Effectiveness and safety of Tongxinluo capsule for diabetic kidney disease: A systematic review and meta-analysis

Abstract

BACKGROUND

Diabetic kidney disease (DKD), a common microvascular complication of diabetes mellitus, is the primary cause of end-stage renal disease. Tongxinluo capsule (TXLC), a traditional Chinese medicinal compound, is widely utilized in China for treating DKD.

AIM

To analyze the effectiveness and safety of TXLC for treating DKD.

METHODS

Eight electronic literature databases were retrieved to obtain randomized controlled trials (RCTs) of TXLC for DKD. RevMan 5.3 software was used for data analysis. Evidence quality was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation System. Publication bias was detected using Stata 16.0 software.

RESULTS

Twenty-two RCTs involving 1941 patients with DKD were identified. Compared with conventional treatment, TXLC combination therapy significantly improved the primary outcomes, including 24-hour urine proteinuria, urine microalbumin, and urinary albumin excretion rate. Regarding secondary outcomes, TXLC combination therapy significantly reduced serum creatinine, blood urea nitrogen, β2-microglobulin, and cystatin C levels; however, it had no significant effect on creatinine clearance rate. In terms of additional outcomes, TXLC combination therapy significantly reduced total cholesterol, triglycerides, low-density lipoprotein cholesterol, fibrinogen, plasma viscosity, whole blood low shear viscosity, whole blood high shear viscosity, and endothelin-1 levels, while increasing nitric oxide levels. However, the addition of TXLC treatment did not significantly affect fasting plasma glucose, 2-hour postprandial blood glucose, glycosylated hemoglobin, high-density lipoprotein cholesterol, or C-reactive protein levels. The safety of TXLC in DKD remains uncertain due to limited adverse event reporting.

CONCLUSION

TXLC may benefit individuals with DKD by improving various health parameters, such as urinary protein levels, renal function, blood lipids, hemorheology, and vascular endothelial function. However, TXLC did not improve all studied outcomes.

Key Words: Tongxinluo capsule; Diabetes mellitus; Chronic kidney disease; Renal protection; Chinese herbal medicines; Systematic review

Core Tip: This is the first English systematic review and meta-analysis of Tongxinluo capsules (TXLC) for diabetic kidney disease (DKD). Twenty-two eligible randomized controlled trials with 1941 individuals with DKD were identified. The meta-analysis demonstrated that TXLCs combined with conventional treatment were more effective in reducing proteinuria and improving multiple parameters, including renal function, lipid profile, hemodynamics, and vascular endothelial function, compared with conventional treatment alone.

INTRODUCTION

Diabetes mellitus (DM) is a public health problem that threatens human health. Approximately 6.7 million individuals are expected to have died from DM or its complications by 2021, representing 12.2% of all-cause deaths[1]. A recent study by the International Diabetes Federation showed that approximately 536.6 million adults worldwide had DM in 2021. The population is expected to rise to 783.2 million by 2045[1]. Diabetic kidney disease (DKD), a prevalent microvascular complication of DM, is a major contributor to chronic kidney disease (CKD) and end-stage renal disease (ESRD). Approximately 30%-40% of individuals with DM are affected by DKD[2]. The progression of DKD to ESRD is 14 times faster than that of other kidney diseases once it enters a phase of massive proteinuria[3]. As the prevalence of DM has increased sharply, the proportion of ESRD caused by DM has risen globally from 22.1% to 31.3%[4]. Additionally, DKD is associated with a significant increase in cardiovascular risk and all-cause mortality[5,6]. Most patients with DKD die of cardiovascular disease and infection before developing ESRD[5]. Therefore, the timely diagnosis and effective management of DKD are critical.

However, its pathogenesis of DKD is unclear. The pathological process involves multiple mechanisms. It may be associated with metabolic abnormalities, hemodynamic disorders, hyperactivation of the renin-angiotensin-aldosterone system, oxidative stress, inflammatory reactions, and genetic factors[7-9]. In terms of treatment, specific intervention targets are lacking in clinical practice. Enhanced lifestyle interventions, optimal glycemic regulation, blood pressure management, and lipid profile normalization remain the cornerstones of DKD management. Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor antagonists are classic drugs used to treat DKD[10]. Recent evidence suggests that glucagon-like peptide-1 receptor agonists, sodium-glucose cotransporter protein 2 inhibitors, and non-steroidal salicorticoid receptor antagonists significantly reduce the risk of renal composite endpoints[11-13]. Although these treatments have shown promising benefits, halting the progression of DKD remains difficult. A large proportion of patients with DKD progress to ESRD and necessitate renal replacement therapy.

Chinese herbal medicines are widely used to treat DKD in China and many other countries. Chinese herbal medicines, including Tongxinluo capsules (TXLC), have demonstrated specific benefits in alleviating clinical symptoms, particularly by reducing proteinuria and enhancing renal function, as supported by multiple trials[14-16]. The TXLC, a Chinese patent medicine, consists of Panax ginseng C. A. Mey (Ginseng Radix Et Rhizoma), Hirudo nipponica Whitman (Hirudo), Buthus martensii Karsch (Scorpio), Paeonia veitchii Lync. (Paeoniae Radix Rubra), Cryptotympana pustulata Fabricius (Cicadae Periostracum), Eupolyphaga sinensis Walker (Eupolyphaga steleophaga), Scolopendra subspinipes mutilans L. Koch (Scolopendra), Santalum album L. (Santali Albi Lignum), Dalbergia odorifera T. Chen (Dalbergiae Odoriferae Lignum), Boswellia carterii Birdw. (Olibanum), Ziziphus jujuba Mill. var. spinosa (Bunge) Hu ex H. F. Chou (Ziziphi Spinosae Semen), and Borneolum Syntheticum. TXLC improves renal function and structure in DM by reducing the body's microinflammatory state, combating oxidative stress, and inhibiting epithelial-mesenchymal transition (EMT)[17-19]. Several preclinical studies have demonstrated the nephroprotective effects of the TXLC components. Ginsenosides, Rg1, Rg3, and 20(R)-ginsenoside Rg3, are important active ingredients of Panax ginseng C. A. Mey (Ginseng Radix Et Rhizoma). Han et al[20] found that the ginsenoside Rg1 attenuates renal lipid accumulation and glomerular fibrosis in type 2 DM mice by inhibiting the CD36/TRPC6/NFAT2 signaling pathway. Wang et al[21] observed that ginsenoside Rg1 ameliorates renal function in a rat model of diabetic nephropathy (DN) by targeting the mTOR/NF-κB/NLRP3 pathway to inhibit podocyte pyroptosis. Ginsenoside Rg3 exhibited effects that induces proliferation and inhibits apoptosis in high glucose-induced mouse mesangial cells. The mechanism was related to the downregulation of miR-216a-5p and stimulation of the MAPK signaling pathway[22]. In a mouse model induced by a high-fat diet and streptozotocin, 20(R)-ginsenoside Rg3 alleviated DN by enhancing antioxidant activity and reducing renal inflammation[23]. Hirudin is a peptide that was isolated from the salivary glands of Hirudo nipponica Whitman (Hirudo). Hirudin exerts significant protective effects against DM-induced renal injury. The mechanism involves suppression of glomerular endothelial cell migration, reduction of pyroptosis, inhibition of abnormal angiogenesis, and attenuation of renal fibrosis[24,25]. Paeoniflorin is an index ingredient of Tongxinluo supermicro powder[26]. It exerts renoprotective properties in DN models through suppressing macrophage infiltration and activation[27], restoring podocyte autophagy, inhibiting apoptosis[28], modulating podocyte necroptosis[29], and promoting antioxidant status[30].

Recently, TXLC has been extensively investigated as a potential treatment for DKD[31-34]. However, systematic evaluations of the quality, effectiveness, as well as safety of these trials are lacking. Therefore, by summarizing the available evidence regarding the application of TXLC in DKD treatment, this study provides further support for its wider clinical application.

MATERIALS AND METHODS

Protocol registration

This study was performed and reported adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline[35]. The systematic review protocol was registered prospectively with the International Prospective Register of Systematic Reviews (PROSPERO). The registration number is CRD42024538829.

Search strategy

Two researchers independently conducted the literature searches to enhance the comprehensiveness and accuracy of the studies. The Chinese language databases searched included the CNKI, Wanfang Data, VIP, and the CBM. The English language databases searched included PubMed, EMBASE, Cochrane Library, and Web of Science. Randomized controlled trials (RCTs) of TXLC for DKD treatment published from the inception of the databases to March 24, 2024, were identified. The literature search was performed by employing a combination of subject terms and free words, specifically tailored to the indexing structure of each database. The search strategy included the following terms: “diabetic nephropathies”, “diabetic nephropathy”, “diabetic kidney disease”, and “Tong Xin Luo” “Tongxinluo”, and “Tongxinluo capsule”. Furthermore, we screened the bibliographies of all selected studies for additional access to relevant literature. The detailed information of search strategies is presented in Supplementary Table 1.

Inclusion criteria

(1) Study type: RCTs; (2) Participants: All the enrolled patients met the diagnostic criteria for DKD[3,36-38]. The study did not restrict factors such as participants' age, gender, course of disease, type of DM, stage of DKD, region, etc.; (3) Interventions and comparisons: The control group received conventional drugs (e.g., hypoglycemic, antihypertensive, antiplatelet, and hypolipidemic drugs), placebo, or dietary exercise control therapy only. The experimental group received TXLC treatment alongside the control group's standard regimen. No limitations were imposed on the dosage or treatment duration of TXLC; and (4) Outcomes: The primary outcomes were 24-hour urine proteinuria (24hUP), urinary albumin excretion rate (UAER), and urine microalbumin (UALB). The secondary outcomes were serum creatinine (Scr), blood urea nitrogen (BUN), β2-microglobulin (β2-MG), cystatin C (CysC), and creatinine clearance rate (Ccr). Additional outcomes included fasting plasma glucose (FPG), 2-h postprandial blood glucose (2hPG), glycosylated hemoglobin (HbA1C), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fibrinogen (FIB), plasma viscosity (PV), whole blood low shear viscosity (WBLSV), whole blood high shear viscosity (WBHSV), C-reactive protein (CRP), nitric oxide (NO), endothelin-1 (ET-1), and adverse events.

Exclusion criteria

(1) Studies that did not report these outcomes; (2) Studies with insufficient or inaccessible data for extraction were not included; (3) For duplicate published studies, those with the earliest publication date were retained; (4) Studies with incomplete or erroneous data for which contact with the original authors failed to provide responses; (5) Studies in which Chinese herbal medicine other than TXLC was used in the experimental group; and (6) Conference abstracts, animal experiments, case reports, and systematic reviews.

Study selection and data extraction

The literature screening, data extraction, and cross-verification processes were conducted independently by two reviewers. When discrepancies arose, a third evaluator was engaged to aid in the final decision-making process. The literature was first screened using Note Express V 3.3.0.7276 Literature management software. A preliminary screening of titles and abstracts was conducted to discard studies that did not meet the eligibility criteria. For the remaining studies, full-text articles were accessed and comprehensively examined to decide whether they met the criteria for final inclusion. An Excel spreadsheet was used to extract the following information: (1) Basic information about the selected studies, including the first author, publication year, and language of publication; (2) Basic characteristics of the participants, such as sample size, ratio of men to women, and average age; (3) Interventions, such as specific medications, dosage, duration of treatment, and route of administration; (4) Outcome indicators and incidence of adverse reactions; and (5) Entries for the risk of bias assessment. For outcomes measured repeatedly over time, the time point with the highest observed efficacy will be chosen for data analysis.

Quality assessment

Two independent reviewers conducted the quality assessment of the selected studies, employing the Cochrane risk-of-bias tool. When discrepancies arose, a third evaluator was engaged to aid in the final decision-making process. The assessment encompassed several methodological domains, including random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other biases (for example, the study has potential bias associated with the particular study design, inconsistency between the baseline conditions of the experimental and control groups, and suspicion or uncertainty of falsification). The full text was read, and each entry was classified according to its risk level: Low, high, or unclear.

Statistical analysis

RevMan 5.3 was used for meta-analysis, while Stata 16.0 was utilized for publication bias assessment. Relative risk was utilized to express the effect statistics for dichotomous variables. The mean difference (MD) was utilized to express the effect statistic when the units of continuous variables were the same, and the standardized mean difference (SMD) was used when the units were different. Q and I² tests were utilized for heterogeneity testing. A fixed-effects model was utilized when heterogeneity was low (I² < 50%), whereas a random-effects model was adopted for analyses with significant heterogeneity. An I² > 75% indicated severe heterogeneity and further subgroup analyses were required to investigate factors contributing to the heterogeneity. This study aimed to carry out subgroup analyses for sample size, duration of intervention, etc. A leave-one-out approach was employed in the sensitivity analysis to evaluate the robustness of the meta-analysis results. For outcome indicators with no fewer than ten articles in the included literature, publication bias was assessed using Egger's tests. Statistical significance was defined as P < 0.05.

Quality of evidence

The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology was applied to evaluate the quality of evidence synthesized in the meta-analyses. The evaluation consisted of five items: Study limitations, inconsistency, indirectness, imprecision, and publication bias. The evidence was graded into four levels of certainty: High, medium, low, and very low.

RESULTS

Study selection

Eight electronic databases were searched, and 345 studies were retrieved. After the elimination of duplicates, 119 studies were included for further analysis. The titles and abstracts were reviewed, and 79 ineligible articles were excluded. Two of the remaining 40 studies were unavailable in the full text. Therefore, only 38 studies were included for full-text screening. After screening the full articles, 16 were excluded due to the following reasons: Review (n = 1), lack of relevant outcomes (n = 5), conference abstracts (n = 3), duplicate publications (n = 2), incomplete data (n = 3), and incorrect data (n = 2). Ultimately, 22 studies were included in the quantitative analysis (Figure 1).

Figure 1  Flowchart of the retrieval and screening process.

Basic characteristics of the included studies

The 22 RCTs[32-34,39-57] included 1941 patients: 1016 in the experimental group and 925 in the control group. One study[45] was a multi-arm clinical trial with four different interventions: Chlorosartan, perindopril, chlorosartan combined with TXLC, and perindopril combined with TXLC. The remaining studies[32-34,39-44,46-57] were two-arm clinical trials. All the study sites were located in mainland China. The publication years were from 2003 to 2022, and the publication languages were all Chinese. The minimum and maximum sample sizes were 45 and 300, respectively. Fourteen trials[33,34,40,43,44,46,47,49-53,55,57] included individuals with stage III DKD. Two trials[41,56] included individuals with stage IV DKD. One trial[42] included individuals with stage III-IV DKD. Five studies[32,39,45,48,54] only mentioned the inclusion of patients with DKD and did not specify the disease stage. Treatment duration ranged from 1 to 6 months, with 16 trials[32,33,40-42,44,45,47,48,50,52-57] limited to 12 weeks or less and six trials[34,39,43,46,49,51] lasting longer than 12 weeks. The basic characteristics of the studies included in this review are summarized in Table 1. Details of the TXLC used in the included studies are shown in Supplementary Table 2.

Table 1 Basic characteristics of the included studies.

Ref.	Sample size	Age (year)	Male/female	Intervention (s)	Comparators	Treatment duration	Stage of DKD	Outcomes
Shen and Sun[32]	E: 45; C: 45	E: 49.41 ± 3.31; C: 49.34 ± 3.23	E: 29/16; C: 28/17	TXLC 4 capsules tid + CT	CT (hypoglycemic drugs; irbesartan)	12 weeks	/	1, 4, 5, 8, 16, 17, 18, 19
Wei et al[33]	E: 69; C: 69	E: 54.8 ± 7.4; C: 55.3 ± 7.2	E: 37/32; C: 35/34	TXLC 3 capsules tid + CT	CT (hypoglycemic drugs; antihypertensive drugs other than ACEI/ARB; irbesartan)	12 weeks	III	7, 21, 22, 23
Yang[34]	E: 38; C: 38	E: 58.27 ± 7.16; C: 58.69 ± 8.03	E: 17/21; C: 18/20	TXLC 3 capsules tid + CT	CT (hypoglycemic drugs; irbesartan)	16 weeks	III	1, 4, 5, 8, 9, 16, 17, 18, 19, 22
Chen et al[39]	E: 47; C: 47	E: 54; C: 50	E: 25/22; C: 24/23	TXLC 4 capsules tid + CT	CT (hypoglycemic drugs; enalapril)	4 months	/	1, 4, 5, 9, 10, 12, 13, 14, 15
Sun and Huang[40]	E: 29; C: 25	E: 55.7 ± 6.9; C: 54.3 ± 5.6	E: 16/13; C: 12/13	TXLC 2 capsules tid + CT	CT (hypoglycemic drugs; CCB)	2 months	III	3, 9, 10, 11
Zhao and Zhang[41]	E: 35; C: 28	E: 26-78; C: 24-76	E: 21/14; C: 17/11	TXLC 2 capsules tid + CT	CT (hypoglycemic drugs; CCB)	8 weeks	IV	3, 6, 8, 9, 22
Cao et al[42]	E: 32; C: 32	E: 34-72; C: 35-69	E: 15/17; C: 14/18	TXLC 2 capsules tid + CT	CT (hypoglycemic drugs; antihypertensive drugs other than ACEI/ARB)	8 weeks	III, IV	3, 4, 5, 11, 12, 13
Liang et al[43]	E: 27; C: 25	56 ± 13	/	TXLC 4 capsules tid + CT	CT (hypoglycemic drugs; irbesartan)	16 weeks	III	1, 3, 4, 5, 8, 16, 18, 19
Peng et al[44]	E: 23; C: 22	E: 56 ± 8.7; C: 57 ± 8.9	E: 17/6; C: 14/8	TXLC 4 capsules tid + CT	CT (hypoglycemic drugs; valsartan)	8 weeks	III	3, 4, 5, 9, 12, 17, 18, 19
Wang[45]	E: 32; C: 31	/	/	TXLC 4 capsules tid + CT	CT (hypoglycemic drugs; losartan)	12 weeks	/	1, 4, 5
Wang[45]	E: 32; C: 31	/	/	TXLC 4 capsules tid + CT	CT (hypoglycemic drugs; perindopril)	12 weeks	/	1, 4, 5
Chen and Feng[46]	E: 31; C: 30	E: 56.0 ± 8.7; C: 57.0 ± 8.9	E: 20/11; C: 17/13	TXLC 4 capsules tid + CT	CT (hypoglycemic drugs; fosinopril sodium tablets)	6 months	III	1, 2, 3, 4, 5, 8
Gu[47]	E: 38; C: 30	E: 56 ± 6; C: 59 ± 5	E: 20/18; C: 10/20	TXLC 2 capsules tid + CT	CT (hypoglycemic drugs; captopril)	3 months	III	2
Guo[48]	E: 33; C: 28	E: 26-71; C: 28-72	E: 21/12; C: 17/11	TXLC 2 capsules tid + CT	CT (insulin; enalapril)	8 weeks	/	3, 4, 5, 9
Li et al[49]	E: 35; C: 35	E: 60 ± 7; C: 59 ± 8	E: 18/17; C: 17/18	TXLC 3 capsules tid + CT	CT (hypoglycemic drugs; enalapril)	14 weeks	III	2, 4, 5, 9, 12, 13
Huang et al[50]	E: 35; C: 34	E: 52.38 ± 9.2; C: 51.4 ± 8.9	E: 27/8; C: 24/10	TXLC 4 capsules tid + CT	CT (hypoglycemic drugs; telmisartan)	10 weeks	III	3, 4, 5, 9, 12, 13, 15, 17, 18, 19, 23
Mu et al[51]	E: 30; C: 30	E: 49 ± 9; C: 50± 9	E: 18/12; C: 16/14	TXLC 3 capsules tid + CT	CT (metformin or gliclazide; valsartan)	6 months	III	3, 4, 6, 9, 10, 11, 12, 13, 14, 23
Bi et al[52]	E: 30; C: 30	E: 61 ± 5; C: 60 ± 4	E: 16/14; C: 15/15	TXLC 3 capsules tid + CT	CT (hypoglycemic drugs; ACEI/ARB)	12 weeks	III	3, 4, 7, 9, 11, 20
Li and Lv[53]	E: 45; C: 45	E: 54.4 ± 3.2; C: 55.4 ± 3.9	E: 30/15; C: 29/16	TXLC 3 capsules tid + CT	CT (hypoglycemic drugs; irbesartan)	12 weeks	III	3, 4, 5, 9, 10, 12, 13, 14, 15, 23
Yan[54]	E: 180; C: 120	E: 55.3 ± 3.5; C: 54.4 ± 3.3	E: 100/80; C: 68/52	TXLC 2 capsules tid + CT	CT (insulin; valsartan)	1 months	/	1, 3, 4, 5, 9, 11, 13, 15, 16, 17, 18, 19
Tian et al[55]	E: 50; C: 50	E: 52 ± 14.25; C: 53 ± 13.82	E: 22/28; C: 23/27	TXLC 3 capsules tid + CT	CT (hypoglycemic drugs; antiplatelet agent; irbesartan)	12 weeks	III	1, 3, 4, 5, 8, 9, 10, 21, 22, 23
Tian et al[56]	E: 50; C: 50	E: 52 ± 11.97; C: 51 ± 12.14	E: 25/25; C: 24/26	TXLC 3 capsules tid + CT	CT (insulin; antiplatelet agent; antihypertensive drugs)	12 weeks	IV	2, 3, 4, 5, 9, 10, 11, 20, 23
Zhang et al[57]	E: 50; C: 50	E: 51 ± 12.97; C: 50 ± 13.16	E: 21/29; C: 25/25	TXLC 3 capsules tid + CT	CT (insulin aspart 30 injection; ACEI/ARB/CCB; antiplatelet agent)	12 weeks	III	1, 2, 6, 7, 8, 9, 10, 11, 23

Outcomes: 1: 24-hour urine proteinuria; 2: Urine microalbumin; 3: Urinary albumin excretion rate; 4: Serum creatinine; 5: Blood urea nitrogen; 6: β2-microglobulin; 7: Cystatin C; 8: Creatinine clearance rate; 9: Fasting plasma glucose; 10: 2-hour postprandial blood glucose; 11: Glycosylated hemoglobin; 12: Total cholesterol; 13: Triglycerides; 14: Low-density lipoprotein cholesterol; 15: High-density lipoprotein cholesterol; 16: Fibrinogen; 17: Plasma viscosity; 18: Whole blood low shear viscosity; 19: Whole blood high shear viscosity; 20: C-reactive protein; 21: Nitric oxide; 22: Endothelin-1; 23: Adverse events. E: Experimental group; C: Control group; TXLC: Tongxinluo capsule; CT: Conventional therapy; ACEI: Angiotensin-converting enzyme inhibitors; ARB: Angiotensin receptor antagonists; CCB: Calcium channel blockers.

Risk bias of included studies

Of the 22 included studies, 7 studies[33,39,52,53,55-57] were grouped using the randomized numerical table method and considered low-risk. The two studies[32,46] were grouped by numerical parity and visit order, and both were considered high-risk. The remaining 13 studies[34,40-45,47-51,54] lacked sufficient description of randomization methods and the risk of bias was unclear. None of the studies reported allocation concealment; consequently, selection bias was assessed as an unclear risk. None of the studies described the blinding of participants and personnel; therefore, performance bias was rated as an unclear risk. Detection bias was categorized as low-risk because the outcome indicators in all studies were objective. The subjects dropped out in one trial[34], but the specific reasons and solutions were not reported. Therefore, attrition bias is considered a high risk factor. Two study[34,57] outcomes were incompletely reported and the reporting bias was assessed as high risk. An obvious disparity in sample sizes was observed between the experimental and control groups across the three studies[41,47,54], which may be related to inadequate randomization. Therefore, other biases were rated as high-risk (Figure 2).

Figure 2  The risk of assessment graph of the included studies.

Effect of TXLC combined with conventional therapy on urinary protein

24hUP: Eleven studies[32,34,39,43,45,46,54-57], including 1086 patients, reported 24hUP. Significant heterogeneity was detected among the studies (P < 0.00001, I² = 93%). Consequently, a meta-analysis was carried out by applying a random effects model. The data showed that the experimental group was superior to the control group in decreasing 24hUP [P < 0.00001, SMD = -1.17, 95%CI: (-1.67, -0.66)] (Figure 3A). To identify the factors influencing heterogeneity, we conducted subgroup analyses depending on intervention duration and sample size. However, none of the subgroup analyses revealed significant changes in heterogeneity (Supplementary Figure 1, Supplementary Table 3).

Figure 3 Forest plots for the meta-analysis of urinary protein. A: 24-hour urine proteinuria; B: Urine microalbumin; C: Urinary albumin excretion rate.

UALB: Two studies[49,57], including 170 patients, reported on UALB. No significant heterogeneity was detected among the studies (P = 0.27, I² = 19%). Consequently, a meta-analysis was carried out by applying a fixed effects model. The data revealed that the addition of TXLC to conventional treatment significantly reduced UALB levels in individuals with DKD [P < 0.00001, SMD = -1.03, 95%CI: (-1.35, -0.71)] (Figure 3B).

UAER: Fifteen studies[40-44,46-48,50-56], including 1247 patients, reported UAER. Significant heterogeneity was detected among the studies (P < 0.00001, I² = 94%). Consequently, a meta-analysis was carried out by applying a random effects model. The experimental group showed a more significant reduction in UAER than that in the control group [P < 0.0001, SMD = -1.19, 95%CI: (-1.73, -0.64)] (Figure 3C). The subgroup analysis was unable to explain the influencing factors of heterogeneity (Supplementary Figure 2; Supplementary Table 3).

Effect of TXLC combined with conventional therapy on renal function

Scr: Eighteen studies[32,34,39,42-46,48-56], including 1505 patients, reported Scr. A high degree of heterogeneity was observed among the studies (P < 0.00001, I² = 98%), prompting the use of a random-effects model for pooling the effect sizes. The data showed that the experimental group had a significantly lower Scr level than that of the control group [P = 0.007, MD = -13.49, 95%CI: (-23.34, -3.64)] (Figure 4A). Subgroup analysis based on intervention duration and sample size failed to reduce heterogeneity between the studies (Supplementary Figure 3, Supplementary Table 3).

Figure 4 Forest plots for the meta-analysis of renal function. A: Serum creatinine; B: Blood urea nitrogen; C: Β2-microglobulin; D: Cystatin C; E: Creatinine clearance rate.

BUN: Sixteen studies[32,34,39,42-46,48-50,53-56], involving 1385 patients, reported BUN levels. Considering the notable heterogeneity present in the studies (P < 0.00001, I² = 77%), a random-effects model was chosen for conducting the meta-analysis. The data indicated that BUN levels were notably reduced in the experimental group compared to the control group [P = 0.003, MD = -0.58, 95%CI: (-0.95, -0.20)] (Figure 4B). The subgroup analysis suggested that intervention duration may be a source of heterogeneity. The homogeneity of the study results was better at intervention durations > 12 weeks (Supplementary Figure 4 and Supplementary Table 3).

β2-MG: β2-MG was reported in three studies[41,51,57], involving 223 patients. A random-effects model was employed for data analysis due to the substantial heterogeneity observed among the studies (P < 0.00001, I² = 94%). Meta-analysis showed that β2-MG was significantly lower in the experimental group compared to the control group [P = 0.002, SMD = -2.12, 95%CI: (-3.46, -0.78)] (Figure 4C). Heterogeneity did not significantly change according to the subgroup analysis of intervention duration or sample size (Supplementary Figure 5, Supplementary Table 3).

CysC: CysC was reported in three studies[33,52,57], involving 298 patients. Considering the notable heterogeneity present in the studies (P < 0.00001, I² = 93%), a random-effects model was chosen for conducting the meta-analysis. Compared to the control group, the experimental group demonstrated significantly lower CysC levels [P = 0.03, MD = -0.31, 95%CI: (-0.58, -0.03)] (Figure 4D). Subgroup analyses based on sample size showed no heterogeneity in subgroups with sample sizes ≥ 100 (P = 0.37, I² = 0%). The detailed results are shown in Supplementary Figure 6 and Supplementary Table 3.

Ccr: Ccr was reported in seven studies[32,34,41,43,46,55,57] involving 529 patients. Random-effects models were used for combined effect sizes because of the large heterogeneity across studies (P < 0.00001, I² = 86%). The meta-analysis revealed no statistically significant difference in Ccr levels between the experimental and control groups [MD = -2.35, 95%CI: (-6.96, 2.25), P = 0.32] (Figure 4E). Subgroup analysis suggested that high or low heterogeneity may be related to intervention duration. Heterogeneity between studies decreased significantly at intervention durations > 12 weeks (P = 0.90, I² = 0%). See Supplementary Figure 7 and Supplementary Table 3 for the detailed results.

Effect of TXLC combined with conventional therapy on glucose metabolism

FPG: FPG was reported in 15 studies[34,39-41,44,48-57] involving 1329 patients. Given the low level of heterogeneity observed across the studies (P = 0.02, I² = 46%), a fixed-effects model was employed in the meta-analysis. The data suggested that combined TXLC had no significant effect on FPG compared with conventional treatment [P = 0.07, MD = 0.08, 95%CI: (-0.01, 0.16)] (Figure 5A).

Figure 5 Forest plots for the meta-analysis of glucose metabolism. A: Fasting plasma glucose; B: 2-hour postprandial blood glucose; C: Glycosylated hemoglobin.

2hPG: The 2hPG was reported in seven studies[39,40,51,53,55-57], including 598 patients. Statistical analyses were performed using a random-effects model because of the heterogeneity across the studies (P = 0.002, I² = 71%). The data suggested that combined TXLC had no significant effect on 2hPG compared with conventional treatment [P = 0.14, MD = -0.33, 95%CI: (-0.77, 0.10)] (Figure 5B).

HbA1c: HbA1C levels were reported in seven studies[40,42,51,52,54,56,57], including 738 patients. Random-effects models were used because of heterogeneity across studies (P = 0.003, I² = 69%). Meta-analysis indicated that combined TXLC had no significant effect on HbA1C compared with conventional treatment [P = 0.28, MD = -0.17, 95%CI: (-0.47, 0.14)] (Figure 5C).

Effect of TXLC combined with conventional therapy on lipid metabolism

TC: TC was reported in seven studies[39,42,44,49-51,53] involving 492 patients. Given the high level of heterogeneity observed across the studies (P < 0.0001, I² = 80%), a random-effects model was selected to combine the effect sizes. The data indicated that the experimental group was superior to the control group in reducing TC [P < 0.00001, MD = -1.03, 95%CI: (-1.35, -0.71)] (Figure 6A). No heterogeneity was found between studies with intervention durations > 12 weeks (P = 0.65, I² = 0%). See Supplementary Figure 8 and Supplementary Table 3 for the detailed results of subgroup analyses.

Figure 6 Forest plots for the meta-analysis of lipid metabolism. A: Total cholesterol; B: Triglycerides; C: Low-density lipoprotein cholesterol; D: High-density lipoprotein cholesterol.

TG: TG was reported in seven studies[39,42,49-51,53,54] involving 747 patients. Considering the notable heterogeneity present in the studies (P < 0.00001, I² = 92%), a random-effects model was chosen for conducting the meta-analysis. Compared with conventional treatment, the combination of TXLC significantly reduced the levels of TG [P < 0.00001, MD = -0.79, 95%CI: (-1.13, -0.45)] (Figure 6B). Subgroup analyses were stratified by the intervention duration and sample size. However, heterogeneity remained (Supplementary Figure 9 and Supplementary Table 3).

LDL-C: LDL-C were reported in three studies[39,51,53] involving 244 patients. A random-effects model was employed for data analysis due to the substantial heterogeneity observed among the studies (P < 0.0001, I² = 90%). Meta-analysis showed that the experimental group was more effective in lowering LDL-C than the control group [P = 0.04, MD = -0.74, 95%CI: (-1.46, -0.02)] (Figure 6C). Subgroup analyses based on intervention duration showed that heterogeneity decreased to 0% at intervention durations > 12 weeks (P = 0.51). See Supplementary Figure 10 and Supplementary Table 3 for the detailed results of subgroup analyses.

HDL-C: HDL-C was reported in four studies[39,50,53,54], including 553 patients. Considering the notable heterogeneity present in the studies (P < 0.00001, I² = 89%), a random-effects model was chosen for conducting the meta-analysis. No statistically significant difference was observed between the experimental and control groups in terms of elevated HDL-C [P = 0.08, MD = 0.19, 95%CI: (-0.02, 0.41)] (Figure 6D). Heterogeneity persisted in subgroup analyses of intervention duration and sample size (Supplementary Figure 11, Supplementary Table 3).

Effect of TXLC combined with conventional therapy on hemorheology

FIB: FIB was reported in four studies[32,34,43,54], including 505 patients. Statistical analysis was carried out using a random-effects model owing to the heterogeneity among the studies (P = 0.007, I² = 75%). The data suggested that TXLC combination therapy significantly reduced FIB levels compared with conventional therapy [P < 0.00001, MD = -1.06, 95%CI: (-1.47, -0.64)] (Figure 7A).

Figure 7 Forest plots for the meta-analysis of hemorheology. A: Fibrinogen; B: Plasma viscosity; C: Whole blood low shear viscosity; D: Whole blood high shear viscosity.

PV: PV was reported in five studies[32,34,44,50,54] involving 567 patients. Considering the high degree of heterogeneity (P < 0.00001, I² = 98%), a random-effects model was adopted. The meta-analysis indicated that TXLC combination therapy significantly reduced PV compared with conventional therapy [P = 0.04, SMD = -1.88, 95%CI: (-3.72, -0.05)] (Figure 7B). The subgroup analysis suggested intervention duration may be an influential factor of heterogeneity. No heterogeneity was observed in the subgroup with an intervention duration > 12 weeks (P = 0.57, I² = 0%). The results of subgroup analyses are provided in Supplementary Figure 12 and Supplementary Table 3.

WBLSV: WBLSV was reported in six studies[32,34,43,44,50,54], including 619 participants. Owing to the high level of heterogeneity among the studies (P < 0.00001, I² = 96%), a random-effects model was used for statistical analysis. The results demonstrated TXLC combination therapy significantly reduced WBLSV levels compared with conventional therapy [P = 0.0005, SMD = -1.81, 95%CI: (-2.83, -0.79)] (Figure 7C). Subgroup analyses showed a significant decline in heterogeneity in the subgroups with an intervention duration > 12 weeks (P = 0.30, I² = 5%). See Supplementary Figure 13 and Supplementary Table 3 for the detailed results of subgroup analyses.

WBHSV: WBHSV was reported in six studies[32,34,43,44,50,54] involving 619 participants. Random-effects models were chosen to pool effect sizes in light of the high heterogeneity (P < 0.00001, I² = 90%). The results demonstrated TXLC combination therapy significantly reduced WBHSV levels compared with conventional therapy [P < 0.00001, SMD = -2.45, 95%CI: (-3.17, -1.72)] (Figure 7D). Subgroup analyses showed no heterogeneity in subgroups with an intervention duration > 12 weeks (P = 0.55, I² = 0%). See Supplementary Figure 14 and Supplementary Table 3 for the detailed results of subgroup analyses.

Effect of TXLC combined with conventional therapy on inflammation and vascular endothelial function

CRP: CRP levels were reported in two studies[52,56] involving 160 participants. Considering the notable heterogeneity present in the studies (P < 0.00001, I² = 96%), a random-effects model was chosen for conducting the meta-analysis. The data suggested combined TXLC had no significant effect on CRP compared with conventional treatment [P = 0.26, MD = -3.34, 95%CI: (-9.13, 2.45)] (Figure 8A). As only a few studies reported data for this outcome, it was unable to search for sources of heterogeneity using subgroup analysis.

Figure 8 Forest plots for the meta-analysis of inflammation and vascular endothelial function. A: C-reactive protein; B: Nitric oxide; C: Endothelin-1.

NO: NO was reported in two studies[33,55], including 238 patients. In light of the heterogeneity (P = 0.11, I² = 61%), random effects models were utilized for statistical analysis. The data suggested the experimental group had significantly increased NO levels compared with the control group [P < 0.0001, MD = 6.89, 95%CI: (3.77, 10.01)] (Figure 8B).

ET-1: ET-1 was reported in four studies[33,34,41,55] involving 364 patients. The heterogeneity test did not reveal any heterogeneity (P = 0.43, I² = 0%). Consequently, we opted for a fixed-effects model in our meta-analysis. The results demonstrated TXLC combination therapy significantly reduced ET-1 Levels compared with conventional therapy (P < 0.00001, MD = -0.54, 95%CI: (-0.75, -0.33)] (Figure 8C).

Adverse events

Only six[33,49-51,55,56] of the included trials reported adverse events. Among the trials, two[55,56] reported that no adverse events occurred in either the experimental or control groups. Mu et al[51] reported gastrointestinal discomfort in three patients in an experimental group. Huang et al[50] reported epigastric discomfort in one patient, abdominal distension in two patients, dizziness in one patient, and dry cough in two patients in the experimental group, whereas epigastric discomfort in two patients, abdominal distension in one patient, and nausea in one patient were observed in the control group. Wei et al[33] reported vertigo in one patient, headache in one patient, and upset stomach in two patients in the experimental group, whereas two patients had headaches and one patient had diarrhea in the control group. Li et al[49] reported some patients in both groups experienced headaches, dizziness, and palpitations when administered irbesartan. However, all these studies[33,49-51] reported that the above adverse events were mild in severity and spontaneously alleviated. The subsequent treatment was not affected by this (Supplementary Table 4).

Subgroup analysis

We performed subgroup analyses of 24hUP, UAER, Scr, BUN, β2-MG, CysC, Ccr, TC, TG, LDL-C, HDL-C, PV, WBLSV, and WBHSV. The results indicated that TXLC combination therapy for a duration of ≤ 12 weeks did not improve PV compared with conventional therapy [P = 0.06, SMD = -2.18, 95%CI: (-4.43, 0.06)]. Combination therapy duration > 12 weeks also did not improve UAER [P = 0.07, SMD = -0.63, 95%CI: (-1.30, 0.04)], Scr [P = 0.09, MD = -5.03, 95%CI: (-10.93, 0.87)], and BUN [P = 0.21, MD = -0.35, 95%CI: (-0.88, 0.19)]. When the sample size was < 100, the combination therapy group elevated HDL-C [P = 0.0001, MD = 0.29, 95%CI: (0.14, 0.43)] but did not improve β2-MG [P = 0.10, SMD = -2.37, 95%CI (-5.15, 0.42)], Scr [P = 0.06, MD = -9.24, 95%CI: (-19.00, 0.52)] and BUN [P = 0.08, MD = -0.30, 95%CI: (-0.63, 0.04)] (Supplementary Table 3).

Sensitivity analysis

The results of the meta-analyses for the remaining outcomes were robust, except for FPG, LDL-C, HDL-C, CysC, CRP, and PV. When conducting the sensitivity analysis for FPG, the results of the meta-analysis changed significantly after excluding the trials by Chen et al[39], Guo[48], Li and Lv[53], and Zhao and Zhang[41]. When performing sensitivity analysis on LDL-C, the meta-analysis results changed from [P = 0.04, MD = -0.74, 95%CI: (-1.46, -0.02)] to [P = 0.12, MD = -0.86, 95%CI: (-1.95, 0.23)] after excluding the trial by Chen et al[39]. In the sensitivity analysis of HDL-C, the meta-analysis result changed from [P = 0.08, MD = 0.19, 95%CI: (-0.02, 0.41)] to [P = 0.0001, MD = 0.29, 95%CI (0.14, 0.43)] after excluding the Yan[54] study. In the sensitivity analysis of CysC, the exclusion of studies by Wei et al[33] and Zhang et al[57] altered the meta-analysis results. The original pooled estimate [P = 0.03, MD = -0.31, 95%CI: (-0.58, -0.03)] shifted to [P = 0.24, MD = -0.30, 95%CI: (-0.79, 0.20)] and [P = 0.12, MD = -0.24, 95%CI: (-0.53, 0.06)], respectively. In the sensitivity analysis of CRP, the meta-analysis results changed from [P = 0.26, MD = -3.34, 95%CI (-9.13, 2.45)] to [P < 0.00001, MD = -6.35, 95%CI: (-8.40, -4.30)] after excluding the study by Bi et al[52]. In the sensitivity analysis of the PV, the combined effect sizes changed from statistically different to not statistically different after excluding the trials by Sun and Huang[40], Peng et al[44], Shen and Sun[32], and Yang[34] (Supplementary Table 5).

Publication bias

As shown in Figure 9, among the outcomes with no fewer than ten included studies, Scr (P = 0.348), BUN (P = 0.571), and UAER (P = 0.617) did not show publication bias. However, there was a publication bias in FPG (P = 0.001) and 24hUP (P = 0.014).

Figure 9 Publication bias analysis. A: 24-hour urine proteinuria; B: Urinary albumin excretion rate; C: Serum creatinine; D: Blood urea nitrogen; E: Fasting plasma glucose.

Quality of evidence

The quality of evidence for UAER, Scr, BUN, and FPG was ‘low’. The quality of evidence for 24hUP, UALB, β2-MG, Ccr, CysC, 2hPG, HbA1C, TC, TG, LDL-C, HDL-C, FIB, PV, WBLSV, WBHSV, CRP, NO, and ET-1 was 'very low’. Factors contributing to the low quality of evidence included poor methodological quality, small sample sizes, high heterogeneity, and potential publication bias (Supplementary Table 6).

DISCUSSION

Summary of evidence

In this study, we reviewed the effectiveness and safety of TXLC in combination with other biomedical treatments for DKD. Twenty-two RCTs involving 1941 participants were included in this systematic review. The results demonstrated the addition of TXLC significantly improved various health parameters in individuals with DKD compared with conventional biomedicine treatment. Specifically, improvements were observed in 24hUP, UALB, UAER, Scr, BUN, β2-MG, CysC, TC, TG, LDL-C, FIB, PV, WBLSV, WBHSV, NO, and ET-1. However, no significant effects were noted on Ccr, FPG, 2hPG, HbA1C, HDL-C, and CRP. In terms of safety, the majority of the included trials did not report adverse events. Therefore, we could not draw conclusions regarding the safety of TXLC intervention in patients with DKD.

Implications for clinical therapy

Role of TXLC in reducing urinary protein and improving renal function: A persistent increase in urinary protein and/or progressive decline in the estimated glomerular filtration rate (GFR) are the main clinical characteristics of DKD. Proteinuria is an important marker of kidney injury and an independent risk factor for the continued progression of renal lesions[58]. Therefore, early diagnosis and effective intervention of proteinuria are extremely important. Coresh et al[59] showed that a 30% reduction in albuminuria over a 2-year baseline period was linked to a 22% decrease in the risk of ESRD; after adjustment for measurement error, the hazard ratio was 0.78 (95%CI: 0.66-0.92). Heerspink et al[60] also reported that for every 30% reduction in geometric mean proteinuria, the risk of clinical endpoints was reduced by an average of 27%. In the current study, TXLC adjuvant therapy significantly decreased 24hUP and UAER in individuals with DKD, which is consistent with a report by Long et al[61]. Additionally, we evaluated the effects of TXLC on the UALB in patients with DKD. The results indicated that the addition of TXLC to conventional biomedicine therapy significantly decreased the UALB. In terms of improving renal function, TXLC supplementation was more beneficial in reducing Scr, BUN, β2-MG, and CysC in patients with DKD. Chen et al[31] also found that TXLC combined with Jinlida granule treatment reduced 24hUP, Scr, BUN, and CysC levels in patients with stage IV DKD compared to those with irbesartan. Several preclinical studies have similarly confirmed the urinary protein-reducing (UALB and UAER) and renal function-protecting (Scr, BUN, and β2-MG) effects of TXLC[62-64].

Proteinuria arises primarily from the disruption of the glomerular filtration barrier. Injury to podocytes, an important component of the filtration barrier, disrupts the integrity of the filtration membrane and leads to decreased glomerular filtration and subsequent proteinuria. Notably, TXLC antagonized podocyte damage in both in vivo and ex vivo DN models. Cui et al[18] found that TXLC protects DN podocytes from apoptosis by resisting oxidative stress and inhibiting the P38 pathway. Another report indicated that the mechanism by which TXLC attenuates podocyte damage is related to the inhibition of Notch1/snail pathway activation and increased nephrin expression[65]. miR-21, a key pathogenic factor in DKD, is upregulated in the renal tissue and serum of DKD patients and DN models[66]. Wang et al[17] reported that miR-21 overexpression promoted renal tubular EMT by enhancing TGF-β1/smad3 and suppressing smad7 expression, whereas TXLC inhibited miR-21-induced EMT, thereby improving renal structure and function. Wu et al[67] observed that TXLC inhibited the intercellular trafficking of TGF-β1-containing exosomes from glomerular endothelial cells to mesangial cells. In addition to inhibiting TGF-β1/Smad signaling[68], inhibiting Wnt/β-catenin activation[69] and modulating the expression of the degradative enzyme system MMP-9/TIMP-1[64] are also important pathways for TXLC to reduce extracellular matrix deposition and resist renal fibrosis. More importantly, TXLC also improves renal tubular reabsorption by upregulating the expression of megalin and cubilin in renal tissues[63]. These findings suggest that TXLC delays DN progression through multiple mechanisms.

Role of TXLC in the regulation of glucolipid metabolism: Regarding glucose metabolism, we found that the addition of TXLC did not significantly improve FPG, 2hPG, or HbA1C levels in patients with DKD compared to conventional treatment. Several previous studies have shown no significant effects of TXLC intervention on FPG and HbA1C in DN mice[62-64,70]. Thus, the renoprotective effect of TXLC in DN may be independent of glycemic reduction. Dyslipidemia and ectopic renal lipid accumulation are strongly associated with DN[71]. Consistent with a previous study[61], the current investigation revealed that TXLC adjuvant therapy significantly decreased TC, TG, and LDL-C levels but did not significantly improve HDL-C levels in patients with DKD. An animal experiment confirmed that TXLC was similar to simvastatin in reducing blood lipids, inhibiting plaque inflammation, and preventing the rupture of vulnerable plaques[72]. Another report stated that TXLC enhanced the lipid-lowering and anti-atherosclerotic effects of atorvastatin[73].

Role of TXLC in improving hemorheology: Hemodynamic abnormalities are a significant factor of proteinuria and glomerulosclerosis in individuals with DKD[74]. Hemorheology is an important index of the response to blood circulation. Improving hemorheology in patients with DKD is beneficial for clinical treatment[75,76]. Preclinical studies have demonstrated that TXLC can modulate the activity of the fibrinolytic system, reduce the hypercoagulable and hyperviscous state of blood, and improve local microcirculation in the kidneys[69,77]. Bai et al[69] observed that TXLC increases the levels of plasminogen activators and decreases the levels of plasminogen activator inhibitor 1 in the serum and renal cortex of DN rats. Data from this study showed that TXLC adjuvant therapy significantly reduced FIB, PV, WBLSV, and WBHSV in individuals with DKD. This finding was in agreement with the results reported by Zou et al[77]. According to a recent meta-analysis, TXLC was found to significantly decrease PSV, WBLSV, and WBHSV in individuals diagnosed with transient ischemic attack[78]. In addition, several drugs in the TXLC formulations exert antiplatelet effects[79,80]. For example, Wang et al[81] found that leeches might be more effective than aspirin in improving blood hyperviscosity.

Effect of TXLC on CRP in patients with DKD: Current evidence suggests that inflammation plays a role in the pathogenesis and progression of DN[82,83]. CRP is an important inflammatory mediator that has been revealed to be involved in the pathogenesis of DN. A significant increase in CRP expression was observed in the serum of DKD patients[84]. CRP concentration serves as an independent risk factor for CKD in individuals with type 2 DM[85]. High-sensitivity CRP levels were significantly and positively related to the presence of DKD[86]. Mechanistically, CRP may accelerate DKD development through multiple pathways. For example, Zhang et al[87] reported that CRP enhanced EMT in HK-2 cells through Wnt/β-catenin and ERK1/2 signaling. Liu et al[88] and You et al[89] observed that under diabetic conditions, CRP can promote renal inflammation and fibrosis through the TGF-β/Smad, CD32b-NF-κB, and CD42b-Smad3-mTOR pathways. Another study found that CRP exacerbates DKD by suppressing podocyte autophagy by inhibiting C3a/C3aR axis signaling[90]. In contrast, DKD was significantly attenuated in CRP-knockout rats[87]. Therefore, CRP emerges as a promising therapeutic target for treating DKD. However, this study revealed that the addition of TXLC did not reduce CRP levels in patients with DKD.

Role of TXLC in improving vascular endothelial function: In patients with DM not treated with ACEI, increases in plasma ET-1 were related to elevated systolic and diastolic blood pressure, whereas in DM patients treated with ACEI, increases in plasma NO were accompanied by significant decreases in systolic and diastolic blood pressure[91]. ET-1 has strong vasoconstrictor and profibrotic effects. In the kidney, ET-1 is essential for controlling the glomerular arteriolar tone, regulating hemodynamics, and maintaining renal perfusion[92,93]. A clinical trial showed that higher plasma ET-1 concentrations in patients with DKD were independently associated with a decreased GFR[94]. NO also has a critical role in modulating renal blood flow and vascular endothelial function[95]. Compared with healthy subjects, NO concentrations were significantly decreased in patients with DM combined with CKD[96]. Conversely, the promotion of NO production attenuates DN-induced vascular injury in renal tissues[97]. This study indicated that TXLC combination therapy was more beneficial than conventional therapy in terms of increasing NO levels and decreasing ET-1 levels. Thus, improving the vascular endothelial function may be one of the pathways of TXLC in the treatment of DKD.

Comparison with previous studies

There is only one published systematic review on TXLC for DKD. Unlike a previous study[61], this systematic review included RCTs published after 2008. Additionally, several outcome metrics (UALB, β2-MG, CysC, FIB, PV, WBLSV, WBHSV, CRP, and NO) were added. Renal tubular injury can occur in the early stages of DKD and has become a crucial therapeutic target[98,99]. SGLT2 inhibitors exert renoprotective properties by targeting renal tubular epithelial cells. Large clinical trials have confirmed that SGLT2 inhibitors can significantly improve renal composite endpoints in individuals with DM complicated by CKD[11,100]. β2-MG and CysC are biomarkers of renal tubular injury. FIB, PV, WBLSV, WBHSV, CRP, and NO are significant indicators reflecting hemodynamics, inflammation, and vascular endothelial function. A comprehensive evaluation of the effectiveness and mechanisms of TXLC in treating DKD was performed by reviewing these outcomes. For outcome metrics with I² > 75%, this study also conducted a subgroup analysis based on intervention duration and sample size to sufficiently explore the influential factors of heterogeneity. The Egger’s test was applied to assess publication bias for outcomes that included no fewer than 10 studies. We also used sensitivity analysis and the GRADE method to evaluate the robustness of the meta-analysis results and the overall quality of each outcome indicator.

Limitations

This systematic review still has some limitations: (1) The findings were less persuasive due to the poor methodological quality of the trials. For example, most trials did not mention specific methods of random sequence generation; allocation concealment, blinding, sample size estimation, or intentionality analysis were not reported in any of the trials; (2) The implementation sites of the included trials were all located in China. Therefore, the results of this study are applicable only for patients with DKD in China; (3) Long-term follow-up data were absent in all the studies reviewed. Therefore, the long-term efficacy of TXLC interventions for DKD remains unclear; (4) Inadequate safety evaluation of trials. Only six of the 22 studies reported adverse events, and the remaining studies did not describe whether adverse events occurred during the study. Therefore, the safety of TXLC for the treatment of DKD is uncertain; (5) None of the included studies differentiated the traditional Chinese syndromes in patients with DKD, which may affect the evaluation of the actual efficacy of TXLC; (6) The included studies differed in the TXLC doses used. This variation may have led to increased heterogeneity between the studies. Although we used a random-effects model to address this heterogeneity, the random-effects model by itself could not completely eliminate variations between the original studies; and (7) Some of the trials did not indicate the exact staging of DKD or specifications for TXLC. Thus, it was difficult to perform a subgroup analysis according to DKD stage and dose to investigate the underlying sources of heterogeneity.

Future perspectives

This systematic review suggests that the clinical trials of TXLC for DKD have several shortcomings. Therefore, we make the following recommendations for conducting future clinical studies on TXLC for DKD: (1) Improve the methodological quality of the studies. Future studies should strictly follow the design principles of RCTs, specify the approaches for randomization, implement allocation concealment and blinding, perform sample size estimation, and conduct intention-to-treat analysis; (2) Conduct multi-center, large-sample studies to improve the extrapolation and reliability of the findings; (3) Long-term follow-up is crucial to assess the long-term efficacy and potential adverse events of pharmaceutical treatments. We emphasize the importance of long-term follow-up and adverse event reporting to evaluate the long-term effectiveness and safety of TXLC in DKD patients; (4) Clinical trials of traditional Chinese medicine (TCM) should focus on standardizing TCM diagnosis and treatment. Future studies should consider syndrome differentiation in patients with DKD; (5) Many large clinical trials have used renal composite endpoint as the primary outcome. We recommend the enhanced monitoring and reporting of renal composite endpoint events in future clinical trials; and (6) There is a lack of studies exploring the relationship between dose and efficacy in TXLC. More high-quality RCTs are required to verify the relationship between dose and therapeutic effectiveness, as well as to evaluate the impact of different doses on clinical outcomes.

CONCLUSION

The evidence in this study showed that TXLC combined with conventional therapy was effective in improving urinary protein (24hUP, UALB, and UAER), renal function (Scr, BUN, β2-MG, and CysC), blood lipids (TC, TG, and LDL-C), hemorheology (FIB, PV, WBLSV, and WBHSV), and vascular endothelial function (NO and ET-1) in patients with DKD. However, because of the limitations of existing studies in terms of quantity and methodological quality, future research should prioritize conducting more multicenter RCTs with large sample sizes and long follow-up periods to better assess the effectiveness and safety of TXLC intervention in DKD.