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. 2024 Dec 15;17(3):584–600. doi: 10.1016/j.chmed.2024.12.002

Traditional Chinese medicine formulas alleviated acute pancreatitis via improvement of microcirculation: A systematic review and meta-analysis

Ji Gao a,1, Chenxia Han a,1, Ning Dai b, Wen Wang c, Tao Jin a, Dan Du d,⁎, Qing Xia a,⁎
PMCID: PMC12301921  PMID: 40734918

Abstract

Objective

Microcirculatory disturbance is pathologically critical to acute pancreatitis (AP), which can be effectively alleviated by traditional Chinese medicine (TCM) formulas that activate blood flow. However, there has been no evidence-based research to date. Therefore, a well-designed systematic review and meta-analysis is necessary to elucidate the therapeutic transformative benefit of improving microcirculation during AP. This study aims to confirm the therapeutic efficacy of TCM formulas and explore the potential mechanisms underlying their effects on AP treatment.

Methods

Studies from eight databases including Pubmed, Embase, Web of Science, Cochrane Library, CNKI, CBM, Wanfang, and Chinese VIP, were screened for the eligible randomized controlled trials (RCTs). The APACHE II score and effectiveness rate were set as primary outcomes, while mortality rate, complications, total hospital stays, serum amylase recovery time, the time until the disappearance of abdominal pain, microcirculation indicators, and inflammation indicators were chosen as secondary outcomes. A systematic review and meta-analysis were subsequently conducted. Network pharmacology analysis was performed to analyze potential bioactive components with relevant targets of the core herbs included in the TCM formulas for activating blood flow.

Results

A total of 51 RCTs (n = 3 721) were included. Compared with conventional western medical treatments alone, TCM groups were associated with lower APACHE II score (SMD =  − 1.36, 95% CI: −2.01 to − 0.71, P = 0.000) and higher effectiveness rate (RR: 1.22, 95% CI: 1.18 to 1.26, P = 0.000). Furthermore, the formulas for activating blood flow demonstrated significant efficacy in improving both microcirculation and inflammation indicators. Additionally, six core Chinese herbal medicines including Rhei Radix et Rhizoma with the highest frequency, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, and Corydalis Rhizoma were filtered out from the adopted TCM formulas. Finally, 166 shared targets between the six herbs and AP were identified. KEGG analysis indicated that lipid and atherosclerosis pathway is highly related to microcirculation.

Conclusion

TCM formulas for activating blood flow significantly improve microcirculation and alleviate AP. Further high-quality, well-designed RCTs and deep mechanism exploration are required.

Keywords: acute pancreatitis, activating blood flow, microcirculatory disturbance, meta-analysis, network pharmacology, Rhei Radix et Rhizoma

1. Introduction

Acute pancreatitis (AP) is one of the most common gastrointestinal emergencies with an increasing global incidence of 34/100 000 (Garg et al., 2019, Petrov and Yadav, 2019). Gallstones, alcohol, and hypertriglyceridemia are critically primary causes of AP. Approximately 20% of AP patients suffer from severe attacks (severe AP, SAP), which can result in a mortality rate as high as 40% (Boxhoorn, Voermans, van Santvoort, & Besselink, 2021). It’s noteworthy that splanchnic vein thrombosis, as a classic SAP pathology, maintains a high occurrence in clinical AP cases ranging from 17% to 22.6%, which is even more prevalent in complicated AP (Anis et al., 2022, Butler et al., 2011, Zhang et al., 2024).

Pancreatic microcirculatory disturbance is a dual contributor to and victim of SAP. The increased permeability of capillaries within the pancreas, along with the influence of various hormones on pancreatic blood flow, results in the provision of terminal arteries to pancreatic lobules, rendering pancreatic tissue vulnerable to ischemia events (Sunamura et al., 1998, Watanabe et al., 1997). After AP onset, trypsin becomes pre-activated and triggers autolysis of pancreatic acinar cells, which further leads to tissue ischemia and hypoxia, microvascular spasm, vascular endothelial cell dysfunction, heightened vascular permeability, and ultimately alterations in blood rheology (Popel & Johnson, 2005). These changes result in pancreatic microcirculatory disturbances that persistently progress SAP. In the presence of inflammatory and vascular events, the comprehensive activation of exogenous and endogenous coagulation pathways further aggravates microcirculatory disturbances and causes disseminated intravascular coagulation (DIC) (Hack, 2000, Sawa et al., 2006). The depletion of coagulation-associated substances leads to a hyperactive fibrinolytic system (Chapin & Hajjar, 2015). Therefore, inflammation-vascular-microcirculation is an important mechanism chain in the progression of AP, and improving pancreatic microcirculation could bring a major breakthrough in therapy strategy.

It has been widely accepted that in traditional Chinese medicine (TCM) theories, toxic and stasis are the basic causes of AP, while blood stasis is an important pathological product of disease development. The general treatment principles for AP mainly include catharsis, moving qi, getting rid of heat, and removing blood stasis (Ma, Liang, Xu, Zhao, & Hu, 2019). Therefore, formulas to activate blood circulation and eliminate blood stasis have been widely used for a long time in AP’s TCM treatments (Song et al., 2019). The formulas for activating blood flow are a series of TCM formulas that remove blood stasis and activate peripheral circulation. Numerous studies have shown formulas for activating blood flow have great advantages over relieving AP (Yang, Wang, & Yue, 2014). However, no evidence-based research has been reported. Some studies have evaluated related drugs for activating blood flow with poor sample sizes and inadequate coverage of drugs (Zou & Hu, 2013). Initially, the present study conducted a comprehensive evidence-based medical evaluation of TCM formulas for activating blood flow in the treatment of AP. Furthermore, a network pharmacology analysis based on the meta-analysis was performed to discover core Chinese herbal medicines, potential usage patterns, as well as the targets and functional pathways of the formulas, in order to guide clinical decision-making and provide directions for subsequent studies.

2. Materials and methods

2.1. Meta-analysis

This meta-analysis was conducted in line with the guidelines provided by Cochrane Handbook 6.3 (Higgins et al., 2022), the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Page et al., 2021), and the PRISMA extension for Chinese herbal medicines 2020 (Zhang et al., 2020). The protocol of this study was registered in PROSPERO (CRD42023424604).

2.1.1. Search strategy

Studies from eight electronic databases, including Pubmed, Embase, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature (CBM), Wanfang Database, and VIP Information-China Science and Technology Journal Database, were retrieved before March 2023 for relevant publications. MeSH terms, keywords, abstract, or title for retrieval included “Medicine, Chinese Traditional” or “Traditional Chinese Medicine” or “Chinese decoction” or “Chinese formula” or “Chinese patent medicine” or “herb therapy”, “Pancreatitis” or “acute pancreatitis”, “randomised controlled trial” or “random*” or “Random allocation” or “clinical study” or “trial*” or “RCT”. There was no language limitation. The search results were manually imported into the literature management software Endnote X9 (Thomson Reuters). Details of the search strategies and screening process were shown in Supporting Information S1.

2.1.2. Inclusion criteria

(1) Types of studies: randomized controlled trials (RCTs) which have assessed the efficacy of TCM formulas by activating blood flow for AP were included in this study. (2) Types of participants: the patients enrolled in this review should meet the basic diagnostic criteria for AP which includes at least two of the below three manifestations: unbearable acute abdominal pain which is typical for AP; serum amylase and/or lipase was three times or more than the upper normal limitation; characteristic computed tomography imaging of AP (Banks et al., 2013). There was no restriction on gender or nationality for the sake of including relevant studies as comprehensively as possible. (3) Types of interventions: both groups received conventional western medical treatments (CWM), while the treatment group supplemented with TCM formulas for activating blood flow. The formulas for activating blood flow included classical TCM formulas for activating blood circulation and resolving blood stasis, such as Fuyuan Huoxue decoction, Buyang Huanwu decoction, Xuefu Zhuyu decoction, Taohong Siwu decoction, et al. Besides, if the formula's name included the words “huoxue” or “huayu” or “tongyu” or “zhuyu” or “gongyu” or “xiaoyu” or “quyu” with its TCM medical rule or function aiming at activating blood circulation and resolving blood stasis, the formula may be included. Detailed definitions for treatments were shown in Supporting Information S2.

2.1.3. Exclusion criteria

(1) Types of studies: clinical experiences, reviews, commentaries, theoretical researches, case reports, letters, and experimental studies. (2) Types of participants: age < 18. (3) Types of interventions: other TCM medical therapies alone or beyond the formulas for activating blood flow, such as acupuncture, moxibustion, cupping, massage, and music therapy, were used for either treatment or control group; Inconsistent basic therapies in both groups; the route of administration is not internal intake, such as enema or intravenous injection. (4) Unable to download the full text. (5) Duplicate publications.

2.1.4. Outcome measures

Primary outcomes: APACHE II score and effectiveness rate. APACHE II score contains acute physiology score, age points and chronic health points. It could be essential in determining the group of patients who have more chance of requiring tertiary care in the course of treatment and evaluating the severity of the disease which was found to correlate well with some platelet indicators (Mimidis et al., 2004). Effectiveness rate is defined as (number of people cured in per group + number of people effective in per group + number of people remission in per group) divided by the total included patients in each group.

Secondary outcomes: mortality rate, complications, total hospital stays, serum amylase recovery time, the time until the disappearance of abdominal pain, microcirculation indicator (D-D, D-dimer; PAF, platelet-activating factor; FIB, fibrinogen; ET, endothelin; TXA2, thromboxane A2; NO, nitric oxide; PGI2, prostaglandin I2), and inflammation indicator (TNF-α, tumor necrosis factor-α; IL-6, interleukin-6; IL-1β, interleukin-1β; CRP, C-reactive protein; HMGB1, high mobility group box protein 1).

2.1.5. Data extraction and assessment of risk of bias

The study selection was conducted by two reviewers (GJ and HCX) according to the inclusion and exclusion criteria, and then they independently extracted data with cross-checking after extraction.

According to the tools in the Cochrane Handbook for the Systematic Review of Interventions (Higgins et al., 2022), the risk of bias for each eligible study was evaluated independently by two investigators (GJ and HCX). The evaluation by Review Manager 5.3 included seven aspects: Random sequence generation about selection bias; Allocation concealment about selection bias; Blinding of participants and personnel about performance bias; Blinding of outcome assessment about detection bias; Incomplete outcome data about attrition bias; Selective reporting about reporting bias; Other bias.

Any disagreements were resolved through the third reviewer (DN).

2.1.6. Quality assessment

The quality of evidence for each outcome was assessed with the Grading of Recommendations Assessment Development and Evaluation (GRADE) system. A summary of findings table for outcomes was performed through GRADEpro3.2 (https://gdt.gradepro.org). Evidence quality was categorized into four levels: very low, low, moderate, and high (Guyatt et al., 2008).

2.1.7. Data synthesis and statistical analyses

We conducted the statistical analyses using STATA software version 12.0 (Stata Corp., College Station, TX, USA). The risk ratio (RR) for binary variables and the standard mean difference (SMD) corresponding to the 95% confidence interval (CI) for continuous variables were examined for combined effect size. The heterogeneity was evaluated by the chi-square and I2 test. If significant heterogeneity was observed among the included studies (P < 0.05 or I2 > 50%), a random-effects model was adopted for statistical analysis; otherwise, a fixed-effects model was used for estimates (Higgins et al., 2003). The subgroup analysis or meta-regression would be conducted to assess the source of the heterogeneity. If there were more than ten studies with high heterogeneity, meta-regression would be conducted for investigation using the characteristics of the AP population, the year of publication, the sample size, the administration route of the formulas for activating blood flow, and the study duration as covariates. The subgroup analysis was carried out to assess the source of the significant heterogeneity according to the same classifications of meta-regression. Sensitivity analysis was performed to determine the stability of the results. Additionally, Funnel plots, Begg’s test, and Egger’s test were used only for at least ten studies to help test the potential publication bias. A P < 0.05 indicated statistical significance.

2.2. Network pharmacology analysis

Formulas andChinese herbal medicines were extracted from the included studies in the meta-analysis. The names of herbs were normalized by the Chinese Pharmacopoeia (2015 edition, China Pharmaceutical Science and Technology Publishing House). SPSS Modeler 18.0 software was used for association rules analysis (Cai, Zhang, Zhu, & Zhu, 2001), and we set the threshold of “support degree” to 20%, the confidence level to 80%, and the maximum number of antecedents to 2 to help analyze medication rules and obtain potential core drugs (Jiang et al., 2023).

The TCMSP database (https://tcmspw.com/tcmsp.php) and TCMIP database (https://www.tcmip.cn) were commonly used to screen the ingredients and targets of the six core drugs, which were selected according to the optimal toxicokinetic rules including absorption, distribution, metabolism, and excretion (ADME) by oral bioavailability (OB) and drug-likeness (DL) (OB ≥ 30%, DL ≥ 0.18) (Wei et al., 2021) and which drug-likeness grading with weak would be rounded off. Literature was also supplemented for the active ingredients and target proteins. The Uniprot database (https://www.Unitprot.org) was utilized to normalize the gene names of target proteins. The targets of AP were searched with the keyword “acute pancreatitis” in four databases, including the OMIM database (https://www.omim.org), Gene Cards (https://www.genecards.org/), DisGeNET database (https://www.disgenet.org/), and Drug Bank (https://www.drugbank.ca/). A venn diagram was conducted to obtain the shared targets between the bioactive ingredients of the six herbs and AP. The common targets were imported into Cytoscape 3.7.1 software to construct the “herb-component-target relationship network” and used to predict the potential mechanisms of the six core herbs in treating AP.

Through the STRING database (https://stringdb.org/), we constructed a PPI network for the shared targets with the “minimum required interaction score: high confidence (0.700)”. The related protein nodes were then imported into the Cytoscape 3.7.1 software for PPI network analysis and identified the hub target which degree value was twice greater than the median degree value of all targets (Wei et al., 2021). Gene ontology (GO) enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) signal pathway enrichment analysis were conducted using the Metascape database (http://metascape.org).

3. Results

3.1. Meta-analysis

3.1.1. Literature search and study characteristics

The flow chart for literature selection was given in Fig. 1. In total, 11 172 potentially related records were derived from the eight databases. After removing duplicates and screening the titles and abstracts, 2865 studies remained. Next, 2 814 studies were excluded. Ultimately, 51 RCTs (Wang, 2008a, Wang, 2008b, Chen, 2015, Zhou, 2015, Xiong, 2018, Zhuang et al., 2018, Yang et al., 2019, Yang et al., 2019, Zhang et al., 2021, Mu and Li, 2021, Mao, 2006, Fang et al., 2007, Wang, 2008a, Wang, 2008b, Zhou and Wu, 2009, Zhao, 2010, Ou, 2011, Tian, 2012, Wang, 2013, Jiang, 2013, Zheng, 2014, Kong et al., 2015, Sha et al., 2016, Zhao, 2017, Niu, 2017, Chen et al., 2018, Li et al., 2018, He et al., 2018, Lu et al., 2018, Jiang, 2019, Ma et al., 2019, Zhu, 2019, Mao et al., 2019, Wang et al., 2019, Yang and Chen, 2019, Huang et al., 2020, Kong et al., 2020, Zhao et al., 2020, Wu, 2021, Fu et al., 2021, Guo et al., 2021, Gao et al., 2021, Xuan et al., 2021, Xiao et al., 2022, Wang and Wang, 2022, Jiang and Wang, 2015, Chen, 2001, Dong and Guo, 2005, Yuan et al., 2018, Qu et al., 2021, Zhu et al., 2017, Zhao, 2018, Li and Zhang, 2016) with a total of 3 721 participants were included in this meta-analysis, with a sample size ranging from 31 to 124. All of the studies were carried out in China and published between 2001 and 2022. The enrolled trials assessed the effects of the formulas for activating blood flow combined with CWM compared to CWM alone. The name, usage and dosage of western medicine used in the TCM group were consistent with those in the CWM group. The duration of treatment varied from 5 to 30 d. The main characteristics were summarized in Table S1. More detailed information such as the herb components on the formulas for activating blood flow was shown in Table 1.

Fig. 1.

Fig. 1

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PRISMA flow diagram of study selection and identification.

Table 1.

Herb components of TCM formulas in included 51 studies.

Formulas Herb components References
Qingxia Huayu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Gardeniae Fructus, Sargentodoxae Caulis Jiang, 2013
Qingxia Huayu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Gardeniae Fructus, Sargentodoxae Caulis Chen, 2015
Qingxia Huayu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Gardeniae Fructus, Sargentodoxae Caulis, Aurantii Fructus Kong, Wang, Zhou, Jiang, & Li, 2015
Qingxia Huayu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Natrii Sulfas, Gardeniae Fructus, Sargentodoxae Caulis Li & Zhang, 2016
Qingxia Huayu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Gardeniae Fructus, Sargentodoxae Caulis Kong et al., 2020
Qingxia Huayu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Gardeniae Fructus, Sargentodoxae Caulis, Aurantii Fructus Zhou, 2015
Qingxia Huayu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Gardeniae Fructus, Sargentodoxae Caulis, Aurantii Fructus Wang & Wang, 2022
Chaihuang Qingyi Huoxue Granule Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Glycyrrhizae Radix et Rhizoma, Gardeniae Fructus, Paeoniae Radix Alba, Astragali Radix, Taraxaci Herba Zhu et al., 2017
Chaihuang Qingyi Huoxue Granule Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Glycyrrhizae Radix et Rhizoma, Gardeniae Fructus, Paeoniae Radix Alba, Astragali Radix, Taraxaci Herba Wang, Xi, & Xi, 2019
Chaihuang Qingyi Huoxue Granule Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Glycyrrhizae Radix et Rhizoma, Gardeniae Fructus, PaeoniaeRradix Alba, Astragali Radix, Taraxaci Herba Yang et al., 2019
Chaihuang Qingyi Huoxue Granule Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Glycyrrhizae Radix et Rhizoma, Gardeniae Fructus, Paeoniae Radix Alba, Astragali Radix, Taraxaci Herba Yang et al., 2019
Chaihuang Qingyi Huoxue Granule Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Glycyrrhizae Radix et Rhizoma, Gardeniae Fructus, Paeoniae Radix Alba, Astragali Radix, Taraxaci Herba Fu, Lu, Song, Jiang, & Li, 2021
Chaihuang Qingyi Huoxue Granule Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Glycyrrhizae Radix et Rhizoma, Gardeniae Fructus, Paeoniae Radix Alba, Astragali Radix, Taraxaci Herba Qu, Zeng, & Zhu, 2021
Tongxia Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Magnoliae Officinalis Cortex, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Paeoniae Radix Alba, Curcumae Radix, Poria, Pinelliae Rhizoma, Herba Patriniae, Dioscoreae Rhizoma Wang, 2013
Tongxia Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Paeoniae Radix Alba, Poria, Pinelliae Rhizoma, Herba Patriniae, Dioscoreae Rhizoma Niu, 2017
Tongxia Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Natrii Sulfas, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Carthami Flos, Astragali Radix Yuan et al., 2018
Tongxia Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Magnoliae Officinalis Cortex, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Paeoniae Radix Alba, Curcumae Radix, Poria, Pinelliae Rhizoma, Herba Patriniae, Dioscoreae Rhizoma Zhuang, Lu, Wen, & Lin, 2018
Huayu Tongfu Mixture Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Natrii Sulfas Dong & Guo, 2005
Huayu Tongfu Mixture Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Natrii Sulfas Zhao, 2010
Huayu Tongfu Mixture Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Natrii Sulfas Ou, 2011
Huoxue Qingjie Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Persicae Semen, Natrii Sulfas, Coptidis Rhizoma Sha, Liang, Zhu, Wang, & Zhu, 2016
Huoxue Qingjie Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Persicae Semen, Natrii Sulfas, Coptidis Rhizoma Lu, Wang, & Guo, 2018
Huoxue Qingjie Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Persicae Semen, Natrii Sulfas, Coptidis Rhizoma Jiang, 2019
Qingre Tongfu Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Magnoliae Officinalis Cortex, Natrii Sulfas, Gardeniae Fructus, Coptidis Rhizoma, Aucklandiae Radix Zhao, 2017
Qingre Tongfu Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Corydalis Rhizoma, Scutellariae Radix, Magnoliae Officinalis Cortex, Natrii Sulfas, Carthami Flos, Moutan Cortex, Chuanxiong Rhizoma, Curcumae Radix, Taraxaci Herba, Curcumae Rhizoma, Sparganii Rhizoma, Forsythiae Fructus, Phellodendri Chinensis Cortex Zhao, 2018
Qingre Tongfu Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Magnoliae Officinalis Cortex, Natrii Sulfas, Gardeniae Fructus, Coptidis Rhizoma, Aucklandiae Radix Yang & Chen, 2019
Fuyuan Huoxue Decoction Rhei Radix et Rhizoma, Bupleuri Radix, Persicae Semen, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Carthami Flos, Trichosanthis Fructus, Manis Squama Wang, 2008a, Wang, 2008b
Fuyuan Huoxue Decoction Rhei Radix et Rhizoma, Bupleuri Radix, Persicae Semen, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Carthami Flos, Trichosanthis Fructus, Manis Squama Wang, 2008a, Wang, 2008b
Dahuang Zhuyu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Corydalis Rhizoma, Persicae Semen, Magnoliae Officinalis Cortex, Natrii Sulfas, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Moutan Cortex, Aurantii Fructus, Citri Reticulatae Pericarpiu, Semen Benincasae Huang et al., 2020
Dahuang Zhuyu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Corydalis Rhizoma, Persicae Semen, Magnoliae Officinalis Cortex, Natrii Sulfas, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Moutan Cortex, Aurantii Fructus, Citri Reticulatae Pericarpium, Benincasae Semen Wu, 2021
Qingyi Huoxue Decoction Rhei Radix et Rhizoma, Paeoniae Radix Rubra, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Coptidis Rhizoma, Astragali Radix, Moutan Cortex, Chuanxiong Rhizoma, Alismatis Rhizoma, Plantaginis Semen, Ophiopogonis Radix, Ginseng Radix et Rhizoma Guo, Guo, & Wang, 2021
Qingyi Huoxue Decoction Rhei Radix et Rhizoma, Paeoniae Radix Rubra, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Coptidis Rhizoma, Astragali Radix, Moutan Cortex, Chuanxiong Rhizoma, Alismatis Rhizoma, Plantaginis Semen, Ophiopogonis Radix, Ginseng Radix et Rhizoma Xuan, Chen, & Xuan, 2021
Qingyi Huayu Jiedu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Magnoliae Officinalis Cortex, Coptidis Rhizoma, Sargentodoxae Caulis, Poria, Aucklandiae Radix, Artemisiae Scopariae Herba, Alismatis Rhizoma, Atractylodis Macrocephalae Rhizoma, Linderae Radix Chen, Wang, & Wang, 2018
Qingyi Huayu Jiedu Decoction Rhei Radix et Rhizoma, Paeoniae Radix Rubra, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Natrii Sulfas, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Coptidis Rhizoma, Carthami Flos, Moutan Cortex, Chuanxiong Rhizoma, Aurantii Fructus, Faeces Trogopterpri, Rehmanniae Radix Praeparata Zhang et al., 2021
Fuzheng Zhuyu Xiehuo Decoction Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Glycyrrhizae Radix et Rhizoma, Paeoniae Radix Alba, Astragali Radix, Aurantii Fructus, Poria, Pinelliae Rhizoma, Curcumae Rhizoma, Sparganii Rhizoma, Citri Reticulatae pericarpium, Trichosanthis Fructus, Artemisiae Scopariae Herba, Atractylodis Macrocephalae rhizoma, Crataegi Fructus, Amomi Fructus Rotundus Xiao, Xu, Zhou, & Tan, 2022
Xuanfu Huayu Decoction Glycyrrhizae Radix et Rhizoma, Curcumae Radix, Poria, Pinelliae Rhizoma, Forsythiae Fructus, Faeces Trogopterpri, Haematitum, Lysimachiae Herba, Typhae Pollen, Inulae Flos, Gleditsiae Spina Chen, 2001
Buyang Huanwu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Persicae Semen, Natrii Sulfas, Coptidis Rhizoma Jiang & Wang, 2015
Xuefu Zhuyu Oral Liquid Paeoniae Radix Rubra, Bupleuri Radix, Persicae Semen, Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Carthami Flos, Chuanxiong Rhizoma, Aurantii Fructus, Rehmanniae Radix Praeparata, Platycodonis Radix, Achyranthis Bidentatae Radix Zheng, 2014
Tongfu Xingqi Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Salviae Miltiorrhizae Radix et Rhizoma, Chuanxiong Rhizoma, Curcumae Rhizoma, Sparganii Rhizoma, Faeces Trogopterpri, Lonicerae Japonicae Flos, Olibanum, Dalbergiae Odoriferae Lignum Xiong, 2018
Tongfu Huoxue Jiedu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Gardeniae Fructus, Angelicae Sinensis Radix, Aucklandiae Radix Li, Ling, Feng, & Wang, 2018
Huoxue Huayu Decoction Salviae Miltiorrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Chuanxiong Rhizoma, Olibanum, Myrrha, Zingiberis Rhizoma Praeparatum, Cinnamomi Cortex, Cyperi Rhizoma He, Feng, Zhu, Yao, & Liu, 2018
Shugan Qingxie Quyu Decoction Rhei Radix et Rhizoma, Paeoniae Radix Rubra, Bupleuri Radix, Corydalis Rhizoma, Persicae Semen, Natrii Sulfas, Angelicae Sinensis Radix, Carthami Flos, Chuanxiong Rhizoma, Aurantii Fructus, Curcumae Radix, Aucklandiae Radix Zhu, 2019
Huoxue Tongyi Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Magnoliae Officinalis Cortex, Natrii Sulfas, Poria, Crataegi Fructus, Hordei Fructus Germinatus, Massa Medicata Fermentata Ma et al., 2019
Qingre Jiedu Quyu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Scutellariae Radix, Magnoliae Officinalis Cortex, Natrii Sulfas, Chuanxiong Rhizoma, Forsythiae Fructus, Lonicerae Japonicae Flos Mao, Feng, Zhang, Zhu, & He, 2019
Qingyi Huoxue Tongyu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Coptidis Rhizoma Mu & Li, 2021
Jiedu Quyu Tongfu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Bupleuri Radix, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Natrii Sulfas, Glycyrrhizae Radix et Rhizoma, Gardeniae Fructus, Paeoniae Radix Alba, Coptidis Rhizoma, Sargentodoxae Caulis, Carthami Flos, Moutan Cortex Gao & Zhou, 2021
Tongfu Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Corydalis Rhizoma, Scutellariae Radix, Persicae Semen, Magnoliae Officinalis Cortex, Natrii Sulfas, Carthami Flos, Moutan Cortex, Curcumae Radix, Curcumae Rhizoma, Sparganii Rhizoma Mao, 2006
Tongfu Huoxue Granule Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Persicae Semen, Magnoliae Officinalis Cortex, Natrii Sulfas, Aucklandiae Radix Zhao, Huang, Ni, & Qin, 2020
Tongxia Huayu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Corydalis Rhizoma, Natrii Sulfas, Moutan Cortex, Curcumae Radix, Polygoni Cuspidati Rhizoma et Radix Fang et al., 2007
Gongxia Zhuyu Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Persicae Semen, Magnoliae Officinalis Cortex, Natrii Sulfas, Sargentodoxae Caulis, Carthami Flos, Moutan Cortex, Herba Patriniae, Arecae Pericarpium, Sennae Folium, Citri Reticulatae Semen, Litchi Semen Zhou & Wu, 2009
Qingyi Liqi Huoxue Decoction Rhei Radix et Rhizoma, Aurantii Fructus Immaturus, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, Scutellariae Radix, Gardeniae Fructus, Paeoniae Radix Alba, Curcumae Radix, Pinelliae Rhizoma, Artemisiae Scopariae Herba, Jujubae Fructus, Zingiberis Rhizoma Recens Tian, 2012
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3.1.2. Risk of bias assessment

The included 51 RCTs were evaluated separately for bias to determine the impact on the conclusions. The quality assessment of the included studies, with a summary and graph of the risk of bias, was shown in Fig. 2. A total of 26 RCTs had a low risk of bias in the generation of random sequence generation while the rest did not. Just one RCT illustrated the method of allocation concealment, with the others unclear. For blinding of participants and personnel and blinding of outcome assessment, all of the studies did not specify the relevant information. Additionally, most of the studies had a low risk of bias for incomplete outcome data, except for one. All RCTs had a low risk of bias in selective reporting. Besides, the other sources of bias for all studies were unclear.

Fig. 2.

Fig. 2

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Risk of bias summary (A) and bias graph (B).

3.1.3. Primary outcomes

As indicated in Fig. 3, nine studies involving 659 patients reported the APACHE II score with significant heterogeneity (P = 0.000, I2 = 92.6%), thus a random-effects model was conducted for analysis. The pooled results indicated that the treatment for activating blood flow effectively reduced the APACHE II score compared to conventional western medical treatment (SMD =  −1.36, 95% CI: −2.01 to −0.71, P = 0.000). No potential source of heterogeneity was found.

Fig. 3.

Fig. 3

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Forest plot following meta-analysis of the APACHE II score in Acute pancreatitis (AP) patients after treating with TCM formulas for activating blood flow.

For effectiveness rate, 38 studies of 2 887 AP patients reported this outcome with a fixed-effects mode, which indicated significant improvement in effectiveness rate in the TCM formula group (RR: 1.22, 95% CI: 1.18 to 1.26, P = 0.000; I2 = 0.0%, P = 0.863) (Fig. 4A). While sensitivity analysis demonstrated reliability (Fig. 4B), the Funnel plot (Fig. 4C), Begg’s test (Fig. 4D), and Egger’s test (Fig. 4E) revealed potential publication bias of these studies, with a P-value equal to 0.000 in Egger’s test. The other sources of bias for all studies were unclear.

Fig. 4.

Fig. 4

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Meta-analysis of the effectiveness rate in AP patients after treating with TCM formulas for activating blood flow. Forest plot following meta-analysis of the effectiveness after using the formulas for activating blood flow (A). Sensitive analysis results of the formulas for activating blood flow in effectiveness (B). Funnel plot for publication bias (C). Begg’s funnel plot analysis for potential publication bias (D). Egger’s funnel plot analysis for revealing potential publication bias (E).

3.1.4. Secondary outcomes: Disease severity

Mortality, complications, and total hospital stays were analyzed in Fig. S1. A fixed-effects model was selected for meta-analysis involving five articles (P = 0.850, I2 = 0.0), which indicated that the TCM formula for activating blood flow treatment could effectively reduce the mortality rate (RR: 0.36, 95% CI: 0.16 to 0.79, P = 0.011). Eight RCTs containing 622 patients used complications as their outcome with a fixed-effects model (P = 0.491, I2 = 0.0). TCM formulas for activating blood flow reduced patient complications (RR: 0.34, 95% CI: 0.24 to 0.50, P = 0.000). Also, the critically reduced total hospital stays were related to the formulas for activating blood flow (SMD =  − 1.22, 95% CI: −1.63 to − 0.82, P = 0.000), with no potential source of the high heterogeneity detected (P = 0.000, I2 = 81.0%).

The meta-analysis results of serum amylase recovery time were given in Fig. S2. Thirteen articles reported information on serum amylase recovery time, which proved the reliability and effectiveness of the TCM group using a random-effects model (SMD =  −2.05, 95% CI: −2.76 to −1.35, P = 0.000; P = 0.000, I2 = 95.7%). Meanwhile, the potential publication bias of these studies was shown in the Funnel plot and Egger’s test, with a P-value equal to 0.002 in Egger’s test.

As shown in Fig. S3, 787 patients from eleven RCTs using a fixed-effects model (SMD =  −1.08, 95% CI: −1.23 to −0.93, P = 0.000; I2 = 16.0%, P = 0.291) demonstrated that the formula for activating blood flow had great advantages over shortening the time until the disappearance of abdominal pain, compared with the pure conventional western medical treatment. There was no evidence of publication bias for it (Egger’s test: P = 0.690).

3.1.5. Secondary outcomes: Microcirculation

Meta-analysis results for microcirculation indicators were shown in Fig. 5. Three included studies involving 192 patients revealed that the formula for activating blood flow was more effective in reducing D-D levels (SMD =  −1.05, 95% CI: −2.01 to −0.08, P = 0.034) (Fig. 5A). A random-effects model was used since high heterogeneity was observed from Wang’s study (Wang 2013) (P = 0.000, I2 = 89.5%). Besides, TCM formula intervention for activating blood flow had potential benefits for reducing PAF levels in another 3 studies with no source of significant heterogeneity (n = 236; SMD =  −2.08, 95% CI: −3.88 to −0.27, P = 0.024; P = 0.000, I2 = 96.6%) (Fig. 5B). As shown in Fig. 5C, 124 AP patients from 2 articles showed the benefits of a decrease in FIB level using the formulas for activating blood flow with a fixed-effects model (SMD =  −1.07, 95% CI: −1.44 to −0.69, P = 0.000; P = 0.701, I2 = 0.0%). Another two studies showed the formulas for activating blood flow reduced the level of ET (SMD =  −2.23, 95% CI: −2.64 to −1.83, P = 0.000; I2 = 8.2%, P = 0.297) (Fig. 5D). Three RCTs evaluating TXA2 indicated the benefits of applying the herbs for activating blood flow (n = 248; SMD =  −1.55, 95% CI: −2.45 to −0.66, P = 0.001) (Fig. 5E). Therefore, a random-effects model was used since high heterogeneity was observed from Xiao’s study (Xiao, Xu, Zhou, & Tan, 2022) with different study durations (I2 = 89.0%, P = 0.000). Two studies showed that the TCM group upgraded the level of NO with little significant heterogeneity (n = 172; SMD = 0.77, 95% CI: 0.46 to 1.08, P = 0.000; I2 = 0.0%, P = 0.942) (Fig. 5F). However, the association between PGI2 and the formula for activating blood flow treatment had little significance (n = 248), with obvious heterogeneity among these studies (SMD =  −0.57, 95% CI: −3.40 to 2.26, P = 0.692; I2 = 98.7%, P = 0.000) (Fig. 5G).

Fig. 5.

Fig. 5

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Forest plot following meta-analysis of the changes for AP patients in microcirculation indicators including D-D, D-dimer (A), PAF, platelet-activating factor (B), FIB, fibrinogen (C), ET, endothelin (D), TXA2, thromboxane A2, NO (E), nitric oxide (F), and PGI2, prostaglandin I2 (G) after treating with TCM formulas for activating blood flow.

3.1.6. Secondary outcomes: Inflammation

As shown in Fig. S4, the combined results of 21 RCTs comprising 1 635 patients (825 in the TCM intervention group and 810 in the control group) demonstrated that the formulas for activating blood flow significantly reduced the TNF-α level when conducting a random-effects model (SMD =  −1.77, 95% CI: −2.06 to −1.48, P = 0.000; P = 0.000, I2 = 84.2%). No source of heterogeneity was found. Sensitivity analysis proved the reliability of our results. However, the potential publication bias of these studies was shown in the Funnel plot and Egger’s test (P = 0.001). The formulas for activating blood flow surely showed great advantages in IL-6 over the comparison group for 18 studies with great reliability according to the sensitivity analysis (n = 1 363; SMD =  −1.93, 95% CI: −2.47 to −1.39, P = 0.000) (Fig. 6). With significant heterogeneity of unknown sources among these RCTs (P = 0.000, I2 = 94.0%), a random-effects model was adopted. However, there might be potential publication bias in the studies shown in the Funnel plot and Egger’s test (P = 0.038). Besides, TCM herbs for activating blood flow obviously decreased other inflammatory indicators, including IL-1β (n = 404; SMD =  −0.97, 95% CI: −1.80 to −0.14, P = 0.022; P = 0.000, I2 = 93.1%), CRP (n = 344; SMD =  −1.36, 95% CI: −2.24 to −0.48, P = 0.002; P = 0.000, I2 = 92.1%), and HMGB1 (n = 185; SMD =  −2.20, 95% CI: −2.83 to −1.56, P = 0.000; P = 0.084, I2 = 66.4%) (Fig. S5).

Fig. 6.

Fig. 6

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Meta-analysis of IL-6 in AP patients with TCM formulas for activating blood flow. Forest plot following meta-analysis of IL-6 after using TCM formulas for activating blood flow (A). Sensitive analysis results of TCM formulas for activating blood flow in IL-6 (B). Funnel plot for publication bias (C). Begg’s funnel plot analysis for testing potential publication bias (D). Egger’s funnel plot analysis for revealing potential publication bias (E).

3.1.7. Meta regression and subgroup analyses

Serum amylase recovery time, TNF-α, and IL-6 satisfied the conditions to make meta-regression for the above outcomes reported (Table S2). For serum amylase recovery time in a meta-regression analysis, the type of AP population, sample size, administration route, and study duration had a significant correlation with the heterogeneity. However, it was inconsistent with the results of subgroup analysis, which might be associated with inconsistent or unclear diagnostic references and insufficient detailed information for the type of AP patients. Evidence of heterogeneity was also observed according to the subgroups (Table S3). There was no significant difference before and after subgroup analysis, except for D-D and TXA2.

3.1.8. Quality assessment of evidence

We showed the summary of findings for the included studies and the GRADE recommendations in Table 2. Totally, the certainty of the evidence for mortality rate, complications, and the time until the disappearance of abdominal pain was moderate; for APACHE II Score, effectiveness rate, total hospital stays, serum amylase recovery time, D-D, FIB, ET, TXA2, NO, TNF-α, IL-6, and IL-1β was low, while the certainty for PAF, PGI2, CRP, and HMGB1 was very low.

Table 2.

Summary of findings for included studies.

Outcomes Anticipated absolute effects* (95% CI)
 Relative effect (95% CI) No. of participants (studies) Certainty of the evidence (GRADE)
Risk with CWM Risk with TCM formulas for activating blood flow plus CWM
APACHE II Score − SMD 1.36
(2.01 to 0.71 lower)		 − 659 (9 RCTs) ⊕⊕○○ low1,2
Effectiveness rate 166
per 1 000		 169 more per 1 000
(138 to 199)		 RR 1.22
(1.18 to 1.26)		 2 887 (38 RCTs) ⊕⊕○○ low1,4
Mortality rate 71
per 1 000		 63 fewer per 1 000
(18 to 85)		 RR 0.38
(0.17 to 0.82)		 407 (5 RCTs) ⊕⊕⊕○ moderate1
Complications 173
per 1 000		 198 fewer per 1 000
(150 to 228)		 RR 0.34
(0.24 to 0.50)		 622 (8 RCTs) ⊕⊕⊕○ moderate1
Total hospital stays − SMD 1.22 lower
(1.63 to 0.82 lower)		 − 617 (8 RCTs) ⊕○○○ low1,2
Serum amylase recovery time − SMD 2.05 lower
(2.76 to 1.35 lower)		 − 1 033 (13 RCTs) ⊕⊕○○ low1,2
Time until the disappearance of abdominal pain − SMD 1.08 lower
(1.23 to 0.93 lower)		 − 787 (11RCTs) ⊕⊕⊕○ moderate1
Microcirculation indicator D-D − SMD 1.05 lower
(2.01 to 0.08 lower)		 − 192 (3 RCTs) ⊕⊕○○ low1,3
PAF − SMD 2.08 lower
(3.88 to 0.27 lower)		 − 236 (3 RCTs) ⊕○○○ very low1,2,3
FIB − SMD 1.07 lower
(1.44 to 0.69 lower)		 − 124 (2 RCTs) ⊕⊕○○ low1,4
ET − SMD 2.23 lower
(2.64 to 1.83 lower)		 − 151 (2 RCTs) ⊕⊕○○ low1,3
TXA2 − SMD 1.55 lower
(2.45 to 0.66 lower)		 − 248 (3 RCTs) ⊕⊕○○ low1,3,4
NO − SMD 0.77 higher
(0.46 to 1.08 higher)		 − 172 (2 RCTs) ⊕⊕○○ low1,3
PGI2 − SMD 0.57 lower
(3.40 lower to 2.26 higher)		 − 248 (3 RCTs) ⊕○○○ very low1,2,3
Inflammation indicator TNF-α − SMD 1.77 lower
(2.06 to 1.48 lower)		 − 1 635 (21 RCTs) ⊕⊕○○ low1,2
IL-6 − SMD 1.93 lower
(2.47 to 1.39 lower)		 − 1 283 (17 RCTs) ⊕⊕○○ low1,2
IL-1β − SMD 0.97 lower
(1.80 to 0.14 lower)		 − 404 (5 RCTs) ⊕⊕○○ low1,2
CRP − SMD 1.36 lower
(2.24 to 0.48 lower)		 − 257 (4 RCTs) ⊕○○○ very low1,2,3
HMGB1 − SMD 2.20 lower
(2.83 to 1.56 lower)		 − 185 (2 RCTs) ⊕○○○ very low1,2,3
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Note: *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI).

TCM: Traditional Chinese Medicine; CWM: conventional western medical treatments; AP: Acute pancreatitis; CI: confidence interval; RR: risk ratio; SMD: standardised mean difference.

GRADE Working Group grades of evidence. High quality: Further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: We are very uncertain about the estimate. 1Due to Risk of bias; 2Due to Inconsistency; 3Due to Inprecision; 4Due to Publication bias.

3.2. Network pharmacology analysis

We identified a total of 70 Chinese herbal medicines from the 51 RCTs included in the above meta-analysis. For frequency analysis, the highest was Rhei Radix et Rhizoma (Dahuang in Chinese, DH), which occurred 47 times with a frequency rate of 8.01%. We considered herbs whose frequency rates were greater than or equal to 1% as high-frequency herbs, a total of 26 Chinese herbal medicines. Detailed information, including the frequency (Fig. 7A) and Chinese pinyin names as well as Latin names (Table S4), about the 70 used herbs was given. We applied SPSS Modeler 18.0 software and its Apriori Algorithm to further analyze association rules about drug combinations for the high-frequency herbs, which were shown in the network diagram (Fig. 7B). Furthermore, the analysis generated 49 pairs of the two Chinese herbal medicines, with the support degrees of Rhei Radix et Rhizoma (DH)—Aurantii Fructus Immaturus (Zhishi in Chinese, ZS) and Rhei Radix et Rhizoma (DH)—Paeoniae Radix Rubra (Chishao in Chinese, CS) being the greatest (92.16%). The top 30 with support degrees of total 288 association rules about drug combinations were shown in Table S5.

Fig. 7.

Fig. 7

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Results of the medication rule analysis for the included 51 studies. (A) Bar chart showing the frequency and percentage of the 70 Chinese herbal medicines belonging to the included studies. (B) The association rule diagram about drug combinations for the 26 high-frequency Chinese herbal medicines. (C) Network contribution map showing potential six core Chinese herbal medicines in TCM formulas for activating blood flow of the 51 studies.

Combined frequency and association rules aside, it was obviously found that the six core Chinese herbal medicines were significantly frequent, whether they were single-use or combinations. Through the association network, Rhei Radix et Rhizoma (DH), Aurantii Fructus Immaturus (ZS), Paeoniae Radix Rubra (CS), Bupleuri Radix (Chaihu in Chinese, CH), Salviae Miltiorrhizae Radix et Rhizoma (Danshen in Chinese, DS), and Corydalis Rhizoma (Yanhusuo in Chinese, YHS) were identified as the potential core Chinese herbal medicines for TCM formulas for activating blood flow in AP treatments (Fig. 7C).

3.2.1. Core targets for AP

We finally obtained 209 bioactive ingredients from 457 chemical ingredients and their relevant 534 targets. The “herb-ingredient-target relationship network” was constructed for core Chinese herbal medicines (Fig. 8A, Table S6). Among the 1 125 targets of AP, 166 shared targets were identified by determining the intersections (Fig. 8B). A protein–protein interaction (PPI) network was constructed for the prediction of herbal targets. The PPI network included 530 nodes and 10 537 edges. Combined with the analyses above and the literature reports (Wei et al., 2021), we identified the top 26 hub targets, including TP53, STAT3, AKT1, TNF, JUN, ACTB, IL6, HSP90AA1, MAPK3, VEGFA, EGFR, CASP3, MYC, IL1B, RELA, MAPK1, INS, ALB, MMP9, ESR1, PIK3R1, CCND1, EGF, MAPK8, TLR4, and HIF1A, which may play a pivotal role for AP treatment (Fig. 8C).

Fig. 8.

Fig. 8

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Network pharmacology prediction of the six core Chinese herbal medicines for AP. The “herb-component-target” network showing targets of bioactive ingredients which belong to the six Chinese herbal medicines (A). Proportional Venn diagram showing the intersection of targets for AP and the six core Chinese herbal medicines (B). The result of PPI analysis for potential targets of the six herbs and AP (C). Highly relevant results of GO analysis for treating AP items (D).Results of the KEGG enrichment analysis revealing five signaling pathways highly relevant to the microcirculation of the six Chinese herbal medicines (E).

3.2.2. GO and KEGG enrichment

To further detect the potential mechanism of the six core Chinese herbal medicines in AP, we performed GO and KEGG analysis. In GO analysis, the biological processes (BP) with a total of 2 113 items, the molecular function (MF) with 178 items, and the cellular component (CC) with 110 entries were shown in Fig. 8D for the top 10 highly relevant items. The KEGG pathways related to the targets (P < 0.05) involved 204 entries. And the relevant analysis results with microcirculation mainly included the lipid and atherosclerosis, the PI3K-Akt signaling pathway, the AGE-RAGE signaling pathway in diabetic complications, the HIF-1 signaling pathway, arachidonic acid metabolism, and other pathways (Fig. 8E).

4. Discussion

Our study proposed the clinical significance of microcirculation, potential Chinese herbal medicines, and target-related therapy in AP. Firstly, by evaluating the effects of TCM formulas for activating blood flow on APACHE II score, effectiveness, and secondary outcomes of disease severity, we concluded that oral administration of TCM formulas for activating blood flow shows significant advantages in AP over the control group with routine western medicine treatments. Next, by evaluating the parameters of microcirculation and inflammation, we confirmed the effect of TCM formulas for activating blood flow on microcirculatory disturbance and inflammation in AP patients. Finally, we analyzed the drug targets and bioactive components of the included TCM formulas for activating blood flow.

4.1. Microcirculatory dysfunction accelerates the development of AP

It has been reported that 54.8% of AP patients have elevated levels of fibrinogen (Ahmed et al., 2018). Early pathological events of AP, like trypsinogen activation, followed by the release of inflammation-microcirculation mediators, could subsequently mediate vascular injury, and then increase vascular permeability and abnormal coagulation (Maduzia et al., 2020). After that, changes in microcirculatory blood rheology and hemodynamics occur as the principal foundation of circulatory flow deterioration, which fuels inflammatory injury (Kotan et al., 2022, Tomkötter et al., 2016, Kotan et al., 2012, Wang et al., 2020). By this means, microcirculatory disturbance persistently exacerbates AP to SAP (Cuthbertson and Christophi, 2006, Plusczyk et al., 2003, Mitchell et al., 2003). Locally scattered thrombosis may form in mild AP, while DIC may occur in severe cases (Feldman et al., 1981, Saif, 2005, Wu, 2000, Aho and Nevalainen, 1980). The elevated pancreatic blood perfusion in mild AP, however, with the development of pancreatic infiltration and edema, microcirculation failure was induced and resulted in systemic inflammatory response (SIRS) and even DIC blowout from the pancreas to the whole body, a dangerous event commonly occurring in late SAP (Foitzik et al., 2002, Liu et al., 2019, Schmidt et al., 2002). In TCM theory, accumulated damp heat and fire toxin are the main pathologies in AP (Ma, Liang, Xu, Zhao, & Hu, 2019; Song et al., 2020), thus, qi stagnation and blood stasis are regarded as crucial pathologies and therapeutic hitting points in AP. The primary effect of TCM formulas for activating blood flow is to activate blood circulation and remove blood stasis. These component Chinese herbal medicines can directly promote blood circulation, some can activate qi flowing, and some can even be helped by catharsis.

Our results indicated that TCM formulas for activating blood flow could effectively enhance vasodilatory function by reducing vasoconstrictors, ET and TXA2, while increasing vasodilators, NO levels. ET, mainly produced by endothelial cells, damages pancreatic cells by constricting vessels, reducing pancreatic blood flow, promoting vascular permeability, and triggering calcium overloading and inflammatory responses (Inoue et al., 2003, Plusczyk et al., 1999, Eibl et al., 2000, Foitzik et al., 2001). TXA2, another important vasoconstrictor, severely stimulates leukocyte-platelet-endothelial interactions, resulting in coagulopathy and enhancing vascular damage, which is massively released during AP (Wang, Liao, Li, Liao, & Qin, 1998). Evidence showed that elevated plasma TXB2, a stable metabolite of TXA2, exacerbated thrombosis and vascular occlusion, significantly exacerbating SAP in rats (Zhang et al., 2009). PAF, the major contributor to microcirculatory disturbance, SIRS, and multi-organ failure (Uhlmann et al., 2008, Kerekes et al., 2001), activates inflammatory cells and amplifies the inflammatory response by releasing inflammatory mediators (Zhang, Wang, & Zhou, 2008). Besides, the degree of D-D elevation was correlated with the severity of AP, as it effectively enhances the coagulation system and induces DIC in parallel with multi-organ failure (Penner, 1998, Carey and Rodgers, 1998). In TCM treatment for activating blood flow, the levels of PAF and D-D were lowered, revealing a beneficial effect on AP microcirculation disturbance. Thus, the effect on microcirculation of TCM formulas for activating blood flow in AP patients partially explains their effectiveness, and the mechanisms may be rooted in the connection between vascular injury and inflammation.

4.2. Microcirculation-inflammation crosstalk: Inflammation-coagulation cascade

Inflammation-mediated coagulation dysfunction leads to hyperactivated platelets, which in turn leads to hypercoagulation, less active anticoagulants, and fibrinolytic dysfunction (Esmon, 2008). This process was regarded as the “inflammation-coagulation cascade”. Pro-inflammatory factors have been shown to mediate platelet activation, and coagulation could accelerate inflammation (Esmon, 2008, Levi et al., 1997, Danckwardt et al., 2013, Abdulla et al., 2011).

Our study found that TCM formulas for activating blood flow effectively diminish inflammatory parameters in AP patients, along with alleviating microcirculation disturbance. Elevated CRP levels promote monocyte-endothelial interactions and abnormally increase the expression of tissue factor (TF) and fibrinogen activator inhibitor-1 (PAI-1) (Cermak et al., 1993). Surprisingly, TCM herbs for activating blood flow greatly decreased CRP, which partly explains the suppression of microcirculation-inflammation crosstalk. Other inflammatory mediators that positively correlate with SAP, including TNF-α, IL-1β, IL-6, and HMGB1 (Zhang et al., 2008, Saluja et al., 2019, Gao et al., 2018), were effectively eliminated by TCM formulas for activating blood flow. Hence, the improvement effect of TCM formulas for activating blood flow on inflammation and microcirculation exhibits a positive feedback mechanism, which preserves clinical significance and transformative application value in AP therapies.

4.3. Drug target of TCM formulas for activating blood flow

TCM shows promising benefits with multiple targets in various diseases. In the context of AP, formulas such as Dachengqi decoction, Qingyi decoction, and Chaiqin Chengqi decoction significantly improved AP (Yi et al., 2020, Hua et al., 2013, Guo et al., 2013). Notably, these formulas share the treating principle of the purgation method, which has been widely accepted in AP therapy. Our meta-analysis first revealed that promoting blood circulation for removing blood stasis with TCM formulas for activating blood flow could effectively ameliorate AP. According to the TCM theory, especially the book Wenbing Tiaobian (Detailed Analysis of Epidemic Warm Diseases) written by Jutong Wu during the Qing Dynasty, a disease usually develops following the sequence from wei, qi, ying, and xue, an order from surface to depth, from mild to severe. At the onset of AP, it is characterized by heat in the qi that stays in the qifen. During its progression, heat toxicity and stasis go further and deeper into yingfen and xuefen, resulting in blood changes (Bian, Liao, Wen, Tian, & Lei, 2021). Toxicity and stasis can be viewed as inflammation and microcirculation, which are mutually reinforcing.

Using medication rule analysis, we identified six core Chinese herbal medicines from the included TCM formulas for activating blood flow. Among the core herbs, Rhei Radix et Rhizoma (DH) clears heat as well as detoxifies and resolves blood stasis. Paeoniae Radix Rubra (CS), Salviae Miltiorrhizae Radix et Rhizoma (DS), and Corydalis Rhizoma (YHS) emerge beneficial effects on blood circulation and pain relief by reducing blood stasis. Aurantii Fructus Immaturus (ZS) and Bupleuri Radix (CH) target qi to ease stasis. All the herbs demonstrated the possibility of improving microcirculation to ameliorate AP according to the TCM theory.

Additionally, the network pharmacology analysis was conducted to better understand the mechanisms of the core TCM herbs for activating blood flow. Combined with 26 hub targets and five essential pathways of the results, these TCM formulas and their related core Chinese herbal medicines may show significant effects on microcirculation-inflammation crosstalk. Emodin protects the vascular endothelium and inhibits vascular permeability. Rhein, also the component of Rhei Radix et Rhizoma (DH), has the ability to downregulate proteins associated with the JAK2/STAT3 signaling pathway (Yang et al., 2022). In addition, the formula Chaihuang Qingyi Huoxue granule included in our study could suppress p-STAT3 and JNK expressions in AP (Tang et al., 2022, Jiang et al., 2019). Naringin, a common component of Aurantii Fructus Immaturus (ZS) and Bupleuri Radix (CH), exhibits anti-inflammatory and antioxidant properties as well as the ability to ameliorate microcirculatory disturbance (Wang et al., 2021). Quercetin, a component of Bupleuri Radix (CH), can lower the inflammation and apoptosis factors (IL-1β, IL-6, TNF-α, MAPK3, and TP53) while also protecting against AP by blocking the p38/MAPK signaling pathway (Zhan et al., 2021, Sheng et al., 2021). Meanwhile, Qingxia Huayu decoction, the most frequently used formula in our included RCTs, demonstrated efficacy in targeting MAPK-related variables and ATF-2 (Kong, Wang, Zhu, Li, & Zhou, 2019). Baicalin, the main bioactive component of Paeoniae Radix Rubra (CS) and Salviae Miltiorrhizae Radix et Rhizoma (DS), can boost NO bioactivity, dilate blood vessels, improve microcirculation, scavenge oxygen free radicals (OFRs), and inhibit the expression of adhesion molecules such as intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) (Wen, Li, & Fu, 2008). Moreover, baicalin was found to ameliorate endothelial dysfunction and platelet activation by inhibiting the AKT-related pathway (Wang et al., 2023). Emodin exactly reduced the expression VEGF proteins in the acute lung injury cell model (Li et al., 2020). Notably, lipid and atherosclerosis pathways associated with lipid metabolism have caught our attention. Elevated evidence has shown that excessive triglyceride hydrolysis releases large amounts of free fatty acids that block capillaries and lead to microthrombosis, further damaging vascular endothelial cells and pancreatic acinar cells, finally exacerbating microcirculatory disturbance and AP (Adiamah, Psaltis, Crook, & Lobo, 2018). Additionally, increased secretion of phospholipase A2 (PLA2) promotes the production of arachidonic acid, which produces large amounts of TXA2 and PGI2 in response to cyclooxygenase, prostaglandin synthase, and thromboxane synthase (Zhang, Wang, & Zhou, 2008). This evidence suggests an important relationship between microcirculation and lipid metabolism, which paves the way for further mechanism research and drug discovery in AP.

5. Limitations and prospects

Firstly, our study only searched for electronic literature, which may not have included unpublished or gray literature. Secondly, high heterogeneity, potential publication bias owing to their low quality, various clinical settings, diverse medication criteria, and incomplete randomization methods of pooled studies might limit the process of meta-analysis. Authoritative and harmonized international standards are urgently needed in the future. Thirdly, the studies with an uneven sample size were all conducted in China, which could limit the variety of populations and affect the suitability of Chinese herbal medicines for foreigners. Therefore, high-quality, multi-center, and large-scale trials should be constructed in the future, aiming to broaden populations and countries. In addition, it is also imperative to further explore and validate the results of the network pharmacology, which includes.

6. Conclusion

With a large number of RCTs, this meta-analysis showed TCM formulas for activating blood flow ameliorated AP efficiently via improving microcirculation. Rhei Radix et Rhizoma, Paeoniae Radix Rubra, Salviae Miltiorrhizae Radix et Rhizoma, Corydalis Rhizoma, Aurantii Fructus Immaturus, and Bupleuri Radix are core Chinese herbal medicines in the series of TCM formulas for activating blood flow.

CRediT authorship contribution statement

Ji Gao: Data curation, Validation, Formal analysis, Visualization, Writing – original draft, Writing – review & editing. Chenxia Han: Data curation, Formal analysis, Funding acquisition, Writing – original draft, Writing – review & editing. Ning Dai: Data curation, Formal analysis, Methodology, Writing – review & editing. Wen Wang: Methodology, Writing – review & editing. Tao Jin: Writing – review & editing. Dan Du: Conceptualization, Project administration, Funding acquisition, Writing – review & editing. Qing Xia: Supervision, Project administration, Funding acquisition, Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The study was supported by National Natural Science Foundation of China (No. 82274321 to Q. X., No. 82374256 to D. D., No. 82104598 to C. H.) and the Sichuan Provincial Natural Science Foundation (No. 2022NSFSC0641 to Q. X.).

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.chmed.2024.12.002.

Contributor Information

Dan Du, Email: dudan1520@163.com.

Qing Xia, Email: Xiaqing@medmail.com.cn.

Appendix A. Supplementary material

The following are the Supplementary data to this article:

Supplementary Data 1
mmc1.docx (829KB, docx)

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