Literature DB >> 33315906

Detection and treatment of mental disorders in patients with coronary heart disease (MenDis-CHD): A cross-sectional study.

Samia Peltzer1, Hendrik Müller2, Ursula Köstler3, Frank Schulz-Nieswandt3, Frank Jessen2,4, Christian Albus1.   

Abstract

Mental disorders (MD) are associated with an increased risk of developing coronary heart disease (CHD) and with higher CHD-related morbidity and mortality. There is a strong recommendation to routinely screen CHD patients for MDs, diagnosis, and treatment by recent guidelines. The current study aimed at mapping CHD patients' (1) state of diagnostics and, if necessary, treatment of MDs, (2) trajectories and detection rate in healthcare, and (3) the influence of MDs and its management on quality of life and patient satisfaction. The design was a cross-sectional study in three settings (two hospitals, two rehabilitation clinics, three cardiology practices). CHD patients were screened for MDs with the Hospital Anxiety and Depression Scale (HADS), and, if screened-positive, examined for MDs with the Structured Clinical Interview for DSM-IV (SCID-I). Quality of Life (EQ-5D), Patient Assessment of Care for Chronic Conditions (PACIC), and previous routine diagnostics and treatment for MDs were examined. Descriptive statistics, Chi-squared tests, and ANOVA were used for analyses. Analyses of the data of 364 patients resulted in 33.8% positive HADS-screenings and 28.0% SCID-I diagnoses. The detection rate of correctly pre-diagnosed MDs was 49.0%. Physicians actively approached approximately thirty percent of patients on MDs; however, only 6.6% of patients underwent psychotherapy and 4.1% medication therapy through psychotherapists/psychiatrists. MD patients scored significantly lower on EQ-5D and the PACIC. The state of diagnostic and treatment of comorbid MDs in patients with CHD is insufficient. Patients showed a positive attitude towards addressing MDs and were satisfied with medical treatment, but less with MD-related advice. Physicians in secondary care need more training inadequately addressing mental comorbidity.

Entities:  

Mesh：

Year:  2020        PMID： 33315906      PMCID： PMC7735609          DOI： 10.1371/journal.pone.0243800

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.240


Introduction

According to the Global Burden of Disease Study, cardiovascular disease, especially coronary heart disease (CHD), will be a leading burden of disease in the coming decades and remains the leading cause of mortality in Europe [1]. Mental disorders (MD), such as major depression and anxiety disorders, are also a significant contributor to the global burden of disease. 14.3% of all deaths worldwide are attributable to MDs [2]. MDs have an enormous impact on healthcare costs, are associated with an increased risk of developing CHD, and worsen prognosis in established disease [3]. Depression is associated with a nearly twofold risk for developing CHD (OR 1.6–1.9) and with higher CHD-related morbidity and mortality (OR 1.6–2.4) [4]. After a myocardial infarction, almost 30% of patients experience depressive symptoms, 20% fulfilled the criteria for depressive disorders. During the next two years after a cardiac event, CHD patients with a comorbid depression disorder have two-fold greater mortality. The risk of dying can increase six-fold when depressive symptoms are severe [5]. Prevalence of anxiety is associated with a significant risk of cardiovascular mortality and CHD (OR 1.41) [6], especially phobic anxiety and panic disorders [5]. Approximately 39% of women and 22% of men experienced anxious symptoms 1.4 years after hospitalization for CHD [7]. The negative impact of MDs on the incidence and prognosis of CHD is mediated by behavioral and psychobiological mechanisms. Firstly, MDs often acts as a barrier to treatment adherence and reluctance to lifestyle change. Secondly, mechanisms like autonomic nervous system dysfunction, dysregulation of the hypothalamic-pituitary-adrenal axis, and proinflammatory and prothrombotic states directly interfere with the etiopathogenesis of CHD [8, 9]. Furthermore, it is assumed that these patients show a reduced health-related quality of life [3] and satisfaction [10]. Consequently, there is a strong recommendation of routine screening for MDs, adequate diagnosis, and treatment in person at risk for CHD and with clinically manifest CHD by recent national and international guidelines [3, 7, 11]. However, only a few studies have been conducted on the topic of the quality of healthcare concerning the screening and treatment of CHD patients with comorbid MDs. Adherence to CHD guidelines in physicians seems to be generally low, even when guidelines predominantly comprise essential somatic recommendations [12]. From a clinical perspective, it is unlikely that physicians regularly screen for MDs due to restraints in daily routine, e.g., lack of time, competence, or reimbursement [13, 14]. A study that examined various care management processes for depression and other chronic diseases found that physicians in primary care used significantly fewer procedures to detect and treat depression than for somatic diseases and that no adequate depression management was provided [15]. Feinstein et al. [14] showed that half of the examined physicians were unaware that depression itself could be a severe risk factor to CHD, 79% used no screening method to diagnose depression, and 71% asked less than half their patients about depression. Thombs et al. [16] found that screening for depression seems to be beneficial only if it results in a correct diagnosis and if appropriate treatment is available. Otherwise, uncritical use of psychometric screening tools could lead to over-diagnosing MDs, and consequently, inappropriate treatment and high costs for the healthcare system. These issues can be assessed with the measurement of patients' health trajectories. Health trajectories provide information about a patient's health status at any specified time, with the possibility of an included endpoint of interest [17]. In this study, we define the term ‘trajectories’ as the patient’s previous healthcare use and days of sick leave within the last twelve months. Hence, for the quality of care, it is essential not only to look at screening per se but also on whether MDs are addressed within the physician-patient interaction, diagnostic and treatment procedures [16], as well as in patients' trajectories within the healthcare system. Research on the quality of care and trajectories within the healthcare system of CHD patients with MDs has only recently begun to emerge. Depressive symptoms have been linked to the prediction of mortality within twelve months. At the same time, depressive symptoms persisted in clinically (85%) and subclinically (47%) depressed patients for at least one year [18], indicating that depressive symptoms after a CHD-related incident bear the potential to limit patients’ quality of life in the long term. This conclusion is supported by the findings of Palacios et al. [19], who looked at the development over time of five groups, differing in severity of MD-related symptoms. Patients from the 'chronic high' and 'worsening' group had significantly higher healthcare costs over patients who were characterized by less symptom severity over the course of time [19]. Up until now, most studies have limited themselves to assessing anxiety and depression in CHD patients. The current study investigates a broader diagnostic spectrum of MDs in CHD patients with the SCID-I (e.g., PTSD, addiction disorder, bipolar disorder, etc.). Furthermore, MenDis-CHD aimed to explore (1) the current state of diagnostics and treatment of MD and non-MD in CHD patients, (2) patients' trajectories and detection rate in secondary care, and (3) implications of mental comorbidity and its management on quality of life and patient satisfaction. Following the literature [4-7], it was expected that approximately 30% of CHD patients would experience depressive symptoms, and 20% would receive a clinical MD diagnosis on SCID-I. When it comes to patients' trajectories, it was expected that MD patients would more often utilize the healthcare system by, e.g., being hospitalized more frequently or being ill more regularly than non-MD patients. Furthermore, it was hypothesized that a significant amount of MD cases would not be detected by physicians in secondary care [14]. At last, it was expected that patients with MDs would experience significantly lower quality of life and satisfaction on psychological and physiological dimensions than non-MD patients [3, 10].

Materials and methods

Theoretical framework and research platform

MenDis-CHD is one of the three current projects of the 'Cologne Care Research and Development Network' (CoRe-Net) [20] in Cologne, Germany, and is funded by the Federal Ministry of Education and Research (BMBF). MenDis-CHD was approved by the Ethics Commission of Cologne University's Faculty of Medicine (committee's reference number: 17–220) on Sept 26th, 2017. This study was conducted according to the principles expressed in the Declaration of Helsinki. Trails registration number: German clinical trials register (Deutsches Register Klinischer Studien, DKRS), i.e., Registration Number: DRKS00012434, date of registration: May 11th, 2017. URL: https://www.drks.de/drks_web/ navigate.do?navigationId = trial.HTML&TRIAL_ID = DRKS00012434. For the study protocol, see [21].

Participants

Participants were included if they were at least 18 years old, had an angiographically documented CHD, were in treatment (e.g., stable angina pectoris, myocardial infarction), had sufficient German language skills, were patients in one of the cohort settings, and were able to give informed consent. Patients were excluded if they had severe or instable physical or mental conditions.

Assessments

Sociodemographic and clinical characteristics

Sociodemographic and clinical data were assessed by questionnaire, comprising age, gender, marital status, professional status, and medical history. The severity of CHD was assessed from the medical chart and contained i.a., NYHA (New York Heart Association; schema for classification of heart diseases according to their degree of severity), cardiac events in the previous medical history (e.g., myocardial infarction), cardiac surgeries (e.g., bypass surgery), congestive heart failure, percutaneous coronary intervention (PCI), and left ventricular ejection fraction.

Current state of psychosomatic support, diagnostics, and treatment

The patient's state of psychosomatic support, previous diagnostics, and treatments were determined using a self-developed 51 items questionnaire. All recruited patients had to answer to the questionnaire, but patients without MDs could skip several questions. The section 'state of psychosomatic support contained five items such as 'yes or no' questions: 'Do you talk with your physician about psychosocial problems?' and multiple-choice questions such as: 'How often did you talk with your physician about mental problems?' with the answer possibilities: 'always (every time) / often (every second appointment) / sometimes / seldom / only once / never.' Example questions for the other sections were: 'Have you had a psychological/psychiatric examination?' for the section 'diagnostics', and 'Are you currently receiving psychotherapy?' for the section 'treatment'. This questionnaire was developed within this study and has yet to be validated. The Hospital Anxiety and Depression Scale (HADS; [22, 23]) was used as a screening tool for depression and anxiety symptoms on two separate scales. If patients scored eight and above in either the depression or anxiety scale, the screening was considered as 'positive’. Participants with a ‘positive’ HADS result were further assessed with the SCID-I to detect a suspected MD (Structured Clinical Interview for DSM-IV; [24]).

Patients' trajectories and detection rate

Patients’ trajectories contained in total five questions within the self-developed 51 items questionnaire regarding frequency of consultation of general practitioner (GP), cardiologists and psychotherapists in the last four weeks and in the last twelve months, the frequency of hospital stay (due to heart disease or other diseases) in the last twelve months and days of sick leave in the last twelve months. An example question was: 'How many days have you been unable to work in the last twelve months?'. Detection rate of MDs in healthcare was assessed with the help of the medical charts of the patients. Patients were classified with currently having MD or not based on their prior diagnoses. During the study, patients then were screened for MDs with the SCID-I. Subsequently, patients were labelled as either (1) incorrectly pre-diagnosed with MDs, (2) incorrectly pre-diagnosed without MDs, (3) correctly pre-diagnosed without MDs, or (4) correctly pre-diagnosed with MDs.

Quality of life and patient satisfaction

Quality of life was assessed with the EURO-Quality of Life 5D-3L questionnaire (EQ-5D; [25]) on five dimensions (mobility, self-care, usual activities, pain and discomfort, anxiety, and depression). Measurement was conducted with a 3-point Likert scale. Raw scores were transformed in unison with the official EuroQoL guidelines into a Visual Analogue Scale (VAS; details see [26]). The higher the EQ-5D score, the lower the health-related quality of life. Also, the EQ-5D contained a visual analog scale with the points 'the best health condition you can imagine' and 'the worst health condition you can imagine', which was used as a quantitative individual measure scale. The Patient Assessment of Care for Chronic Conditions (PACIC; [27]) evaluated patient-healthcare team interactions and aspects of self-management support. The PACIC has five subscales, which measure: patient activation, delivery system design/decision support, goal setting, problem-solving/contextual counseling, and follow-up/coordination. The higher the mean total score, the better the team interactions and support. A modified version of the PACIC was used in this study. The original version of the short-form PACIC uses an 11-point scale, uniformly ranging from 0% to 100%. Our study utilized a 5-point-Likert scale, assessing patients' satisfaction regarding the topics mentioned above (this was advised by one of the developers of the PACIC for having less room for interpretation). Questions concerning the validation of this combination of questions and measurement techniques will be addressed in a separate manuscript.

Procedures

Patients were recruited in two cardiologic hospital departments, three practices, and two rehabilitation clinics in Cologne, Germany. The recruitment phase took place between Jan 15th, 2018, and Mar 29th, 2019. We used the clustered sampling technique, where two hospitals (center one: 'hospitals'), two rehabilitation clinics (center two: 'rehabilitation clinics'), and three cardiology practices (center three: 'practices') were used as sampling units. As in single-stage cluster sampling, all eligible patients of the chosen sampling units were then included in the study if they wanted to participate and fulfilled the inclusion criteria. Patients were screened for eligibility and documented in a screening log. Patients who fulfilled the inclusion criteria were adequately instructed about the procedure of the study, gave written informed consent, and were handed out the questionnaire-set which they filled in. If the HADS was positive, a second appointment was arranged to perform the SCID-I. All researchers were trained in applying the SCID-I and experienced in conducting it. If patients were diagnosed with MD, they were offered immediate psychological support and further information on psychotherapeutic treatment such as addresses of psychosomatic/ psychological ambulances, or psychotherapists.

Data analysis

All presented data were analyzed with IBM SPSS Statistics 22 [28]. The dataset was controlled for outliers, missing values, and implausible values. When cases with either missing or impossible values were identified, we compared these values to the equivalent 'paper and pencil' versions for correction. When outliers were found on a dependent variable, the analysis was conducted twice: once with and once without the outlier to verify that the outlier did not influence the result inadequately. No outlier had to be removed. Example: some patients required pervasive medical care, which resulted in them having more regular contact with physicians than the rest of the sample. Multiple variables were created from existing variables to reduce the number of value levels for factorial variables. For each analysis, we tested a priori if the respective statistical assumptions were violated: for ANOVA: Independence of errors, homogeneity of variance between groups, and normality of residuals within groups. Weighted means approach based on the size of each factor level was used for unequal cell sizes in variance analyses. To do this, weighted effect codes were used. Minor violations for normality of residuals were found. However, Welch's F (a robust estimate) backed the prior obtained results. Both assumptions for Pearson's Chi-Squared test (i.e., both variables should be measured at an ordinal or nominal level, and both variables should consist of two or more categorical, independent groups) were controlled for and met. The current state of diagnostics and treatment of MD and non-MD in CHD patients (research aim one) was investigated using Pearson’s Chi-squared tests to determine whether there was a statistically significant difference between expected and observed frequencies. See Table 2 for all items used to address this aim. Research aims two (Patients' trajectories and detection rate in secondary care) and three (implications of mental comorbidity and its management on quality of life and patient satisfaction) were examined using Analyses of Covariance (ANCOVAs). (Not) Having MD served as between-subjects factor. The displayed variables in Table 3 were used as dependent variables. In addition to the research aims we also investigated sociodemographic data and clinical characteristics of the cohort (see Table 1). The threshold for significance was set at α = .05. P-values from Tables 2 and 3 were corrected for confounding variables, i.e., age, gender, and NYHA score.
Table 2

Overview of results of MD and non-MD patients regarding the current state of psychosomatic support, diagnostics, and treatment.

Patients with MDPatients without MDP-valueTotal
N = 102, n (%)N = 262, n (%)N = 364, n (%)
Current state of psychosomatic support
Talking with the physician about psychosocial problems6260.89937.8< .00116144.2
Frequency of talking with the physician about psychosocial problems.427
    Always (on every doctor’s appointment)1312.8145.3277.4
    Often (on every second doctor’s appointment)1110.8166.1277.4
    Sometimes2524.54316.46818.7
    Seldom76.9228.4298.0
    Only once43.920.861.6
    Never10.962.371.9
Actively approached by the physician on MDs4242.27227.5.64111431.3
Found it appropriate to have been asked by the physician4242.26926.3.59411130.5
Diagnostics
Own perception of decline of mental well-being5654.9269.9< .0018222.5
Asked by others about the decline of mental well-being3231.4155.7.0134712.9
If yes, by whom ab
    General practitioner1211.831.2154.1
    Clinic--20.820.5
    Rehabilitation clinic43.931.271.9
    Cardiologist21.920.841.1
    Family & acquaintances (three categories)4847.1269.97420.3
    Others54.9--51.4
Psychological/psychiatric examination carried out4645.162.3< .0015214.3
Diagnosed positively MD symptoms4645.1186.9< .0016417.6
If yes, by whom a
    General practitioner109.810.4b113.0
    Cardiologist------
    Psychiatrist/psychotherapist2827.520.8308.2
    Neurologist54.910.461.6
    Other65.9--61.6
Referral for additional diagnostics3029.431.2< .001339.1
If yes, to whom a.021
    Psychiatrist/psychotherapist2524.520.8277.4
    Neurologist43.931.271.9
    Other10.9--10.3
Type of examination ab
    Questionnaires1615.710.4174.7
    Tests1413.741.5184.9
    Physical examination1110.831.2143.8
    CT/MRT65.941.5102.7
    Others1211.820.8143.8
Patient’s knowledge about MD diagnosis4140.283.1< .0014913.5
Type of diagnosis a< .001
    Depression2928.4--298.0
    Anxiety disorder1211.8--123.3
    Other21.951.971.9
Receiving an explanation of what the MD diagnosis means for further treatment2827.541.5.001328.8
Treatment
Was a treatment for MDs recommended?3736.341.5.1764111.3
If yes, what treatment
    Medication21.910.430.8
    Psychotherapy2221.641.5267.1
    Both98.810.4102.7
    Other10.910.420.5
Currently undergoing psychotherapy2221.620.8.003246.6
Perceived improvement through psychotherapy1817.731.2.750215.8
Currently undergoing medication therapy1312.820.8.020154.1
Perceived improvement through medication therapy1211.810.4.078133.6

Abbreviations: MD, Mental Disorder. All analyses were corrected for possible effects of age, gender, and NYHA.

aNote: Multiple-choice question.

bNote: At least one cell was too small for the appropriate analysis.

Table 3

Estimates of fixed effects, standard errors, p-values, degrees of freedom, and confidence intervals for MD and non-MD patients.

ModelsbaSEpdf95% CI
Patients' trajectories
Frequency contact with physician in last 4 weeks-0.030.191.8701[-0.406, 0.344]
Frequency contact with psychotherapist in last 12 months-9.535.393.0851[-20.410, 1.358]
Frequency hospital stays due to heart disease in the last 12 months2.213.100.4771[-3.898, 8.311]
Frequency hospital stays due to other diseases in the last 12 months-4.573.631.2111[-14.649, 0.838]
Frequency of days of sick leave in the last 12 months-19.297.704.0131[-34.449, -4.138]
Frequency of days of sick leave in the last four weeks-3.5021.988.0811[-7.438, 0.434]
Detection rate
The detection rate of MDs in the healthcare system-0.5660.098< .0011[-0.759, -0.373]
Quality of life
Mobility-0.0880.053.1001[-0.193, 0.017]
Self-care0.0070.036.8401[-0.063, 0.078]
Usual activities-0.1390.058.0181[-0.254, -0.024]
Pain/discomfort-0.2160.069.0021[-0.352, -0.080]
Anxiety/depression-0.5110.052< .0011[-0.614, -0.409]
Estimation of current health status-0.0570.084.4951[-0.223, 0.108]
Patient satisfaction
Given choices about treatment to think about0.4890.180.0071[0.136, 0.842]
Satisfied that my care was well organized0.3180.109.0041[0.105, 0.532]
Helped to set specific goals to improve my eating or exercise0.3000.157.0561[-0.008, 0.608]
Given a copy of my treatment plan0.3300.169.0521[-0.003, 0.664]
Encouraged to go to a specific group or class to help me cope with my chronic condition0.2070.186.2671[-0.159, 0.574]
Asked questions, either directly or on a survey, about my health habits0.2020.152.1841[-0.097, 0.501]
Helped to make a treatment plan that I could carry out in my daily life0.2310.191.2261[-0.144, 0.606]
Helped to plan ahead so I could take care of my condition even in hard times0.1810.192.3451[-0.195, 0.558]
Asked how my chronic condition affects my life0.0570.183.7531[-0.302, 0.417]
Contacted after a visit to see how things were going0.3240.196.0981[-0.061, 0.709]
Told how my visits with other types of doctors, like an eye doctor or other specialist, helped my treatment0.2080.187.2661[-0.159, 0.575]
Total satisfaction0.3350.108.0021[0.123, 0.547]

Abbreviations: MD, Mental Disorder. All analyses were corrected for possible effects of age, gender, and NYHA.

aNote: Direction of the effect: From MD to non-MD.

Table 1

Overview of sociodemographic and clinical characteristics.

Patients with MDPatients without MDP-valueTotal
N = 102, n (%)N = 262, n (%)N = 364, n (%)
Sociodemographic data
Gender.002
    Male6058.819875.625870.9
    Female4241.26424.410629.1
Age.001
    35–49 years98.8155.7246.6
    50–59 years3029.45922.58924.5
    60–69 years3938.27227.511130.5
    70–79 years109.88030.59024.7
    80–95 years1413.73613.75013.7
Marital status.292
    Living together7068.619474.126472.5
    Living alone3231.46825.910027.5
Professional qualification a.245
    None1413.7186.9328.8
    Apprenticeship4948.012748.517648.4
    Vocational school1413.74416.85815.9
    College/university1514.75119.56618.1
    Other109.8228.4328.8
Retired4847.114354.6.19719152.5
Clinical characteristics
Somatic comorbidity ab
    Peripheral arterial disease98.8249.2339.1
    Congestive heart failure2524.57729.410228.0
    Transient ischemic attack/stroke54.9228.4277.4
    Cancer21.9--20.5
Left ventricular ejection fraction.597
    > 40%8280.420477.928678.6
    ≤ 40%2019.65822.17821.4
NYHA.001
    NYHA I2625.510138.612734.9
    NYHA II4140.211543.915642.9
    NYHA III3534.34617.68122.3
Patients with both myocardial infarction and PCI intervention6260.814555.3.88620756.9
Only PCI intervention8583.322184.4.96030684.1
Bypass surgery2120.64717.9.5606818.7
Cardiac valve surgery65.9186.9.733246.6
HADS Anxiety< .001
    Positive (≥ 8)6866.7186.98623.6
HADS Depression< .001
    Positive (≥ 8)5553.972.76217.0
HADS Total< .001
    Positive (sum score ≥ 14)102100.0218.012333.8

Abbreviations: MD, Mental Disorder; NYHA, New York Heart Association; PCI, Percutaneous Coronary Intervention; HADS, Hospital Anxiety and Depression Scale.

aNote: Multiple-choice question.

bNote: At least one cell was too small for the appropriate analysis.

Abbreviations: MD, Mental Disorder; NYHA, New York Heart Association; PCI, Percutaneous Coronary Intervention; HADS, Hospital Anxiety and Depression Scale. aNote: Multiple-choice question. bNote: At least one cell was too small for the appropriate analysis. Abbreviations: MD, Mental Disorder. All analyses were corrected for possible effects of age, gender, and NYHA. aNote: Multiple-choice question. bNote: At least one cell was too small for the appropriate analysis. Abbreviations: MD, Mental Disorder. All analyses were corrected for possible effects of age, gender, and NYHA. aNote: Direction of the effect: From MD to non-MD.

Results

In total, 753 patients were screened for eligibility, and 374 patients were recruited. Overall, ten recruited patients dropped out of the study due to incomplete questionnaires or withdrawal of the informed consent. A total of 364 patients entered the analysis. Separated by treatment setting, we included 107 patients from hospitals, 157 from rehabilitation clinics, and 100 patients in cardiology practices. In the following results, all percentages relate to the maximum number of patients who were eligible for the underlying question. In some cases, this number is equal to the whole sample. Fig 1 depicts a flow chart presenting the recruitment process.
Fig 1

Flowchart of the recruitment procedure.

Abbreviations: CHD, coronary heart disease.

Flowchart of the recruitment procedure.

Abbreviations: CHD, coronary heart disease.

Sociodemographic and clinical characteristics

Most patients were male (n = 258, 70.9%) with a mean age (both genders) of 65.9 years (SD = 11.4). One-fifth had a left ventricular ejection fraction of <40%. Most patients had a myocardial infarction and were treated with PCI. The HADS-screening was ‘positive’ in n = 123 patients (33.8%). SCID-I interview revealed that 102 (28.0%) patients had at least one SCID-I diagnosis. For an overview of the characteristics, see Table 1. The most common diagnoses were unipolar depression, anxiety disorder, and substance use/addiction disorder. An overview of all SCID diagnoses is given in the S1 Table.

Current state of psychosomatic support, diagnostics, and treatment

Approximately 61% of MD patients and 38% of non-MD patients talked to their primary attending physician (e.g., GP or cardiologist) about psychosocial problems. Both MD and non-MD patients reported mostly to only talk 'sometimes' with their physician about MDs. Overall, physicians actively approached 31% of patients to talk about MDs. MD patients were most likely to report a decline in their mental well-being. Forty-six MD patients (45.1%) and six non-MD patients (2.3%) underwent psychological/psychiatric examinations in secondary care. Also, forty-one MD patients (40.2%) knew about their MD diagnosis, and only 28 MD patients (27.5%) received an explanation of what the MD diagnosis means for their further treatment. Looking at the treatment section, only 11.3% of all patients (MD and non-MD) received a treatment recommendation, with 6.6% of all patients getting psychotherapy and 4.1% of all patients receiving medication therapy. For detailed information on MD and non-MD patients, please see Table 2.

Patients' trajectories and detection rate

After correcting for gender, age, and NYHA, significant differences in trajectories of healthcare between CHD patients with and without MDs have been found. On average, MD patients reported more days of sick leave over the last twelve months than non-MD patients (M = 101 days, SD = 75.9 and M = 83 days, SD = 53.8, respectively). Also, it was found that MD patients had more days of sick leave in the last four weeks before the study (M = 23, SD = 9.5, and M = 19, SD = 9.5, respectively). MD patients also reported making use of psychotherapeutic aid more often than non-MD patients (M = 10.2 times, SD = 17.2 and M = 6.6 times, SD = 10.1, respectively). However, these differences were only marginally significant. Overall, MD and non-MD patients were not always correctly diagnosed previously by their physician as such (χ(1) = 119. 412, p < .001). Fifty patients (13.7%, true-positive) were correctly pre-diagnosed with MDs. Further, 255 patients (70.1%) were correctly diagnosed as healthy (true-negative), seven were falsely pre-diagnosed as suffering from MDs (1.9%, false-positive) and 52 (14.3%) were incorrectly pre-diagnosed as healthy (false-negative) with the consequence that these patients suffered from MD symptoms, but did not receive diagnostics nor treatment. Summing up, compared to the total sample, 59 (16.2%) patients were misdiagnosed by their attending, most of which (88.1%) as mentally healthy even though they were not. A total of 102 patients were diagnosed with MDs in this study through our assessment with the HADS and the SCID-I. Fifty of them were correctly pre-diagnosed by the attending physician, yielding in a detection rate of 49.0% on the part of the physicians. Correctly pre-diagnosed MD patients talked more often with their physicians about MDs, were more often actively approached by the physician on MDs, had more psychological examinations, and got more help with the search for psychotherapeutic treatment. Incorrectly pre-diagnosed MD patients were rarely noticed as suffering from MDs, were seldom referred to diagnostics, and rarely got a recommendation for further treatment. For detailed information, see Table 3 and S2 Table.

Quality of life and patient satisfaction

The analysis of the EQ-5D-3L showed a left-skewed distribution, indicating that most of the participants reported no restrictions in health-related quality of life. Out of the six dimensions, MD patients differed significantly in three of them. MD patients reported less quality of life when it comes to activities in everyday life than non-MD patients (M = 1.5, SD = 0.6 vs. M = 1.3, SD = 0.5, respectively), pain and discomfort (M = 1.9, SD = 0.6 vs. M = 1.6, SD = 0.6, respectively) and anxiety and depression (M = 1.7, SD = 0.5 vs. M = 1.2, SD = 0.4, respectively). No significant differences have been found on the dimension's mobility, self-care, and general estimation of one's health status. Overall, patients reported being satisfied with their received medical care across all items (M = 4.2, SD = 0.9). On average, patients reported high satisfaction with the organization of their care (M = 4.3, SD = 0.9), the general course of medical treatment (M = 4.2, SD = 0.9), and receiving a copy of their treatment plan (M = 4.1, SD = 1.4). Satisfaction was lowest on dimensions of psychological support received by their physician, for example helping the patient develop a plan to be able to cope when the chronic condition worsens (M = 2.8, SD = 1.6), making a treatment plan to improve daily life (M = 2.6, SD = 1.6), or encouraging the patient to find self-help groups to cope with their chronic condition (M = 2.3, SD = 1.5). MD patients scored (marginally) significantly lower on five patient satisfaction measures as compared to non-MD patients. MD patients stated that, on average, they were given more than one treatment option to choose from less frequently (M = 2.9, SD = 1.5, and M = 3.5, SD = 1.5, respectively), they were satisfied less with the organization of their care (M = 4.1, SD = 1.1, and M = 4.4, SD = 0.8, respectively), they experienced less support from doctors to set specific goals to improve eating or exercise behavior (M = 3.6, SD = 1.4, and M = 3.9, SD = 1.2, respectively), and they reported to have received copies of their treatment plan less frequently (M = 3.9, SD = 1.5, and M = 4.2, SD = 1.4, respectively). For more detailed information regarding all items, see Table 3.

Additional analyses

This study provides some additional analysis regarding the interaction between MDs and healthcare. For detailed information, see S1 Appendix.

Discussion

The current study aimed to explore (1) the current state of diagnostics and treatment of MD and non-MD in CHD patients, (2) patients' trajectories and detection rate in secondary care, and (3) implications of mental comorbidity and its management on quality of life and patient satisfaction. Both hypotheses concerning the current state of diagnostics and treatment of MD and non-MD CHD patients were confirmed: It was found that approximately 33.8% of the sample was screened positive on the HADS. SCID-I interview revealed that 28% had at least one SCID-I diagnosis. Only 6.6% of patients underwent psychotherapy and 4.1% medication therapy through psychotherapists/psychiatrists. First, findings regarding diagnostics are in accordance with the literature, as in general, 30% of patients experience depressive symptoms, 20% fulfill criteria for depressive disorders [5], and most MD patients were diagnosed with depression, anxiety disorder, or a combination of both [4, 5, 7]. Especially depression and anxiety disorders, therefore, have to be taken into account when treating someone for CHD, as they occur regularly, worsen the prognosis [3] and are associated with higher morbidity and mortality [4, 6, 7]. Secondly, the results of the study indicate that there are too few conversations about MD in physician-patient-interactions. This may be one reason why physicians have difficulties to identify patients with MDs and recommend treatment for MDs. Further, due to known restrictions like lack of time and knowledge [14, 29], it seems following the literature difficult for physicians to address severe issues (e.g., more than MD screening) with psychological content in addition to established somatically-oriented treatment. Also, patients might be insecure about whether they should talk about MDs or are unaware of the option of psychotherapy or drug therapy, which is why the physician should be the one making the first step and ask about possible psychological issues. If physicians suspect that a patient might suffer from MDs, they should provide information about mental healthcare and possibly help patients making contact with psychological caretakers. A beneficial effect would be that patients perceive physicians as empathetic, significantly improving patient satisfaction and compliance in terms of information exchange, satisfaction with treatment, perceived expertise, and interpersonal trust [30]. In the next step, the patient would be referred to a psychotherapist or psychiatrist. This would come with advantages for the patient and the physician alike. The patient would be monitored by an MD expert, resulting in increased diagnostic accuracy and adequate treatment. The physician could concentrate solely on the treatment of CHD and screening for MD-related symptoms. Regarding patients' trajectories, our expectations were partly confirmed. MD patients utilized parts of the healthcare system more frequently than non-MD patients. MD patients reported being sick more frequently as compared to non-MD patients for the last 12 months. The detection rate of MDs in secondary care (e.g., general practitioners and cardiologists) was about 49%, confirming the hypothesis that a significant amount of MD cases would not be found by physicians in secondary care. The diagnostic accuracy of MDs in CHD patients is insufficient. It is not surprising that patients with MDs utilize the healthcare system more often than non-MD patients. However, the increased use of the healthcare system seems to occur at the wrong end. Most CHD patients approach their physicians more frequently due to health problems facilitated by their MDs instead of visiting mental healthcare professionals. Physicians are increasingly called upon to provide appropriate MD diagnostics and treatment [31], while physicians' ability to detect, diagnose, and adequately treat patients with MDs is often considered unsatisfied. After three years in the healthcare system, about 14% of patients with depression or anxiety remained unrecognized [32]. The recognition of mental problems in only half of the affected people results in MD patients not getting adequate treatment and possibly worsening their symptoms. The current study adds to the findings that physicians in primary care use significantly fewer procedures to detect and treat MDs than for somatic diseases and that no adequate MD management was provided [15]. Patients with MDs went mostly unrecognized by the physician, indicating that physicians did not screen properly for comorbid MDs in CHD patients. Other studies have shown that 50% of physicians are unaware of MDs like depression to be a risk factor to CHD [14]. Most physicians also did not use any screening tools to detect MDs like depression, nor did they talk to their patients about depressive symptoms. Although the studies mentioned above refer to primary care situations and are therefore not directly comparable with the secondary care examined here, both studies showed that consequences of non-accidental misdiagnoses could be manifold, with limitation of the recovery from and handling of CHD being the most severe consequence. The medical system does not catch a relevant number of patients suffering from MDs. An erroneous detection rate not only hinders patients from addressing CHD-related symptoms properly but also impairs their quality of life in the long turn. MD patients reported less quality of life on psychological dimensions like discomfort or anxiety, but not on physiological dimensions like mobility or self-care, rendering our expectations regarding quality of life half confirmed. The same holds for the hypothesis regarding MD patients' satisfaction with their treatment. On five of 12 dimensions, MD patients reported a critical shortage concerning aspects of basic psychological care like coping with MD/CHD, and support to gain self-help related skills. Patients expressed a need for unmet psychological support provided by the physician, regardless of whether they suffered from MDs or not. Patient satisfaction and quality of life seem to be critical components in the treatment of patients with CHD and MDs. Both influence treatment adherence, and as a result, patients who report high satisfaction and quality of life benefit more from care than less satisfied patients. Furthermore, patient satisfaction predicts outcomes right from the initial stages of treatment, e.g., when assessed within the first two days of hospital care [33]. If patients are not satisfied with the care they receive, one has to expect that patients are less likely to adhere to the necessary treatment courses and do not realize recommended lifestyle changes, which can result in a vicious circle in which patients experience more symptoms, get sick more often, have to visit their physician more often, and possibly develop a MD or worsen current MD symptoms [34]. The physician can break this vicious circle by involving the patient in the course of treatment through shared decision-making and patient-centered care (i.a., perceptions of influence on the treatment course, feeling understood by the physician). If this is initiated early enough by the physician within the physician-patient communication, patient satisfaction and thus treatment adherence can be maintained and improved. In the course of shared decision-making, it appears to be beneficial that the physician recommends and discusses in-depth diagnosis and treatment of MDs with the patient after a positive MD screening. The shared decision on MD treatment can also increase adherence, which in turn can improve patient satisfaction and quality of life [35].

Strengths and limitations

MenDis-CHD gives insights into how CHD patients with MDs are treated in clinical practice and how patients utilized the healthcare system. Another strength of this study was that every person had a thorough psychological screening for depression and anxiety symptoms and, if applicable, an assessment of mental disorders employing SCID-I. Therefore, patients had the opportunity to get a valid diagnosis, immediate support and information about further treatment possibilities. The current study also had limitations. The sample size on some questions of the questionnaire was too small for statistical analyses due to lack of eligibility, so that analysis remained at a descriptive level. However, only a minority of the self-developed items were affected. Further, we possibly did not detect all MDs because participants were only tested with a SCID-I interview if the HADS-screening was 'positive.' We used a cross-sectional study design in which we examined several cohorts exclusively from the Cologne area, Germany, within a short, limited period. Perhaps the time span or locality may have caused a sample bias because patients were not retested multiple times, and there was no multicenter testing. In addition, subjective items could be affected by recall bias. One example could be the question about the number of days of sick leave during the last year. This could be overcome by adding objective measurements of those items, i.e., the actual, registered number of days of sick leave someone has asked for in the last year.

Implications for further research

The sample size of the current study was mediocre; therefore, a repetition with a larger sample size would be advantageous to examine the generalizability of the results. The perspective of physicians could be explored regarding their perception of barriers and limitations in care for CHD patients with MDs. Together with the needs and preferences of patients, the results from MenDis-CHD could inform guidelines for the detection and treatment of MDs in CHD patients.

Conclusion

We found that the state of diagnostics and treatment of MD in patients with CHD was insufficient. Although patients expressed a positive attitude towards addressing MDs within a medical context and were generally satisfied with the medical healthcare, guidance for disease self-management and treatment of MDs was insufficient. Training of physicians concerning screening and treatment of comorbid MDs could have a positive impact on health-related quality of life and possibly could reduce CHD risk factors.

Overview of all SCID-I diagnoses.

Abbreviations: SCID, Diagnostic and Statistical Manual of Mental Disorders. aNote: patients can have more than one SCID diagnosis. (DOCX) Click here for additional data file.

Trajectories of the healthcare system.

Showing the difference in the current state of psychosomatic support between patients who had both a pre-existing MD diagnosis and were positively tested in our study (SCID-I) versus patients who had no pre-existing MD diagnosis but were positively tested (SCID-I). Abbreviations: MD, Mental Disorder; SCID, Diagnostic and Statistical Manual of Mental Disorders. aNote: All percentages relate to the maximum number of patients who were eligible for the presented questions. bNote: At least one cell was too small for the appropriate analysis. (DOCX) Click here for additional data file.

Additional analyses: Interaction between MD and healthcare.

Abbreviations: MD, mental disorders. (DOCX) Click here for additional data file. 3 Aug 2020 PONE-D-20-20310 Detection and treatment of mental disorders in patients with coronary heart disease (MenDis-CHD): A cross-sectional study PLOS ONE Dear Dr. Peltzer, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by September 2, 2020. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. 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(Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Thank you for the opportunity to review the manuscript titled “Detection and treatment of mental disorders in patients with coronary heart disease (MenDis-CHD): A cross-sectional study”. The authors aimed to analyze (1) the state of diagnostics and treatment of mental disorders in CHD patients; (2) patient’s trajectories in secondary care, and (3) draw implications regarding quality of life and patient satisfaction. Regarding their aims, the authors find, that (1) 28% of the sample reported a psychiatric diagnosis (SCID-I), out of which nearly half were correctly pre-diagnosed. Moreover, only 7% underwent psychotherapy and 4% medication therapy for mental disorders; (2) Patients with mental disorders reported longer stays in hospital and more sick days than those without; (3) Patients with mental disorders showed a reduced quality of life and lower patients satisfaction compared to those without. In sum, this manuscript analyzes an interesting and relevant topic. However, I have some questions and comments regarding methods and reporting, which could help to improve the transparency and readability of the manuscript. *Overall structure/language 1. In my opinion, because a range of different outcomes was analyzed, and some results were reported on the entire sample, people with mental disorders, or a comparison, the results and discussion could be restructured/revised to enhance the clarity of the manuscript. 2. Moreover, the manuscript could benefit from minor language editing. *Abstract The use of bivariate statistics and rather descriptive nature of the study should be stated as early as in the abstract. *Introduction 1. The authors state that “(...) evidence concerning the quality of psychosomatic care and trajectories within the healthcare system in CHD patients with MD is scarce.” (p. 4). However, there are some longitudinal studies available regarding trajectories of mental health (particularly anxiety and depression), quality of life, mental health treatment, and health care costs in patients with CHD, that are, in my opinion, not considered (e.g. DOI 10.1016/j.jpsychores.2017.10.015; 10.1159/000501502). In light of this, it should be stated more clearly what this study adds to the existing scientific literature. 2. The sentence „MenDis-CHD could successfully archive these aims.“ is, in my opinion, rather a conclusion and should be removed from the aim/introduction section. *Materials & Methods 1. For reasons of transparency, please elaborate on sampling technique. 2. In general, the description of the questionnaire was rather short and further details on the assessment of outcomes could be added. Please elaborate. 3. Analysis: Because the authors state that only a minority of the questionnaire items had subgroups that were to small for statistical analysis (p. 16), I am particularly interested why the analysis was on a bivariate level and there was no adjustment for confounding variables for the main outcomes, e.g. by means of regression. *Strength & Limitations: 1. A major strength of this study, that is not mentioned in this section and could be added, is the thorough assessment of mental disorders by means of SCID-I. Having said this, as a positive HADS-screening was the prerequisite for the SCID assessment some MDs may also have been undetected. 2. Moreover, I feel that some statements in this section are a conclusion or result rather than a strength of the study and its design and I would recommend revising. 3. In the limitations section I would strongly recommend to include the cross-sectional nature of the study and the assessment of health care use/sick days for the previous 12 months in self-report, which could be affected by recall bias. *Tables 1. I was wondering why the results in the tables were presented by recruitment setting, as stratification by setting was not the aim/research question of the study and these results are not discussed in detail. 2. Percentages could be added in Supplementary Tables. Reviewer #2: Review of manuscript “Detection and treatment of mental disorders in patients with coronary heart disease (MenDis-CHD): A cross-sectional study” This was a cross-sectional study conducted in three settings (hospital, cardiac rehabilitation (CR) and cardiology practices). From my understanding the aims of the study were to identify the prevalence of mental disorders (MD), by undertaking MD screening; examine the accuracy of MD detection; to investigate the acceptability by patients of being approached by a physician regarding MD; to investigate the prevalence of treatment for MD (presumably amongst those who screen positive); and to comment on the adequacy of the diagnosis and treatment of MD in patients with coronary heart disease (CHD). There are several issues which I believe need to be addressed before this manuscript is acceptable for publication. 1. There is no clear statement of the aims of the study in the abstract. The aim stated (to explore the state of healthcare recording diagnostics and treatment of MDs in secondary care in CHD patients with MD) is vague and cannot be tested. Three aims are stated in the Introduction, but again these are relatively vague and not clear (eg. aim 2: what ‘patients’ trajectories’ are you referring to? Clear aim needs to be articulated in both the abstract and the Introduction. 2. There are sentences in the Introduction that do not make sense. For example, page 3 line 57-58: ‘…are both among the top ten disorders concerning year’s lives with disability worldwide’ and page 3 line 66 ‘the negative impact of MD on the incidence and prognosis…’ of what? Presumably this is on the CHD incidence and prognosis. The manuscript requires a thorough edit for grammatical correctness. 3. Some of the crucial references are too old and therefore not relevant to today’s setting. For example, page 3 line 76: to support the point that ‘adherence to CHD guidelines in physicians seems to be generally low..’ a reference about acceptance of guidelines by family care physicians in 2002 is cited. It is highly likely that this citation does not reflect guideline acceptance at present. 4. Remove the term ‘suffered from’ in lines 108 and 111 on page 5 and line 185 on page 7. It is more appropriate to say ‘had angiographically documented CHD’ and ‘had severe and unstable physical or mental conditions’ and ‘had had myocardial infarction’. ‘Suffered’ is a subjective word, whereas ‘had’ is objective. 5. In the Assessments section (page 5 lines 118-122), it is unclear whether the 158 item questionnaire was given to all patients or only to those who screened positive for MD. It seems that many of the items would not be relevant unless a person has a diagnosed MD. Indeed, the detail of the 158 item questionnaire is inadequate as the reader is unable to ascertain what is actually asked in this very extensive questionnaire. Has this questionnaire been used before? Who developed it? Has it been validated? Is it publicly available? All this information needs to be provided. 6. In the Results section, on page 8 line 190-191, it is stated that “There were significant differences in trajectories of healthcare between CHD patients with and without MD”. Given that this is a key result of the study (relating to the aims), these results should be presented in a table. At present, the results are presented in sentences referring to days in hospital, days of sick leave etc, with mean number of days reported. However, there is no significance level reported for any of these statements so it is not possible for the reader to determine if these differences were statistically significant. Moreover, in some of these statements the n value is slotted into the sentence, which is not a conventional approach. As stated, this information should be presented comprehensively in a table. 7. Table 1 reports on differences based on patient recruitment setting (hospital, CR, cardiology practice). To my mind, these differences are largely methodological and should be stated in a simple sentence rather than in a table. For example, the sociodemographic differences are largely cofounded: CR participants are younger, more likely living alone and have fewer qualifications, whereas hospital and practice patients are older and more likely retired. By virtue of their younger age, it is not surprising then that the CR cohort have higher rates of anxiety, SCID diagnosis and unipolar depression – these trends are consistent with the literature that reports higher mental health problems in younger patients. Again, I reiterate, these are patterns that are a result of the recruitment strategies used in the study, rather than a key finding relevant to the aims, so they do not deserve to be put in Table 1 but instead should be commented on in describing the heterogeneity of the study sample. 8. Instead of the current Table 1, a table comparing characteristics of MD vs. non-MD patients would be much more revealing to the reader. 9. In the section titled Current state of diagnostics and treatment (page 10), there appear to be some errors. On line 233-234 it is stated that ‘Patients in rehabilitation clinics were most likely to report a decline in their mental wellbeing’, however according to Table 2 this difference was not significant (p=.639). Likewise, the statement on line 238-240 implies that these differences were significant (ie. rehab patients being informed about MD diagnosis, diagnosed more often, received an explanation and got treatment recommendations), whereas according to the data in Table 2 all these differences are not significant. Further, the statement that ‘4.1% had medication therapy’ (line 241) is again not consistent with the data presented in Table 2. 10. Indeed, Table 2 is impossible to interpret. There is no indication throughout the table as to what is the total N for each variable, therefore the numbers (n) and percentages (%) do not correspond. For example, regarding ‘own perception of decline in mental wellbeing’ 20/107 is 18% not 58.8% as reported in the table. Without stating the total N for each variable, it is impossible to verify the data and therefore impossible for the reader to interpret the results. 11. Again, the current Table 2 is not very informative to the reader and does not reflect the aims of the study. The study was not designed to compare the rates of MD and other variables between patients from each of the three study settings: as stated, these findings are merely an incidental bi-product of the methodology employed by the researchers. It would be much more informative to present a table of the differences in all these variables for patients with and without MD. 12. The patient satisfaction data would be better presented in a table, with all relevant questionnaire items shown, so that the reader can quickly scan the results. Currently, there is no actual data shown so it is impossible for the reader to interpret the satisfaction levels for each item, and the relative satisfaction between items. 13. In the section on Interaction between MD and healthcare, why is the sentence reporting differences between rehab and other centres in HADS scores reported here? This belongs back with the earlier data on differences in patient characteristics across the three settings, not here in the section on MD and healthcare. 14. The final results reported on page 13-14 report on differences between MD ad Non-MD patients on talking and not talking to physicians. I cannot understand why this is of any clinical significance? It is completely self-evident that MD patients would talk with physicians about MD more often than would non-MD patients (talking about MD is clearly not relevant to someone who does not have MD). Can the authors explain the clinical relevance of this information, or exclude it? 15. In the Discussion, line 316 on page 14, it is stated that women were twice as likely to develop MDs. However, this has not been reported or mentioned in the Results (or I was unable to find it). Plus, why is this result refenced to citation number 26 if it is from the findings of the present study? 16. Overall, the Discussion needs to be presented in light of previous literature and studies regarding the detection and management of mental disorders in cardiac patients, and in the population more broadly. In its current form, it is not adequately nuanced, it does not adequately relate the study findings to the literature, it is not synthesised in a way which adds further illumination of the findings for the reader, and is largely a summary of some of the findings presented in the Results. 17. Some of the references are incomplete. For example, references 8, 10, 20, ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). 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Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please check reviewer 1´s comments in particular. I agree, that your manuscript still needs some clarification and improvement of readability. Please submit your revised manuscript by December 10, 2020. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols We look forward to receiving your revised manuscript. Kind regards, Stephan Doering, M.D. Academic Editor PLOS ONE Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: (No Response) Reviewer #2: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: (No Response) ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Thank you for the opportunity to review the revised manuscript titled “Detection and treatment of mental disorders in patients with coronary heart disease (MenDis-CHD): A cross-sectional study”. I would like to thank the authors for all the important revisions made to the manuscript. While this has enhanced the readability of your work, there are still some uncertainties, which, I assume, result from unclear wording and the many outcomes/items analyzed in this manuscript. I have provided some suggestions to enhance transparency to the reader. However, further revision and editing may be needed as well. 1. General notes on wording 1.1. Please make sure to use abbreviations/wording uniformly to enhance readability: “EQ5D” vs. “EQ-5D”;“CHD patients” vs. “CHD-patients”; for mental disorders, sometimes “MD” is used for singular and plural forms, while at other times, “MDs” is used to indicate the plural form; “sick leave” vs. “days of illness”, etc. 1.2. “Trajectory”: In my opinion “trajectory” refers to the observation of individuals at several points in time which would permit the analysis of intra-individual change or trajectories over time using longitudinal datasets. Because this was a cross-sectional study with a retrospective assessment of preceding health care use, this should be made clearer, e.g. “previous health care use and days of sick leave within the last X months”. 1.3. “Diagnosis”: Particularly in the section “patients’ trajectories and detection rates” it is oftentimes not quite clear what the term “diagnosis” refers to - does it mean MD/SCID result in your study or a previously documented diagnosis, i.e. detection as a case by a previous physician? Please revise for clarity. 2. Introduction I originally suggested to state the relevance of the study in more detail as well as in light of some more recent longitudinal studies that were, in my opinion, not considered when considering health care use/ costs/quality of life associated with mental health problems and depression management in patients with CHD in the introduction (“originally p. 4, “(...) evidence concerning the quality of psychosomatic care and trajectories within the healthcare system in CHD patients with MD is scarce.”). While the authors stated to have included the references and discussed the difference to their study, I cannot find them in the revised manuscript. 3. Methods Thank you for providing further information on the assessments, Unfortunately, even with the added details, it is still not clear to me which assessment and which statistical method was used for which reported result exactly. In line with this, by which assessment was the detection rate of mental disorders in healthcare assessed? Further restructuring of the “Assessments”-Section by section headings could be helpful. Moreover, the exact method of analysis for each research question could be added to the Tables/briefly mentioned in the text; or each research question and method of analysis should be described in more detail in the “data analysis” section for reasons of transparency. 4. Results 4.1. Please avoid the use of “marginally significant”. Because an alpha of 0.05 was set for all analyses as the threshold for significant effects, results are either significant at this threshold or they are not. In line with this, why are p-values over 0.05 (e.g., contact with psychotherapists: p = 0.085) printed in bold in Table 3? 4.2. Additional analyses on interaction: The consideration of the different recruitment settings was not described as an aim of the study, there seems to be no a priori hypothesis about this additional analysis, and the results are not discussed in the discussion section. In line with this and because the manuscript already includes many analyses and outcomes, I would suggest to fully exclude the additional analysis or put it completely into the appendix as an exploratory, additional analysis, with a brief reference to it in the main manuscript. 5. Discussion 5.1. As far as I can tell, the study could not analyze whether treatment received for MDs was adequate according to treatment guidelines, such as the German S3-Leitlinien (i.e., details on type and dose of medication/detailed information on psychotherapy). However, treatment adequacy was discussed (l. 396), while the study analyzes to whether or not the physician talked about mental health with their patients? Please revise. 5.2. In the strengths & limitations section it is described that participants who fulfilled the criteria for a SCID-diagnosis were offered immediate psychological support and further information on psychotherapeutic treatment. While this thoughtful offer seems to be part of the study design (and should therefore be mentioned in the methods section) it does not seem to immediately influence the results of this manuscript or their interpretation. Therefore, it should not be described as detailed in the strengths section. Reviewer #2: The authors have adequately addressed the reviewers' comments and the manuscript is now much improved. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 16 Nov 2020 Thank you very much for your helpful recommendations. We adapted the manuscript following your recommendations and hope to improve the quality of it. Submitted filename: Response to Reviewers.docx Click here for additional data file. 26 Nov 2020 Detection and treatment of mental disorders in patients with coronary heart disease (MenDis-CHD): A cross-sectional study PONE-D-20-20310R2 Dear Dr. Peltzer, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Stephan Doering, M.D. Academic Editor PLOS ONE 4 Dec 2020 PONE-D-20-20310R2 Detection and treatment of mental disorders in patients with coronary heart disease (MenDis-CHD): A cross-sectional study Dear Dr. Peltzer: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Professor Stephan Doering Academic Editor PLOS ONE
  29 in total

Review 1.  Psychosocial perspectives in cardiovascular disease.

Authors:  Susanne S Pedersen; Roland von Känel; Phillip J Tully; Johan Denollet
Journal:  Eur J Prev Cardiol       Date:  2017-06       Impact factor: 7.804

2.  Depression and coronary heart disease: 2018 position paper of the ESC working group on coronary pathophysiology and microcirculation.

Authors:  Viola Vaccarino; Lina Badimon; J Douglas Bremner; Edina Cenko; Judit Cubedo; Maria Dorobantu; Dirk J Duncker; Akos Koller; Olivia Manfrini; Davor Milicic; Teresa Padro; Axel R Pries; Arshed A Quyyumi; Dimitris Tousoulis; Danijela Trifunovic; Zorana Vasiljevic; Cor de Wit; Raffaele Bugiardini
Journal:  Eur Heart J       Date:  2020-05-01       Impact factor: 29.983

3.  Satisfaction with mental health treatment among patients with a non-Western migrant background: a survey in a Danish specialized outpatient mental health clinic.

Authors:  Laura Glahder Lindberg; Sara Skriver Mundy; Maria Kristiansen; Katrine Schepelern Johansen; Jessica Carlsson
Journal:  Eur J Public Health       Date:  2019-08-01       Impact factor: 3.367

4.  Development and validation of the Patient Assessment of Chronic Illness Care (PACIC).

Authors:  Russell E Glasgow; Edward H Wagner; Judith Schaefer; Lisa D Mahoney; Robert J Reid; Sarah M Greene
Journal:  Med Care       Date:  2005-05       Impact factor: 2.983

5.  'I saw the panic rise in her eyes, and evidence-based medicine went out of the door.' An exploratory qualitative study of the barriers to secondary prevention in the management of coronary heart disease.

Authors:  William S M Summerskill; Catherine Pope
Journal:  Fam Pract       Date:  2002-12       Impact factor: 2.267

6.  Life satisfaction and mental health problems (18 to 35 years).

Authors:  D M Fergusson; G F H McLeod; L J Horwood; N R Swain; S Chapple; R Poulton
Journal:  Psychol Med       Date:  2015-03-25       Impact factor: 7.723

7.  Care Management Processes Used Less Often For Depression Than For Other Chronic Conditions In US Primary Care Practices.

Authors:  Tara F Bishop; Patricia P Ramsay; Lawrence P Casalino; Yuhua Bao; Harold A Pincus; Stephen M Shortell
Journal:  Health Aff (Millwood)       Date:  2016-03       Impact factor: 6.301

8.  General practitioners' opinions on how to improve treatment of mental disorders in primary health care. Interviews with one hundred Norwegian general practitioners.

Authors:  Arnstein Mykletun; Ann Kristin Knudsen; Tone Tangen; Simon Overland
Journal:  BMC Health Serv Res       Date:  2010-02-09       Impact factor: 2.655

9.  Primary care patients with anxiety and depression: need for care from the patient's perspective.

Authors:  Marijn A Prins; Peter F M Verhaak; Klaas van der Meer; Brenda W J H Penninx; Jozien M Bensing
Journal:  J Affect Disord       Date:  2009-05-05       Impact factor: 4.839

Review 10.  Does evidence support the American Heart Association's recommendation to screen patients for depression in cardiovascular care? An updated systematic review.

Authors:  Brett D Thombs; Michelle Roseman; James C Coyne; Peter de Jonge; Vanessa C Delisle; Erin Arthurs; Brooke Levis; Roy C Ziegelstein
Journal:  PLoS One       Date:  2013-01-07       Impact factor: 3.240
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