been demonstrated to be a reliable predictor of depression severity with mild, moderate, moderately severe to severe depression corresponding to a score of 5, 10 and 15, respectively [24]. PHQ-9 score ≥ 10 indicates clinical depression and has a sensitivity of 88% and a specificity of 88% for major depression [25]. Given the fact that even mild depression symptom classified by PHQ-9 is associated with a worse prognosis of cardiac patients [26], clinical characteristics between subjects with PHQ-9 score < 5 and ≥ 5 have also been compared. The Chinese version of PHQ-9 has been validated in Chinese cardiac patients [27].

A number of researches have proved that PHQ-9 has two-factor structure and can be divided into somatic and cognitive depression symptom subscales. To be accurate, we listed 5 representative models (one-factor model: Model 1 [28]; four two-factor models: Model 2a [29‐31], Model 2b [18, 19, 21], Model 2c [32‐34], Model 2d [30]) (see Additional file 1: Table S1), and implemented confirmatory factor analysis (CFA) with items as continuously-scaled and maximum likelihood estimation with a mean-adjustment analysis method for non-normality data using Mplus 7 software. Model 2c turned out to be the best model with fit indices indicating adequately fit [35]. Internal consistency coefficients (Cronbach’s α) were 0.76 for factor 1 (somatic) and 0.79 for factor 2 (cognitive). The error-free factors were correlated at 0.85. We accordingly calculated the sum scores of the two dimensions as factor scores (somatic and cognitive).

GAD-7 is a 7-item self-report scale based on DSM-IV criteria [36]. Items of GAD-7 are also rated on a 0–3 Likert-type scale. It measures the severity of generalized anxiety disorders and also exhibits good convergent validity when compared with other commonly-used anxiety scales [37]. Total score ranges from 0 to 21 with a score of 0–4, 5–9, 10–14, 15–21 representing normal, mild, moderate and severe levels of anxiety, respectively. Analogously, GAD-7 score ≥ 10 indicates clinical anxiety, since the sensitivity and specificity for generalized anxiety disorder reached 89 and 82%, respectively. The minimal clinical important difference has not been established. Considering the widely use of the cutoff of 5 to distinguish patients from normal state, differences between patients with GAD-7 score < 5 and ≥ 5 have also been compared. The Chinese version of GAD-7 has been validated in Chinese cardiac patients [38]. Previous studies have shown the underlying structure of GAD-7 to be unidimension [37, 39].

Coronary artery stenosis severity was assessed according to the number of three main vessels with stenosis ≥50% as shown by angiography. However, a ≥ 30% lumen stenosis in left main coronary artery would be directly classified as the highest level of severity.

Due to the difference of education systems, the schooling year for participants in each stage may not be the same. The four levels of education background represented illiteracy or primary school, junior high school, senior high school and technical school or college or university level.

Creatinine clearance was estimated using the Cockcroft-Gault formula with the value of serum creatinine tested at admission.

Statistical analysis mainly contained three parts: (1) We first compared patients’ characteristics according to different cutoffs for depression and anxiety to figure out the dominant predictors of mood disturbance; (2) Next, we evaluated whether NYHA classification could be an integrated index indicating patients’ status; (3) Finally, we explored the association between NYHA classes and depression or anxiety symptoms.

Except for data of Nt-ProBNP and LVEF, model independent variates were missing for at least 1 study variate in 14 patients (3.2%), with no study variate having > 1.8% missing data. Mean or median imputation depending on distribution pattern were applied using SAS STDIZE procedure. All tests for significance were two-tailed at the threshold of 0.05 and were performed with SAS 9.4 software.

Of the 443 consecutive angina pectoris inpatients screened, 123(27.8%), 34(7.7%) and 15(3.4%) inpatients were categorized as with mild, moderate and moderately severe to severe depression symptom, 103(23.3%), 13(2.9%), 11(2.5%) with mild, moderate and severe anxiety symptom. Patients’ characteristics were presented in Table 1 and Additional file 2: Table S2.

Compared with individual who had no or mild depression symptom, those with clinical depression (PHQ-9 score ≥ 10) were more likely to be less educated (p = .041), with higher NYHA classes (p = .017) and a history of antidepressant treatment (p < .001). A slight trend toward significance was observed for a prescription of loop diuretics (p = .062) or aldosterone receptor antagonist (p = .083). However, when comparing those not depressed with depressed patients, features that marked worse physical status became quite outstanding (see Table 1). Besides, the depressed participants tended to be older (p = .019), female (p < .001), without marriage partner (p = .023) and less educated (p < .001). The average scores of somatic depressive depression symptoms in each depression severity groups were 1.39 (SD 1.18), 4.37 (SD 1.44), 8.90 (SD 2.81), taking up 78.1, 68.9 and 63.3% of the total score, respectively.

Unlike depression, no difference except for an antidepressant treatment history (p = .010) was observed between the patients with or without clinical anxiety. Interestingly in comparison of the anxious and non-anxious, we noticed that anxious subjects tended to be female (p < .001), less educated (p = .001), with less severe coronary artery stenosis (p = .050) and a history of antidepressant treatment (p < .001) (see Additional file 2: Table S2).

In univariate analyses (Table 2), we discovered that significant differences existed among groups in age (p < .001), EF (p < .001), Nt-ProBNP (p < .001), creatinine clearance (p < .001), coronary artery stenosis severity (p < .001), medical history of hypertension (p = .003) or diabetes (p < .001), prescription of loop diuretics (p < .001) or aldosterone receptor antagonist (p < .001), depression severity (p < .001), somatic (p < .001) and cognitive (p < .001) depressive symptoms, but not in anxiety severity (p = 0.99), type of AP (p = 0.24), nor education background (p = 0.83). After multivariate adjustment using ordinal logistic regression model, significance retained for age (p = .024), EF (p = .037), Nt-ProBNP (p = .006), coronary artery stenosis severity (p = .034) and history of diabetes (p = .016) (see Additional file 3: Table S3), revealing a multiple impact of age, CHD severity, diabetes and heart failure on NYHA classes.

The Pearson’s correlation coefficients of PHQ-9 and GAD-7 scores was 0.72 (p < .001). As shown in Fig. 2, a non-differential interrelationship of depression and anxiety in different NYHA classes in AP (Fig. 2.A) and UPA patients (Fig. 2.C) was observed. For SAP, subjects in NYHA class III/IV seemed to be less anxious than those in NYHA class I and II under the same level of depression (Fig. 2.B). The ratio of anxiety and depression symptom scores differed significantly between SAP and UAP patients in NYHA class III/IV with at least mild depression symptoms (p = .018), but no difference between groups exited in separate analyses neither for anxiety nor depression.

Comparing the results of the binary and ordinal logistic models (see Table 3), a great consistency was observed in analyses for depression and anxiety in SAP patients, but not in UAP counterparts. For SAP patients, NYHA classes was significantly associated with levels of depression (binary model: p = .010; ordinal model: p < .001). This close correlation was also verified in UAP patients though only with ordinal model (binary model: p = 0.46; ordinal model: p = .005). Detailed analyses demonstrated that NYHA class I and II subjects in all AP types were statistically at equivalent risk for depression (for AP: NYHA II vs I binary model OR 1.32 (0.59,2.96), p = 0.50; ordinal model OR 1.17 (0.73,1.88), p = 0.52), although NYHA II subjects with UAP seemed more likely to be depressed in comparison with those SAP counterparts through the results of both models and analyses of somatic and cognitive depressive symptoms. One possible reason for this phenomenon is that SAP patients in NYHA class II may more frequently have the psychological expectancy of angina when doing excessive activities, but NYHA class I patients may not. NYHA III/IV patients, by contrast, shared a sharply higher risk (for AP: NYHA III/IV vs I binary model OR 3.32 (1.28,8.61), p = .013; ordinal model OR 3.94 (2.11,7.36), p < .001). NYHA class was found to be not associated with levels of anxiety regardless of the AP types. Additionally, education background was demonstrated to correlate with the risk for depression and anxiety only in UAP inpatients.

Similar trend was also revealed in binary logistic analyses for somatic and cognitive depressive symptoms as shown in Table 4. The only difference beyond their synchronous changes was that cognitive depressive symptoms in UAP and AP patients were affected by gender (for UAP patients: OR 2.11 (1.08,4.11), p = .029; for AP patients: OR 1.82 (1.10,3.01), p = .020), but somatic symptoms were not.