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The Effect of Cardiac Rehabilitation on Lipid Levels in Patients with Coronary Heart Disease. A Systematic Review and Meta-Analysis

Authors:

Gang Wu,

Department of Cardiology, Bengbu second people’s hospital, Bengbu, Anhui province, 233000, CN
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Yemei Hu,

Department of Cardiology, Bengbu second people’s hospital, Bengbu, Anhui province, 233000, CN
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Kun Ding,

Department of Cardiology, Bengbu second people’s hospital, Bengbu, Anhui province, 233000, CN
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Xuedong Li,

Department of Cardiology, Bengbu second people’s hospital, Bengbu, Anhui province, 233000, CN
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Jun Li,

Department of Cardiology, Bengbu second people’s hospital, Bengbu, Anhui province, 233000, CN
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Zhuo Shang

Bengbu second people’s hospital, No. 302 of Yan’ an Road, Bengbu, Anhui province, 233000, CN
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Abstract

Background: Cardiac rehabilitation (CR) is a multidisciplinary medical program. Most studies have emphasized the effect of exercise-based CR in lowering lipid levels; however, the effect of CR as a comprehensive program on lipid levels remains unclear.

Methods: Electronic database were searched up to 2022. Randomized controlled trials with lipid profile indicators were included. Standardized mean differences (SMDs) and 95% CIs were used to evaluate the effect size. Begg’s funnel plot and Egger’s linear regression test were used to assess publication bias.

Results: CR remarkably reduced low-density lipoprotein cholesterol (LDL-C) levels (SMD = –0.23; 95%CI: [–0.38, –0.08]; P < 0.001), triglyceride (TG) levels (SMD = –0.17; 95%CI: [–0.28, –0.06]; P < 0.001), and total cholesterol (TC) levels (SMD = –0.30; 95%CI: [–0.43, –0.16]; P < 0.001) and increased high-density lipoprotein cholesterol (HDL-C) levels (SMD = 0.19; 95%CI: [0.10, 0.29]; P < 0.001).

Conclusions: CR reduce TC, TG, and LDL-C levels while improving HDL-C levels. CR should be promoted and more trials should be conducted for long-term CR.

How to Cite: Wu G, Hu Y, Ding K, Li X, Li J, Shang Z. The Effect of Cardiac Rehabilitation on Lipid Levels in Patients with Coronary Heart Disease. A Systematic Review and Meta-Analysis. Global Heart. 2022;17(1):83. DOI: http://doi.org/10.5334/gh.1170
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  Published on 29 Nov 2022
 Accepted on 26 Oct 2022            Submitted on 20 Jul 2022

Introduction

Coronary heart disease (CHD) is a type of heart disease characterized by progressive coronary atherosclerotic lesions and the accumulation of fatty deposits along the inner layer of the coronary arteries, resulting in narrowing or blockage of coronary arteries and myocardial ischemia. CHD is a major component of cardiovascular disease and the leading cause of morbidity and mortality in the developed world [1, 2]. Patients diagnosed with CHD are at increased risk of premature death, myocardial infarction, and readmission to hospital. CHD is an important public health concern and economic burden worldwide [3]. According to clinical guidelines, secondary prevention strategies are crucial after diagnosis because controlling risk factors is the key to recurrence management [4].

Cardiac rehabilitation (CR) is an integration of multiple coordinated, intentional interventions that could offer a comprehensive platform for the administration of secondary prevention measures, such as evidence-based pharmacotherapy, cardiac risk factor management, nutritional counselling, patient education, and physical activity training [5, 6].

The proper control of risk factors, such as blood pressure and lipid levels, play an important role in decelerating disease progression and preventing recurrence and complications. Several meta-analyses have shown that exercise-based CR lowers blood lipid levels and blood pressure [7, 8]. However, CR is an integrated and comprehensive program; therefore, we have updated and supplemented the data with the aim to measure the effect of multiple modalities of CR on lipids.

Methods

We performed this systematic review and meta-analysis of trials to investigate CR interventions for patients with coronary heart disease (CHD) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.

Literature search strategy

Relevant studies were identified through a systematic search of the following electronic databases: MEDLINE, PubMed, EMBASE (Ovid), Web of Science, Scopus, and Cochrane Central Register of Controlled Trials up to 2022. The following Medical Subject Headings (MeSH) terms: ‘cardiac rehabilitation’ or ‘lifestyle change’ or ‘exercise training’ or ‘prevention program’ and ‘CHD’ or ‘CAD’ or ‘AMI’ or ‘ACS’ and ‘lipid profile’ or ‘HDL-C’ or ‘LDL-C’ or ‘TC’ or ‘TG’ were applied in our search strategy. We manually reviewed relevant review articles, reference lists of published trials, and conference abstracts (American Society of Clinical Oncology [ASCO], Annual Meetings, and the European Cancer Conference [ECCO]) for potentially eligible studies.

Inclusion and exclusion criteria for study collection

Studies were included if they met the following criteria: 1) controlled trials of cardiac rehabilitation (life modification, exercise training, etc.) regardless of whether it included allocation concealment or blinding; 2) adult (age ≥ 18 years) patients with coronary artery diseases (CAD) or CHD; 3) intervention group involved patients undergoing cardiac rehabilitation and control group included patients undergoing usual care or medication; and 4) measurement indicators were lipid profiles such as LDL-C, HDL-C, TC, TG. Studies were excluded if they conformed to the following criteria: 1) articles were not in English; 2) studies with a control group of home-based or community-based cardiac rehabilitation; and 3) studies with insufficient information or data. Two investigators independently checked whether each study met the inclusion criteria, and discrepancies were resolved by a third reviewer.

Data extraction

Two researchers independently extracted basic information from the included studies (title, first author, publication year, author information, and document source) and characteristics of study patients (sex, age, country, sample size, and interventions) for both the experimental and control groups and obtained outcome measurements. Any inconsistencies were resolved through consensus.

Quality assessment

Study quality was assessed using the Newcastle-Ottawa Scale (NOS). The total scores ranged from 0 to 9 points; trials considered ‘high quality’ scored higher than six. Two reviewers assessed the quality of the studies separately, and discrepancies were assessed by a third researcher.

Statistical analysis

Statistical analyses were performed using Stata statistical software (version 13.0; Stata Corp., College Station, TX, USA). SMD and 95% CIs were used to evaluate the effect size. The Q test and I2 analysis, with a significance level of <0.1 were employed to assess the heterogeneity between studies. Meta-regression analysis was used to analyze the source of heterogeneity. Begg’s funnel plot and Egger’s linear regression test were used to investigate the possibility of publication bias. Differences were considered statistically significant at P < 0.05.

Results

Literature selection

In total, 3,624 potentially relevant articles were identified through an online search. After careful examination of titles and abstracts, 3,397 were excluded; 1,565 publications were excluded as review articles and other ineligible types of references, 114 were non-English language articles, 227 included experiments on non-human species, 301 articles were duplicates, and 667 had non-targeted endpoints (Figure 1). The remaining 227 articles were retrieved for more detailed assessment. After screening the full text, 162 studies were further excluded because of incomplete data (n = 50), non-target interventions (n = 78), data that could not be extracted directly (n = 33), not including non-CHD patients (n = 6), unsuitable control groups (n = 6), and incomplete data (n = 3). Ultimately, 51 studies were included in the meta-analysis [9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59].

Diagram of including studies selection procedures
Figure 1 

Diagram of including studies selection procedures.

Characteristics of included studies

Fifty-one eligible studies with 10,286 patients were included, all of which were published between 1979 and 2022. The sample sizes ranged from 15 to 903 patients (median = 63). The age of all included patients ranged from 51 to 77.3 years old (median = 58.6); three studies had a three-arm parallel design, while forty-eight studies had a two-arm parallel design (CR and comparison). In Wosornu et al.’s [15] study, participants were assigned to three groups (control group, aerobic group, and strength group), which included people in CR, case-managed, and community-based groups. In a study by Volaklis et al., patients were grouped into land exercise, water exercise, and control. Nine studies were performed in the USA, five in the UK, six in Australia, four in Canada, three in Norway, three in HK, four in Sweden, two in Germany, two in Italy, two in Greece, fifteen studies from other countries. Forty-five studies collected TC measurements. Thirty-seven studies provided information on HDL-C as an endpoint, and forty-three studies used.

LDL-C as the endpoint. Thirty-eight studies used TG levels as the endpoint (Table 1).

Table 1

Characteristics of Including Studies.


AUTHOR COUNTRY TYPE OF DISEASE NO. OF PATIENT AGE MEAN (SD) GENDER(M/F) INTERVENTION NOS SCALE



T C T C T C

Kallio
1979
Finland AMI 183 187 54.4 54.1 151/37 150/37 Health education
Exercise training
6

Ornish
1990
USA CAD 22 19 56.1(7.5) 59.8(9.1) 21/1 15/4 Lifestyle modification 8

Schuler
1992
Germany CAD 56 57 52.8(5.8) 54.2(7.7) NA NA Lifestyle modification
Exercise training
8

Debusk
1994
USA AMI 293 292 57(8) 57(8) 230/63 231/61 Lifestyle modification
Exercise training
7

Fletcher
1994
USA CAD 16 19 62(8) 63(7) 16/0 19/0 Exercise training 6

Haskwell
1994
USA CAD 119 127 58.3(9.2) 56.2(8.2) 99/20 117/10 Lifestyle modification 7

Wosornua
1996
UK CAD 27 27 56.5(8.9) 56.6(7.0) 27/0 27/0 Aerobic exercise training 8

Wosornub
1996
UK CAD 27 27 59.2(6.4) 56.6(7.0) 27/0 27/0 Strength exercise
training
8

Gallacher
1997
UK CAD 198 209 NA NA NA NA Education
(Stress management)
8

Niebauer
1997
UK CAD 56 57 NA NA 56/0 57/0 Lifestyle modification
Exercise training
9

Ornish
1998
USA ACS 20 15 57.4(6.4) 61.8(7.5) 20/0 12/3 Lifestyle modification 9

Carlssona
1998
Sweden CAD 75 67 62.2(5.8) 61.7(6.0) 58/17 51/16 Lifestyle modification
Exercise training
8

Carlssonb
1998
Sweden CAD 31 32 62.7(4.8) 59.8(4.8) 26/5 27/5 Lifestyle modification
Exercise training
8

Bang
1999
Sweden CAD 46 41 53(7) 53(7) 37/9 36/5 Lifestyle modification 8

Toobert
2000
USA CHD 14 10 64(10) 63(11) NA NA Lifestyle modification 8

Belardinelli
2001
Italy and USA CAD 59 59 53(11) 59(10) 49/10 50/9 Exercise training 8

Gordon a
2002
USA CAD 45 52 60(9) 61(10) 34/11 38/14 Lifestyle modification
Education
8

Gordon b
2002
USA CAD 45 45 60(9) 60(9) 34/11 35/10 Lifestyle modification
Education
8

Vale
2002
Australia CAD 107 112 61.5(10.3) 60.6(9.5) 80/27 84/28 Education
Exercise training
7

Yu
2003
HK CHD 72 40 62.3(11.2) 61.2(10.2) 59/13 30/10 Exercise training 6

The Vestfold Heartcare Study Group 2003 Norway CHD 98 99 54(8) 55(8) 79/19 83/16 Lifestyle modification 8

Lear
2003
Canada CAD 151 151 64.8(8.8) 63.4(10.2) 125/26 124/27 Lifestyle modification 8

Vale
2003
Australia CHD 398 394 58.6(10.6) 58.3(10.3) 313/85 297/97 Education
Exercise training
7

Vona
2004
Italy AMI 28 24 56(6) 57(8) 21/7 19/5 Exercise training 7

Volaklisa
2007
Greece CAD; MI 12 10 53(4) 51(3) NA NA Exercise training 7

Volaklisb
2007
Greece CAD; MI 12 10 58 (3) 51(3) NA NA Exercise training 7

Zutz
2007
Canada CAD 8 7 58(4) 59(12) 7/1 5/2 Lifestyle modification 7

Naser
2008
Iran CHD 50 50 54.8 53.2 45/5 39/11 Lifestyle modification 7

Seki
2008
Japan CHD; ACS; MI 14 10 64(10) 63(11) NA NA Exercise training 7

Balen
2008
Croatia AMI 30 30 59 (9) 61 (10) 21/9 23/7 Exercise training 7

Murphy
2009
Ireland MI 444 459 68.5(9.3) 66.5(9.9) 311/133 320/139 Lifestyle
modification
Education
7

Zetta
2011
UK CAD 109 109 65.9(10.0) 64.8(10) 71/38 78/31 Lifestyle modification
Education
7

Munk
2011
Norway CAD 18 18 59.5(10) 60.7(9) 16/2 14/4 Exercise training 7

Moholdt
2012
Norway MI 59 30 57.5(9.3) 56.7(10.4) 49/10 25/5 Exercise training 7

Oerkild
2012
Denmark MI 19 21 77.3(6.0) 76.5(7.7) 12/7 11/10 Lifestyle modification
Education
8

Vernooij
2012
Netherland CAD 164 166 60.7(7.8) 59.2(8.9) 128/36 118/48 Lifestyle modification
Education
8

Luk
2012
HK CAD 32 32 67.7(9.0) 66.6(7.9) 24/8 24/8 Exercise training 7

Lear
2014
Canada CVD 38 40 59.2(10.7) 58.6(9) 34/4 32/8 Lifestyle modification
Exercise training
Education by internet
8

Raghuram
2014
India CAD 129 121 53.3(6.4) 52.6(6.9) NA NA Yoga training 8

Chow
2015
Australia CHD 352 358 57.9(9.1) 57.3(9.3) 287/65 295/63 Lifestyle modification 7

Hassan
2016
Egypt CAD 30 30 NA NA 21/9 20/10 Lifestyle modification
Education
8

Johnston
2016
Sweden MI 86 80 56.8(8.0) 58.4(8.6) 71/15 63/17 Lifestyle modification
Education
7

Tamburús
2016
Brazil CAD 15 17 NA NA NA NA Exercise training 8

Lin
2017
HK CAD 144 144 75.3(7.5) 74.3(7.5) 94/50 97/47 Education 7

Park
2017
South Korea AMI 32 32 57(12) 55(10) 29/3 27/5 Education 7

Dorje
2019
Australia MI; unstable or stable angina 156 156 59.1(9.4) 61.9(8.7) 128/28 126/30 Lifestyle modification
Education by Wechat
8

Maddison
2019
Australia; New Zealand CHD 82 80 61(13.2) 61.5(12.2) 69/13 70/10 Lifestyle modification
Education
8

Santo
2019
Australia CHD 107 56 58.4(9.0) 56.8
(8.6)
93/14 50/6 Education 7

Wienbergen
2019
Germany MI 143 138 56.5(9.1) 56.4
(10.3)
117/36 112/26 Education
telephone visits and telemetric risk factor control
8

Chaves
2019
Canada MI 12 11 60.7(13.3) 60.6
(8.4)
12/0 4/7 Lifestyle modification
Education
8

Zheng
2019
China AMI 411 411 56.2(9.3) 56.6 (9.7) 353/58 353/58 Lifestyle modification
Education by text messages
8

Campo
2020
Italy ACS 118 117 76(6) 76.6 (5.2) 92/26 89/28 Lifestyle modification
Education
8

Uddin
2020
USA CHD 71 71 54(6) 55(6) 66/5 63/8 Lifestyle modification
Education
8

Yudi
2021
Australia ACS 83 85 56.8(9.9) 56.2
(10.2)
71/12 69/16 Lifestyle modification
Education by smartphone
7

Dalli Peydro
2022
Spain ACS 31 28 57.5(9.0) 54.7(9.9) 27/4 27/1 Lifestyle modification
Education by
smartphone
7

ACS: acute coronary syndrome; AMI: acute myocardial infarction; CAD: coronary atherosclerotic heart disease; CHD: coronary heart disease; CVD: coronary vascular disease; MI: myocardial infarction; NA: not available; NOS: Newcastle–Ottawa Scale.

Meta-analysis results

TC levels

Forty-four out of 51 studies included in our analysis reported on TC levels after CR. The forest plot showed that ten studies had significantly lower TC serum levels in the intervention group. The results of the studies reported that CR could significantly reduce TC serum levels compared with control groups (SMD = –0.30; 95%CI: [–0.43, –0.16]; P < 0.001, Figure 2).

Forrest plot of TC levels after CR treatment. TC: total cholesterol; CR: cardiac rehabilitation; SMD: standardized mean difference
Figure 2 

Forrest plot of TC levels after CR treatment. TC: total cholesterol; CR: cardiac rehabilitation; SMD: standardized mean difference.

HDL-C levels

Thirty-seven out of 51 studies included in this analysis reported on HDL-C levels after CR. The forest plot showed that the HDL-C serum levels in three studies were significantly higher in the CR group than in the control group. The results of the overall study revealed HDL-C serum levels were remarkably increased after CR (SMD = 0.19; 95%CI: [0.10, 0.29]; P < 0.001, Figure 3).

Forrest plot of HDL-C levels after CR treatment. HDL-C: high-density lipoprotein cholesterol; SMD: standardized mean difference
Figure 3 

Forrest plot of HDL-C levels after CR treatment. HDL-C: high-density lipoprotein cholesterol; SMD: standardized mean difference.

LDL-C levels

Out of 51 studies, 42 included in this analysis reported on LDL-C levels after CR. The forest plot showed that the serum LDL-C levels in three studies were significantly lower in the CR group than in the control group. The results of the overall study revealed that compared with control group, LDL-C serum levels were reduced after CR (SMD = –0.23; 95%CI: [–0.38, –0.08]; P < 0.001, Figure 4).

Forrest plot of LDL-C levels after CR treatment. LDL-C: low-density lipoprotein cholesterol; SMD: standardized mean difference
Figure 4 

Forrest plot of LDL-C levels after CR treatment. LDL-C: low-density lipoprotein cholesterol; SMD: standardized mean difference.

TG levels

Out of 51 studies, 37 included in this analysis reported on TG levels after CR. The forest plot showed that TG serum levels in 10 studies were significantly lower in the CR group than in the control group. In the results of the overall study, significant decrease in serum TG levels were observed after CR (SMD = –0.17; 95%CI: [–0.28, –0.06]; P < 0.001, Figure 5).

Forrest plot of TG levels after CR treatment. TG: triglyceride; SMD: standardized mean difference
Figure 5 

Forrest plot of TG levels after CR treatment. TG: triglyceride; SMD: standardized mean difference.

Apolipoprotein A

Five out of 51 studies included in this analysis and reported on apolipoprotein A (ApoA) levels after CR. The forest plot of ApoA serum levels showed no significant differences between the CR and control groups (SMD = –0.46; 95%CI: [–1.22, 0.30]; P = 0.24, Figure S1).

Apolipoprotein B

Five out of 51 studies included in this analysis and reported on apolipoprotein B (ApoB) levels after CR. The forest plot of ApoB serum levels showed no significant differences between the CR and control groups (SMD = –0.94; 95%CI: [–2.01, 0.13]; P = 0.09, Figure S2).

Subgroup analysis

The subgroup analysis was performed based on the following factors: publication year, sample size (<100 or ≥100), region, number of interventions, and study quality (score <7 or score ≥7).

Subgroup analysis according to publication year

We executed a subgroup analysis based on publication year, and included studies were divided into three subgroups: before 2000, 2000–2010 and after 2010. CR could obviously increase HDL-C level in all three subgroups. However, CR significantly decreased LDL-C level in subgroups of before 2000 (SMD: –0.75; 95%CI: –1.12, –0.38) and after 2010 (SMD: –0.13; 95%CI: –0.38, –0.08). Remarkably reduced TC level in subgroups of before 2000 (SMD: –0.52; 95%CI: –0.81, –0.22) and 2000–2010 (SMD: –0.40; 95%CI: –0.70, –0.10) and lower TG level in subgroups of 2000–2010 (SMD: –0.29; 95%CI: –0.51, –0.06) and after 2010 (SMD: –0.23; 95%CI: –0.39, –0.08) were observed when compared with control group (Table S3–S6).

Subgroup analysis according to sample size

Stratified group analysis was conducted based on the sample size and the studies were divided into two subgroups: those with number of patients less than 100 (<100) and greater than or equal to 100 (≥100). Results showed that in subgroup of sample size <100, LDL-C level was significantly decreased after CR (SMD: –0.32; 95%CI: –0.59, –0.04). In subgroup of sample size ≥100, TC (SMD: –0.39; 95%CI: –0.55, –0.24) and TG (SMD: –0.22; 95%CI: –0.34, –0.10) levels were considerably reduced after CR (Table S4–S6).

Subgroup analysis according to the number of interventions

We also carried out the subgroup analysis in terms of number of interventions. Studies were divided into three subgroups: those with one type, two types and three types interventions. We found that HDL-C level was significantly improved in subgroup of one type intervention (SMD: 0.25; 95%CI: 0.11, 0.39) and two types interventions (SMD: 0.10; 95%CI: 0.02, 0.18) subgroup. LDL-C level was decreased in subgroup of two types interventions (SMD: –0.30; 95%CI: –0.49, –0.12). TC level was reduced in subgroup of one type (SMD: –0.32; 95%CI: –0.54, –0.11) and two types interventions (SMD: –0.30; 95%CI: –0.48, –0.13). TG levels were reduced in subgroup of one type (SMD: –0.20; 95%CI: –0.38, –0.02) and two types interventions (SMD: –0.12; 95%CI: –0.23, –0.01) (Table S3–S6).

Subgroup analysis according to different regions

Subgroup analysis was performed in accordance with studies conducted in different regions. Based on the region, the studies were divided into six subgroups including US and Canada, Europe, Asia-Pacific, country combination, Africa, and South America subgroups. Based on the pooled results, we found that in US and Canada subgroup, LDL-C (SMD: –0.60; 95%CI: –0.95, –0.26) and TC (SMD: –0.49; 95%CI: –0.85, –0.14) levels were significantly reduced. In Europe subgroup, HDL-C (SMD: 0.17; 95%CI: 0.06, 0.28) was significantly improved, TC (SMD: –0.49; 95%CI: –0.85, –0.14) was reduced. In Asia-Pacific subgroup, HDL-C was increased (SMD: 0.24; 95%CI: 0.02, 0.45) and, TG level was reduced (SMD: –0.25; 95%CI: –0.41, –0.09). In combination subgroup, HDL-C was enhanced (SMD: 0.39; 95%CI: 0.03, 0.76) and, LDL-C (SMD: –0.71; 95%CI: –1.08, –0.34), TC (SMD: –1.4; 95%CI: –1.8, –0.99) and TG (SMD: –0.57; 95%CI: –0.94, –0.20) levels were all reduced. In Africa and South America subgroup, CR had insignificant effect on outcomes (Table S3–S6). As for ApoA and ApoB, we found insignificant differences between CR group and control group. We also did not find any potential sources of heterogeneity in this analysis (Table S1–S6).

Publication bias

According to the results of Egger’s test and Begg’s funnel plots, there was no publication bias seen among TG, TC, HDL-C, LDL-C, ApoA, and ApoB. The details are presented in Table S7 and Figure S3.

Discussion

This study highlights the effect of CR on lipid levels in patients with CHD. According to our results, CR can significantly reduce serum LDL-C, TC, and TG levels and increase serum HDL-C levels. The ApoA and ApoB levels did not change significantly.

The conclusion of our study is not in accordance with that of previous studies. In Chen’s study, LDL-C and HDL-C levels were improved after aerobic exercise, but TG and TC serum levels did not substantially change [8]. They collected four articles to conduct their analysis, though we have assembled 51 studies in our systematic review. The reason for the varied results may be the small number of articles on lipid analysis included in their studies. Similarly inconsistent with our conclusion, a meta-analysis by Javaherian et al. indicated that CR considerably reduced serum LDL-C, TC, and TG levels; however, no marked change was observed in HDL-C serum levels. They evaluated exercise-based CR and focused on all types of CR, including exercise, education, lifestyle modification, and so on. First, their CR range was more comprehensive. Second, our number of included articles was higher than that in their study. Third, they selected patients with cardiovascular disease (CVD) for analysis, while we restricted our review to patients with CHD. Few studies have focused on ApoA and ApoB; thus, the data were not sufficient.

In the subgroup analysis, we found that in one type and two types interventions subgroup, HDL-C levels were enhanced; LDL-C and TC levels were reduced. However, all endpoints found no significant differences in three types interventions subgroup; this might be due to inclusion of inadequate number of studies, (For each endpoint, only one study was included in three types interventions group). In subgroup of before 2000, LDL-C and TC levels were decreased. In subgroup of after 2010, LDL-C and TG levels were reduced. HDL-C was increased in all three subgroups according to the publication years. TC and TG levels were reduced in subgroup of sample size ≥100; LDL-C level was decreased after CR in studies with sample size<100. HDL-C, LDL-C, TG, and TC levels in group with study quality score higher than seven were obviously affected in positive way after CR. In terms of region, there were no magnificent differences observed in studies conducted in Africa and South America region after CR. Nevertheless, in other three regions, CR had remarkable effects on HDL-C, LDL-C, TC and TG. This difference might have been caused firstly by the inclusion of inadequate number of studies in Africa and South America region. Secondly, medical skills, types of insurance for commercially insured patients with different socioeconomic status and medication adherence were in different regions (Table S1-S6).

This study focused on comprehensively investigating the effects of CR on lipid profiles. In this study, CR was widely defined and not limited to specific types, such as exercise training. Moreover, all the trials included in this study were randomized controlled trials. Another strength of our study is the number of trials we were able to include in this review. Fifty-one articles provide a sufficient amount of trials for review. Consequently, our conclusions are hypothesized to be more reliable because of the larger number and higher quality of studies that we were able to incorporate in our systematic review.

Limitations

Our analysis has some limitations. First, although the subgroup analysis was performed using a fixed model, the source of heterogeneity was still not observed. Second, in over 50 studies, most patients were male, and due to a lack of data assessing CR effect by sex, a subgroup analysis of sex was not performed. Third, we included articles only in English, and all other non-English and written literatures were excluded. Considering these limitations, the results should be interpreted with caution.

Conclusion

In conclusion, this study illustrates that CR can reduce the levels of TC, TG, and LDL-C and improve levels of HDL-C. However, ApoA and ApoB levels did not change significantly after CR. Considering the efficacy of CR on improving blood lipid levels, which plays an important role in delaying disease progression and preventing recurrence and complications, CR should be widely promoted, and more clinical trials should be conducted regarding the long-term effects of CR.

Data Accessibility Statement

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Additional Files

The additional files for this article can be found as follows:

Supplementary Figures

Figures S1 to S3. DOI: https://doi.org/10.5334/gh.1170.s1

Supplementary Tables

Tables S1 to S7. DOI: https://doi.org/10.5334/gh.1170.s2

Acknowledgements

We would like to thank Editage (www.editage.cn) for English language editing.

Funding information

This research was supported by Research Program of Health Commission of Anhui.

Province. Grant Number: AHWJ2021b095.

Competing Interests

The authors have no competing interests to declare.

Authors contributions

ZS contributed to conception and design of the research. GW contributed to data collection, and data analysis. YH contributed to data analysis. KD contributed to manuscript writing. XL and JL contributed to revising the manuscript critically for important intellectual content. All authors have read and approved the manuscript.

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