Abstract
Objective
To systematically compare the clinical efficacy and safety of four posterior surgical approaches—olecranon osteotomy (OO), triceps-reflecting approach (TRA), triceps-splitting approach (TS), and triceps tongue approach (TT)—for the treatment of AO/OTA type C complete intra-articular distal humerus fractures, and to provide evidence-based guidance for surgical approach selection.
Methods
This study was conducted in accordance with the PRISMA 2020 guidelines. PubMed, EMBASE, Web of Science, the Cochrane Library, and major Chinese databases were systematically searched for randomized controlled trials published up to September 2025. Eligible studies included patients with AO/OTA type C complete intra-articular distal humerus fractures treated using OO, TRA, TS, or TT approaches. Primary outcomes included the rate of excellent or good functional outcomes, Mayo Elbow Performance Score (MEPS), operative time, intraoperative blood loss, and overall complication rate. A network meta-analysis was performed using Stata 16.0, calculating odds ratios (ORs) or mean differences (MDs) with corresponding 95% confidence intervals (CIs). Between-study heterogeneity (τ2) and network consistency were assessed, and the surface under the cumulative ranking curve (SUCRA) was used to estimate the probability ranking of each surgical approach.
Results
A total of 12 randomized controlled trials involving 1,258 patients with AO/OTA type C complete intra-articular distal humerus fractures were included. Network meta-analysis demonstrated no statistically significant differences among the four posterior approaches with respect to the rate of excellent or good functional outcomes, MEPS, operative time, or intraoperative blood loss. SUCRA rankings suggested that OO ranked relatively higher for functional outcome and operative time, while TS ranked higher for intraoperative blood loss; however, none of these comparisons reached statistical significance. Regarding overall complication rates, TRA was associated with a lower risk of complications compared with OO, whereas TS showed a higher complication rate than OO. No statistically significant differences were observed in the remaining comparisons.
Conclusion
Current evidence indicates that OO, TRA, TS, and TT posterior approaches provide comparable overall clinical outcomes in the management of AO/OTA type C complete intra-articular distal humerus fractures, with most outcome measures showing no statistically significant differences. SUCRA rankings reflect only relative probability trends within the network model and should not be interpreted as substitutes for effect sizes or statistical significance. Surgical approach selection should therefore be individualized based on fracture characteristics, soft tissue conditions, and surgeon experience.
Keywords: Distal humerus fracture, AO/OTA type c fracture, Surgical approach, Network meta-analysis, Olecranon osteotomy
Introduction
Complete intra-articular distal humerus fractures are complex injuries typically resulting from high-energy direct or indirect trauma, with fracture lines frequently involving the articular surface of the elbow joint. Epidemiological data indicate that these fractures account for approximately 0.5%–7% of all fractures, with up to 96% involving the articular surface [1]. A bimodal age distribution has been reported, predominantly affecting adolescent males aged 12–19 years and elderly women over 80 years of age [2]. Owing to the complex anatomy of the distal humerus, poor bone quality, and proximity to critical neurovascular structures, surgical management remains challenging. Adequate exposure is required to achieve anatomical reduction, while minimizing soft tissue disruption to preserve elbow function, representing a major technical dilemma for orthopedic surgeons [3].
Currently, dual-plate fixation has been widely accepted as the standard surgical treatment for AO/OTA type C distal humerus fractures. However, the optimal posterior surgical approach remains controversial. Commonly used approaches include the olecranon osteotomy (OO), triceps splitting approach (TS; also referred to in some Chinese literature as the medial–lateral triceps splitting approach), triceps tongue approach (TT), and triceps-reflecting approach (TRA). The OO approach provides excellent visualization of the articular surface and facilitates accurate fracture reduction; nevertheless, it is associated with potential complications such as delayed union or nonunion of the osteotomy, implant irritation, and hardware-related symptoms [4, 5]. Non-osteotomy approaches, including TS and TT, avoid olecranon-related complications and reduce direct disruption of the extensor mechanism, but often provide limited exposure, making fracture reduction technically demanding, particularly in highly comminuted fractures [6].
The TRA has emerged as a modified non-osteotomy technique in recent years. By reflecting the triceps–anconeus complex as a single unit, this approach aims to balance adequate exposure with preservation of soft tissue integrity and has gained increasing clinical acceptance [7]. Several studies have compared the clinical outcomes of different posterior approaches. Some reports suggest that the TRA can achieve exposure comparable to the OO approach while reducing intraoperative blood loss, nerve injury, and osteotomy-related complications [8]. Other studies have demonstrated favorable functional outcomes with the TRA combined with dual-plate fixation, reporting a postoperative flexion–extension arc of up to 121°, a mean Mayo Elbow Performance Index (MEPI) score of 81 points, and a Disabilities of the Arm, Shoulder and Hand (DASH) score of approximately 11.7, facilitating early postoperative rehabilitation [9]. However, contrasting evidence indicates that in cases of severe comminution or multi-fragmentary fractures, the exposure provided by the TRA may be inferior to that achieved with olecranon osteotomy [7, 10].
Given these inconsistent findings, the optimal selection of posterior surgical approaches according to fracture characteristics and surgical requirements remains unclear. Therefore, the present study aims to systematically compare the clinical efficacy and safety of OO, TS, TT, and TRA in the treatment of complete intra-articular distal humerus fractures using a network meta-analysis, with the goal of providing more comprehensive and reliable evidence to inform surgical decision-making.
Methods
Eligibility criteria
This study was conducted in strict accordance with the PRISMA 2020 guidelines and aimed to compare the clinical outcomes of different posterior surgical approaches for the treatment of AO/OTA type C distal humerus fractures.
Inclusion criteria were as follows:1.Study design: randomized controlled trials (RCTs);2.Participants: adult patients (≥ 18 years) diagnosed with complete intra-articular distal humerus fractures or AO/OTA type C distal humerus fractures confirmed by imaging modalities (plain radiography or computed tomography), regardless of sex;3.Interventions: studies comparing one or more of the following posterior surgical approaches: olecranon osteotomy (OO), triceps splitting approach (TS; also referred to in some Chinese literature as medial–lateral triceps splitting), triceps tongue approach (TT), and triceps-reflecting approach (TRA);4.Outcomes: studies reporting at least one of the following primary outcomes: (1) rate of excellent or good postoperative functional outcomes (% or number of cases); (2) Mayo Elbow Performance Score (MEPS); (3) operative time (min); (4) intraoperative blood loss (mL); (5) overall complication rate;
5.Data availability: sufficient data reported as means ± standard deviations or event counts to allow quantitative synthesis;6.Language: studies published in English or Chinese with full text available.
Exclusion criteria were as follows:1.non-randomized studies, including retrospective studies, case series, reviews, conference abstracts, or commentaries;2.studies including AO/OTA type A or type B distal humerus fractures without separate analysis of type C fractures;3.studies not reporting any primary outcome of interest;4.incomplete or irretrievable data unsuitable for meta-analysis;5.duplicate publications or studies with overlapping patient populations;6.non-clinical studies, including biomechanical experiments, cadaveric studies, imaging simulations, reviews, case reports, or conference abstracts.
Identification and management of overlapping or duplicate publications
To avoid duplicate inclusion of identical patient cohorts, all potentially eligible studies were carefully screened for overlapping data. Baseline characteristics, including sample size, mean age and standard deviation, AO/OTA fracture classification, follow-up duration, geographic region, and study period, were compared across studies.
During this process, studies by Song et al. (2014) [11] and Shen et al. (2014) [36] were found to be highly similar in terms of sample size, age distribution, fracture classification, and follow-up duration, suggesting that they may have originated from the same patient cohort. To maintain the independence of included data and avoid double counting, the study by Shen et al. (2014) was excluded, and the study by Song et al. (2014), which provided more comprehensive outcome data, was retained.
Literature search strategy
Two investigators independently performed a systematic literature search of eight electronic databases: PubMed, EMBASE, Web of Science, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, Wanfang Data, and SinoMed.
The search covered all records from database inception to September 2025. Search terms included combinations of Medical Subject Headings (MeSH) and free-text terms such as “complete intra-articular distal humerus fracture,” “distal humeral fracture,” “AO type C,” “olecranon osteotomy,” “triceps splitting,” “triceps tongue flap,” “triceps-reflecting approach,” and “posterior surgical approach.” Boolean operators were used to construct comprehensive search strategies to maximize sensitivity and ensure complete retrieval of relevant studies.
Study selection and data extraction
All retrieved records were managed using EndNote X9 software. Two investigators independently screened titles and abstracts to exclude duplicates, reviews, and clearly irrelevant studies. Full-text articles were then assessed according to the predefined eligibility criteria to determine final inclusion.The following data were extracted: first author and publication year, sample size (intervention and control groups), patient age, AO/OTA fracture classification, intervention and comparator surgical approaches, outcome measures (rate of excellent or good functional outcomes, MEPS, operative time, intraoperative blood loss, and overall complication rate), follow-up duration, and risk-of-bias information. Data extraction was cross-checked, and any discrepancies were resolved through discussion with a third investigator.
Risk of bias assessment
The methodological quality of all included randomized controlled trials was assessed using the Revised Cochrane Risk of Bias tool for randomized trials (RoB 2.0). The following domains were evaluated: (1) bias arising from the randomization process, (2) bias due to deviations from intended interventions, (3) bias due to missing outcome data, (4) bias in outcome measurement, and (5) bias in selection of the reported result. Two investigators independently assessed the risk of bias and classified each domain as low risk, high risk, or some concerns. Any disagreements were resolved by consensus or consultation with a third investigator.
Statistical analysis
Network meta-analysis (NMA) was performed using Stata version 16.0. Considering potential clinical and methodological heterogeneity among studies in terms of patient characteristics, surgical techniques, and clinical settings, all outcomes were synthesized using random-effects network meta-analysis models.Continuous outcomes (MEPS, operative time, and intraoperative blood loss) were expressed as mean differences (MDs), whereas dichotomous outcomes (rate of excellent or good functional outcomes and overall complication rate) were expressed as odds ratios (ORs), both with corresponding 95% confidence intervals (CIs). Between-study heterogeneity was quantified using the τ2 statistic.Network plots were constructed to illustrate the geometry of direct and indirect comparisons among different surgical approaches, and league tables were generated to present pairwise comparison results. Treatment ranking probabilities were estimated using the surface under the cumulative ranking curve (SUCRA), with values ranging from 0% to 100%, where higher values indicate a greater probability of being the most favorable intervention within the network.Network consistency was evaluated using both local node-splitting (side-splitting) methods and global inconsistency models. Publication bias was qualitatively assessed using comparison-adjusted funnel plots. All statistical tests were two-sided, and a P value < 0.05 was considered statistically significant.
Results
Study selection
A total of 3,627 records were initially identified from eight electronic databases. After removing 1,578 duplicate records using EndNote X9 software, 2,049 articles remained for further screening. Titles, abstracts, and publication types were then screened, resulting in the exclusion of 296 non-original studies, including reviews, systematic reviews, case reports, and conference abstracts. In addition, 1141 studies were excluded because they did not meet the inclusion criteria, such as failing to compare different posterior surgical approaches or enrolling patients without complete intra-articular distal humerus fractures or AO/OTA type C distal humerus fractures.Consequently, 612 articles were retrieved for full-text assessment. During full-text review, 600 studies were excluded due to failure to report any of the predefined outcomes of interest (rate of excellent or good functional outcomes, Mayo Elbow Performance Score [MEPS], operative time, intraoperative blood loss, or overall complication rate), incomplete or non-extractable data, duplicated data, or unavailability of full-text articles.Ultimately, 12 randomized controlled trials that met all eligibility criteria were included in the systematic review and network meta-analysis. The detailed study selection process is illustrated in Fig. 1.
Fig. 1.
Flow diagram of the literature selection process in this study
Study characteristics and risk of bias assessment
A total of 12 randomized controlled trials (RCTs) involving 1258 adult patients with AO/OTA type C complete intra-articular distal humerus fractures were included in the present analysis. The sample sizes of individual studies ranged from 40 to 150 participants, with generally comparable numbers of patients allocated to the intervention and control groups within each trial. The included studies were published between 2014 and 2024, and all enrolled adult populations, with mean ages predominantly ranging from 30 to 55 years.
Regarding fracture classification, several studies further subclassified AO/OTA type C fractures into C1, C2, and C3 subtypes, whereas others reported fractures as AO-C without further specification. In terms of interventions, all included studies employed posterior surgical approaches combined with internal fixation. Olecranon osteotomy (OO) was the most frequently investigated approach and was included as either the experimental or control intervention in all trials. Other posterior approaches evaluated across studies included the triceps splitting approach (TS), triceps tongue approach (TT), and triceps-reflecting approach (TRA). Although the specific combinations of surgical approaches compared varied among studies, all comparisons focused on these commonly used posterior approaches.
With respect to outcome reporting, all included studies reported the rate of excellent or good postoperative functional outcomes. Additional outcomes, including the Mayo Elbow Performance Score (MEPS), operative time, intraoperative blood loss, and postoperative complication rate, were reported in a subset of studies, resulting in some variability in outcome availability across trials. Follow-up durations ranged from 3 to 18 months, with most studies reporting follow-up periods of 6 to 12 months; a small number of studies provided longer-term follow-up data. Detailed baseline characteristics of the included studies are summarized in Table 1.
Table 1.
Summary of the characteristics of the 12 included randomized controlled trials
| Study (First author, Year) | Sample size (Exp/Ctrl) | Age (years) | AO fracture type (C1/C2/C3) | Intervention group | Control group | Outcomes reported | Follow-up duration |
|---|---|---|---|---|---|---|---|
| Song [11] | 42/43 | 43.5 ± 5.4/43.6 ± 5.5 | OO: C1 = 18, C2 = 13, C3 = 11/TS: C1 = 19, C2 = 12, C3 = 12 | OO | TS | 1,2,3,4 | 12 months |
| Wu [12] | 23/23 | 53.3 ± 10.2/55.5 ± 9.6 | C1 = 12, C2 = 20, C3 = 14 | OO | TS | 1,3,5 | 6 months |
| Da [13] | 41/41 | 45.1 ± 3.4/45.1 ± 3.3 | AO-C (not specified) | OO | TT | 1,3,4 | ≥ 3 months |
| Teng [14] | 49/49 | 43.4 ± 2.3/43.8 ± 2.2 | OO: C1 = 20, C2 = 25, C3 = 4/TS: C1 = 19, C2 = 24, C3 = 6 | TS | OO | 1,3,4 | 12 months |
| Pazila Aila [15] | 35/35 | 33.5 ± 10.4/34.1 ± 9.5 | OO: C1 = 12, C2 = 9, C3 = 14/TT: C1 = 15, C2 = 8, C3 = 12 | OO | TT | 1,3,4,5 | 12 months |
| Huang [16] | 50/50 | 48.5 ± 5.9/48.8 ± 5.5 | AO-C (not specified) | OO | TT | 1,3,4,5 | 6–12 months |
| Dong [17] | 49/49 | 46 ± 10/48 ± 9 | OO: C1 = 9–10; C2 = 13–15; C3 = 27–24 | OO | TT | 1,3,4 | 12 months |
| Du [18] | 26/26 | 37.3/37.5 | All C3 type | OO | TS | 1,2 | 18 months (mean 14–43 months) |
| Fang [19] | 45/45 | 44.6 ± 6.9/44.8 ± 7.2 | OO: C1 = 12, C2 = 16, C3 = 17/TS: C1 = 13, C2 = 17, C3 = 15 | OO | TS | 1,2 | 1, 3, 6 months |
| Muhammad Usman Khalid [20] | 75/75 | 53.84 ± 11.86/44.19 ± 15.59 | AO-C (not specified) | OO | TS | 1,2 | 3 months |
| Nuthan Jagadeesh [21] | 20/20 | 43 ± 12.4/40.3 ± 13.1 | TRA: C1 = 12, C2 = 6, C3 = 2/OO: C1 = 10, C2 = 8, C3 = 2 | TRA | OO | 1,2,5 | 15–16 months |
| Rohit Ailan [22] | 20/20 | 43.2 (18–58)/37.5 (21–55) | TRA: C1 = 7, C2 = 11, C3 = 3/OO: C1 = 7, C2 = 9, C3 = 3 | TRA | OO | 1,2,3,5 | 12 months |
OO = olecranon osteotomy; TS = triceps-splitting approach (also referred to as the medial–lateral triceps splitting approach in some Chinese studies); TT = triceps tongue-shaped flap approach; TRA = triceps-reflecting approach.Outcome indicators: 1 = Postoperative functional excellence rate (% or cases); 2 = Mayo Elbow Performance Score (MEPS, points); 3 = Operative time (minutes); 4 = Intraoperative blood loss (mL); 5 = Overall incidence of complications
The methodological quality of the included trials was assessed using the Revised Cochrane Risk of Bias tool for randomized trials (RoB 2.0), and the results are presented in Table 2. Several studies reported adequate randomization procedures and complete outcome data, and were therefore judged to be at low risk of bias overall. Some studies were rated as having “some concerns” due to insufficient reporting of random sequence generation, allocation concealment, or blinding procedures. A small number of trials employed non-rigorous randomization methods, such as allocation based on admission order or odd–even numbering, and were consequently assessed as being at high risk of bias. Overall, although methodological quality varied among the included studies, no substantial or systematic missing outcome data were identified.
Table 2.
Summary of risk of bias assessment (RoB 2.0) for the 12 included studies
| No. | Author (Year) | Randomization process | Deviations from interventions | Missing outcome data | Measurement of the outcome | Selection of the reported result | Overall risk of bias | Summary of key assessment reasons |
|---|---|---|---|---|---|---|---|---|
| 1 | Dong (2021) | Low risk | Unclear | Low risk | Unclear | Unclear | Low risk | Adequate randomization; complete data; no major missing outcomes. |
| 2 | Khalid (2015) | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear risk | Claimed randomization but insufficient methodological details; lack of blinding. |
| 3 | Fang (2024) | Low risk | Unclear | Low risk | Unclear | Unclear | Low risk | Random number table; standardized procedure; complete outcome reporting. |
| 4 | Jagadeesh (2020) | High risk | Unclear | Low risk | Unclear | Unclear | High risk | Odd–even allocation without concealment; predictable assignment. |
| 5 | Teng (2017) | Low risk | Unclear | Low risk | Unclear | Unclear | Low risk | Reasonable randomization; complete data; limited intervention bias. |
| 6 | Ailani (2024) | Unclear | Low risk | Unclear | Unclear | Low risk | Unclear risk | Computerized randomization but unclear concealment; partial loss to follow-up. |
| 7 | Du (2022) | Low risk | Unclear | Low risk | Unclear | Unclear | Low risk | Clear randomization; reasonable grouping; complete data. |
| 8 | Song (2014) | High risk | Unclear | Low risk | Unclear | Unclear | High risk | Sequential allocation (pseudo-randomization); no blinding. |
| 9 | Huang (2019) | Unclear | Unclear | Low risk | Unclear | Unclear | Unclear risk | Adequate randomization but no blinded assessors. |
| 10 | Pazila Aila (2018) | Unclear | Unclear | Low risk | Unclear | Unclear | Unclear risk | Random number table; complete data; no trial registration. |
| 11 | Dai (2017) | Unclear | Unclear | Low risk | Unclear | Unclear | Unclear risk | Envelope randomization but unclear sealing; lack of blinding. |
| 12 | Wu (2016) | Unclear | Unclear | Low risk | Unclear | Unclear | Unclear risk | Reasonable randomization; complete data; no assessment blinding. |
RoB 2.0 domains include: (1) Randomization process; (2) Deviations from intended interventions; (3) Missing outcome data; (4) Measurement of the outcome; (5) Selection of the reported result. Overall bias levels are categorized as Low risk, High risk, or Unclear risk
Network meta-analysis results
Rate of excellent or good postoperative functional outcomes
A total of 12 randomized controlled trials involving four posterior surgical approaches (olecranon osteotomy [OO], triceps-reflecting approach [TRA], triceps splitting approach [TS], and triceps tongue approach [TT]) were included in the network meta-analysis. The network geometry demonstrated good connectivity, with all approaches linked through direct or indirect comparisons (Fig. 2).With respect to heterogeneity, between-study variability was quantified using the τ2 parameter in the random-effects network meta-analysis model (τ = 1.19, τ2 = 1.42). Given the relatively simple network structure, node-splitting analysis did not detect any significant inconsistency between direct and indirect evidence, indicating good overall network consistency.Using OO as the reference intervention, the multivariate random-effects model showed no statistically significant differences among the posterior approaches. Specifically, the log odds ratio (log OR) for TRA versus OO was − 0.07 (95% CI, − 2.25 to 2.11; P = 0.948), for TS versus OO was − 0.39 (95% CI, − 1.48 to 0.71; P = 0.487), and for TT versus OO was − 0.77 (95% CI, − 2.05 to 0.51; P = 0.241). None of these comparisons reached statistical significance. Similarly, indirect comparisons among the remaining approaches did not demonstrate significant differences, suggesting comparable overall efficacy of the four posterior approaches in terms of postoperative functional outcome (Table 3).Based on 10,000 Monte Carlo simulations, SUCRA ranking probabilities indicated that OO (71.7%) and TRA (59.4%) ranked relatively higher, followed by TS (44.0%), whereas TT (24.9%) ranked lowest. As none of the pairwise comparisons showed statistically significant effect sizes, these rankings should be interpreted with caution and reflect only the relative probability of each approach within the network model rather than definitive superiority (Fig. 3; Table 4).Comparison-adjusted funnel plots did not reveal any obvious asymmetry, suggesting a low risk of publication bias for this outcome (Fig. 4).
Fig. 2.
Network plot of the network meta-analysis (NMA) for postoperative functional excellence rate
Table 3.
League table of postoperative functional excellent rate (OR [95% CI])
| Comparison | OR (95% CI) | Interpretation |
|---|---|---|
| B vs. A (TRA vs. OO) | −0.07 (− 2.25, 2.11) | No statistically significant difference |
| C vs. A (TS vs. OO) | −0.39 (− 1.48, 0.71) | No statistically significant difference |
| D vs. A (TT vs. OO) | −0.77 (− 2.05, 0.51) | No statistically significant difference |
| C vs. B (TS vs. TRA) | – | No statistically significant difference (indirect comparison) |
| D vs. B (TT vs. TRA) | – | No statistically significant difference (indirect comparison) |
| D vs. C (TT vs. TS) | – | No statistically significant difference (indirect comparison) |
A = OO; B = TRA; C = TS; D = TT
Fig. 3.
Surface under the cumulative ranking curve (SUCRA) ranking plot for postoperative functional excellence rate
Table 4.
SUCRA ranking of postoperative functional excellent rate
| Surgical approach | SUCRA (%) | PrBest (%) | Mean rank |
|---|---|---|---|
| A (OO) | 71.7 | 34.9 | 1.8 |
| B (TRA) | 59.4 | 43.4 | 2.2 |
| C (TS) | 44.0 | 14.7 | 2.7 |
| D (TT) | 24.9 | 7.0 | 3.3 |
A higher SUCRA value indicates a higher probability of being ranked as a more effective surgical approach within the network model
Fig. 4.
Funnel plot assessing publication bias for postoperative functional excellence rate. Note A = OO, B = TRA, C = TS, D = TT
Mayo elbow performance score
Six randomized controlled trials comparing three posterior surgical approaches—olecranon osteotomy (OO), triceps-reflecting approach (TRA), and triceps splitting approach (TS)—were included in the network meta-analysis for the Mayo Elbow Performance Score (MEPS). The network geometry was fully connected and allowed for the integration of both direct and indirect evidence (Fig. 5).Between-study heterogeneity was quantified using the τ2 statistic in the random-effects network meta-analysis model (τ = 7.02, τ2 = 49.21). Given the simple network structure, which included only comparisons among OO, TRA, and TS, node-splitting analysis did not identify any significant inconsistency between direct and indirect evidence, indicating good overall model consistency.Using OO as the reference intervention, the random-effects model showed no statistically significant differences in MEPS among the three surgical approaches. Specifically, the mean difference (MD) for TRA versus OO was − 0.10 (95% CI, − 9.91 to 9.71; P = 0.984), while the MD for TS versus OO was − 0.75 (95% CI, − 7.83 to 6.33; P = 0.835). Indirect comparisons likewise revealed no significant differences, suggesting comparable overall effects of the three posterior approaches on postoperative elbow function as assessed by MEPS (Table 5).SUCRA ranking probabilities were similar across the three approaches, with OO ranking at 54.2%, followed by TRA at 52.0% and TS at 43.8%. The close distribution of SUCRA values did not indicate a clearly superior approach. As none of the effect estimates reached statistical significance, these rankings should be interpreted cautiously and reflect only relative probability trends within the network model (Fig. 6; Table 6).Comparison-adjusted funnel plots were approximately symmetrical, with no evident indication of publication bias for this outcome (Fig. 7).
Fig. 5.
Network plot of the network meta-analysis (NMA) for Mayo Elbow Performance Score (MEPS)
Table 5.
League table of the Mayo elbow performance score (MD [95% CI])
| Comparison | MD (95% CI) | Interpretation |
|---|---|---|
| B vs. A (TRA vs. OO) | −0.10 (− 9.91, 9.71) | No statistically significant difference |
| C vs. A (TS vs. OO) | −0.75 (− 7.83, 6.33) | No statistically significant difference |
| C vs. B (TS vs. TRA) | — (no significant difference, indirect comparison) | No statistically significant difference |
A = OO; B = TRA; C = TS.
Fig. 6.
SUCRA ranking plot for Mayo Elbow Performance Score (MEPS)
Table 6.
SUCRA ranking of the Mayo elbow performance score
| Surgical approach | SUCRA (%) | Probability of being the best (PrBest, %) | Mean rank |
|---|---|---|---|
| A (OO) | 54.2 | 29.2 | 1.9 |
| B (TRA) | 52.0 | 41.9 | 2.0 |
| C (TS) | 43.8 | 29.0 | 2.1 |
Higher SUCRA values indicate a higher probability of being ranked more favorably for this outcome
Fig. 7.
Funnel plot assessing publication bias for Mayo Elbow Performance Score (MEPS). Note A=OO, B = TRA, C = TS, D = TT
Operative time
Eight randomized controlled trials comparing operative time among four posterior surgical approaches—olecranon osteotomy (OO), triceps-reflecting approach (TRA), triceps splitting approach (TS), and triceps tongue approach (TT)—were included in the network meta-analysis. The network geometry was complete and well connected, supporting both direct and indirect comparisons among all approaches (Fig. 8).Between-study heterogeneity was assessed using the τ2 statistic in the random-effects network meta-analysis model (τ = 21.59, τ2 = 466.20). Given the relatively simple network structure, node-splitting analysis did not identify any significant inconsistency between direct and indirect evidence, indicating good overall network consistency.
Fig. 8.
Network plot of the network meta-analysis (NMA) for operative time
Using OO as the reference intervention, the multivariate random-effects model revealed no statistically significant differences in operative time among the four approaches. Specifically, the mean difference (MD) for TRA versus OO was 8.00 min (95% CI, − 34.49 to 50.49; P = 0.712), for TS versus OO was 24.10 min (95% CI, − 0.56 to 48.76; P = 0.055), and for TT versus OO was 11.90 min (95% CI, − 9.53 to 33.33; P = 0.277). Although the comparison between TS and OO approached statistical significance, it did not reach the conventional threshold (P = 0.055). Indirect comparisons among the remaining approaches also did not demonstrate statistically significant differences, suggesting comparable operative times across the four posterior approaches (Table 7).Based on 10,000 Monte Carlo simulations, SUCRA ranking probabilities indicated that OO ranked highest (82.4%), followed by TRA (55.5%), TT (45.0%), and TS (17.0%). These rankings suggest that the OO approach had a higher probability of being associated with shorter operative time within the network model. However, as none of the effect estimates reached statistical significance, the SUCRA rankings should be interpreted with caution and should not be considered definitive evidence of superiority (Fig. 9; Table 8). Comparison-adjusted funnel plots did not reveal any obvious asymmetry, indicating a low risk of publication bias for this outcome (Fig. 10).
Table 7.
League table of operative time (MD [95% CI])
| Comparison | MD (95% CI) | Interpretation |
|---|---|---|
| TRA vs. OO (B vs. A) | 8.00 (− 34.49, 50.49) | No statistically significant difference |
| TS vs. OO (C vs. A) | 24.10 (− 0.56, 48.76) | No statistically significant difference (P = 0.055, marginally close to significance but not statistically significant) |
| TT vs. OO (D vs. A) | 11.90 (− 9.53, 33.33) | No statistically significant difference |
| TS vs. TRA (C vs. B) | – (Indirect comparison, no statistically significant difference) | No statistically significant difference |
| TT vs. TRA (D vs. B) | – (Indirect comparison, no statistically significant difference) | No statistically significant difference |
| TT vs. TS (D vs. C) | – (Indirect comparison, no statistically significant difference) | No statistically significant difference |
A = OO; B = TRA; C = TS; D = TT
Fig. 9.
SUCRA ranking plot for operative time
Table 8.
SUCRA ranking of operative time
| Surgical approach | SUCRA (%) | PrBest (%) | Mean rank |
|---|---|---|---|
| A (OO) | 82.4 | 53.8 | 1.5 |
| B (TRA) | 55.5 | 34.3 | 2.3 |
| D (TT) | 45.0 | 10.0 | 2.6 |
| C (TS) | 17.0 | 1.9 | 3.5 |
Higher SUCRA values indicate a higher probability of a shorter operative time
Fig. 10.
Comparison-adjusted funnel plot assessing publication bias for operative time. Note A=OO, B = TRA, C = TS, D = TT
Intraoperative blood loss
Six randomized controlled trials comparing intraoperative blood loss among three posterior surgical approaches—olecranon osteotomy (OO), triceps splitting approach (TS), and triceps tongue approach (TT)—were included in the network meta-analysis. The network geometry was complete and well connected, supporting both direct and indirect comparisons among the three approaches (Fig. 11).Between-study heterogeneity was quantified using the τ2 statistic in the random-effects network meta-analysis model (τ = 101.57, τ2 = 10,317.0). Given the simple network structure, node-splitting analysis did not detect any significant inconsistency between direct and indirect evidence, indicating good overall network consistency.Using OO as the reference intervention, the multivariate random-effects model showed no statistically significant differences in intraoperative blood loss. Specifically, the mean difference (MD) for TS versus OO was − 104.96 mL (95% CI, − 245.92 to 36.01; P = 0.144), while the MD for TT versus OO was 48.99 mL (95% CI, − 50.81 to 148.80; P = 0.336). Both comparisons failed to reach statistical significance, suggesting no clear difference in intraoperative blood loss among the three approaches. Indirect comparison between TS and TT also did not demonstrate a statistically significant difference (Table 9).Based on 10,000 Monte Carlo simulations, SUCRA ranking probabilities indicated that TS ranked highest (94.0%), suggesting a higher probability of lower intraoperative blood loss, followed by OO (45.6%) and TT (10.4%). However, as the confidence intervals of all effect estimates crossed zero and none of the comparisons reached statistical significance, these rankings should be interpreted cautiously and represent only relative probability trends rather than definitive conclusions (Fig. 12; Table 10).Comparison-adjusted funnel plots appeared largely symmetrical, indicating a low risk of publication bias for this outcome (Fig. 13).
Fig. 11.
Network plot of the network meta-analysis (NMA) for intraoperative blood loss
Table 9.
League table of intraoperative blood loss (MD [95% CI])
| Comparison | MD (95% CI) | Interpretation |
|---|---|---|
| TS vs. OO (B vs. A) | −104.96 (− 245.92, 36.01) | No statistically significant difference (P = 0.144) |
| TT vs. OO (C vs. A) | 48.99 (− 50.81, 148.80) | No statistically significant difference (P = 0.336) |
| TT vs. TS (C vs. B) | (Indirect comparison, no statistically significant difference) | No statistically significant difference |
A = OO; B = TS; C = TT
Fig. 12.
SUCRA ranking plot for intraoperative blood loss
Table 10.
SUCRA ranking of intraoperative blood loss
| Surgical approach | SUCRA (%) | PrBest (%) | Mean rank |
|---|---|---|---|
| B (TS) | 94.0 | 90.9 | 1.1 |
| A (OO) | 45.6 | 6.3 | 2.1 |
| C (TT) | 10.4 | 2.8 | 2.8 |
Higher SUCRA values indicate a higher probability of less intraoperative blood loss for this outcome
Fig. 13.
Funnel plot assessing publication bias for intraoperative blood loss. Note A=OO, B = TRA, C = TS, D = TT
Overall complication rate
Five randomized controlled trials comparing postoperative complication rates among four posterior surgical approaches—olecranon osteotomy (OO), triceps-reflecting approach (TRA), triceps splitting approach (TS), and triceps tongue approach (TT)—were included in the network meta-analysis. The network geometry demonstrated good connectivity, allowing for the integration of both direct and indirect evidence (Fig. 14).Between-study heterogeneity was negligible, with the random-effects network meta-analysis estimating extremely low between-study variance (τ = 4.44 × 10−11, τ2 ≈ 0), indicating minimal statistical heterogeneity across studies. Given the simple network structure, node-splitting analysis did not detect any significant inconsistency between direct and indirect evidence, suggesting good overall network consistency.Using OO as the reference intervention, the multivariate random-effects model revealed statistically significant differences in overall complication rates for two comparisons. Specifically, the log odds ratio (log OR) for TRA versus OO was − 1.64 (95% CI, − 2.65 to − 0.63; P = 0.001), indicating a significantly lower complication risk associated with the TRA. In contrast, the log OR for TS versus OO was 1.37 (95% CI, 0.08 to 2.65; P = 0.037), suggesting a significantly higher complication risk with the TS approach. No statistically significant difference was observed between TT and OO (log OR = 0.26; 95% CI, − 0.75 to 1.27; P = 0.612). Indirect comparisons among the remaining approaches (e.g., TRA vs. TT, TRA vs. TS, and TS vs. TT) did not demonstrate statistically significant differences (Table 11).Based on 10,000 Monte Carlo simulations, SUCRA ranking probabilities indicated that TRA ranked highest (99.8%), reflecting the highest probability of being associated with the lowest overall complication risk, followed by OO (55.8%), TT (40.8%), and TS (3.7%). Although TRA showed a marked advantage in SUCRA ranking, these results should be interpreted in conjunction with the corresponding effect sizes and associated uncertainty. Except for the statistically significant differences observed between TRA and OO and between TS and OO, no other comparisons reached statistical significance; therefore, the SUCRA rankings should be interpreted with caution (Fig. 15; Table 12).Comparison-adjusted funnel plots did not reveal any obvious asymmetry, suggesting a low risk of publication bias for this outcome (Fig. 16).
Fig. 14.
Network plot of the network meta-analysis (NMA) for overall incidence of complications
Table 11.
League table of overall complication rate (OR [95% CI])
| Comparison | OR (95% CI) | Interpretation |
|---|---|---|
| TRA vs. OO (B vs. A) | 0.19 (0.07, 0.53) | The complication rate was significantly lower with TRA than with OO (P = 0.001) |
| TS vs. OO (C vs. A) | 3.93 (1.09, 14.20) | The complication rate was significantly higher with TS than with OO (P = 0.037) |
| TT vs. OO (D vs. A) | 1.30 (0.47, 3.56) | No statistically significant difference (P = 0.612) |
| TS vs. TRA (C vs. B) | (Indirect comparison, no statistically significant difference) | No statistically significant difference |
| TT vs. TRA (D vs. B) | (Indirect comparison, no statistically significant difference) | No statistically significant difference |
| TT vs. TS (D vs. C) | (Indirect comparison, no statistically significant difference) | No statistically significant difference |
A = OO; B = TRA; C = TS; D = TT
Fig. 15.
SUCRA ranking plot for overall incidence of complications
Table 12.
SUCRA ranking of overall complication rate
| Surgical approach | SUCRA (%) | PrBest (%) | Mean rank |
|---|---|---|---|
| B (TRA) | 99.8 | 99.5 | 1.0 |
| A (OO) | 55.8 | 0.0 | 2.3 |
| D (TT) | 40.8 | 0.5 | 2.8 |
| C (TS) | 3.7 | 0.0 | 3.9 |
Higher SUCRA values indicate a higher probability of a lower risk of overall complications
Fig. 16.
Funnel plot assessing publication bias for overall incidence of complications. Note A=OO, B = TRA, C = TS, D = TT
Discussion
In this study, a network meta-analysis was conducted to systematically compare the efficacy and safety of four commonly used posterior surgical approaches—olecranon osteotomy (OO), triceps-reflecting approach (TRA), triceps splitting approach (TS), and triceps tongue approach (TT)—for the treatment of AO/OTA type C complete intra-articular distal humerus fractures. Overall, no statistically significant differences were observed among the four approaches with respect to major efficacy-related outcomes, including the rate of excellent or good postoperative functional outcomes, Mayo Elbow Performance Score (MEPS), operative time, and intraoperative blood loss. These findings suggest that, based on currently available randomized controlled evidence, none of the posterior approaches demonstrates a clear overall superiority in terms of clinical efficacy.
In addition, SUCRA rankings were used to estimate the probability of each surgical approach occupying a relatively favorable position for each outcome. It should be emphasized that SUCRA rankings represent relative probability distributions under the assumptions of the network model and do not replace effect size estimates or statistical significance testing. Therefore, when most pairwise comparisons fail to reach statistical significance, SUCRA results should be interpreted as descriptive trends rather than evidence of definitive clinical advantage or grounds for preferential recommendation of a specific approach.
Regarding functional recovery, no statistically significant differences were identified among the posterior approaches in terms of either the rate of excellent or good functional outcomes or MEPS. Although the OO approach tended to rank relatively higher in SUCRA analyses for certain functional outcomes, this trend has often been attributed in previous studies to its ability to provide extensive visualization of the articular surface, thereby facilitating anatomical reduction in complex intra-articular fractures [23–26]. However, in the present analysis, the corresponding effect estimates were associated with wide confidence intervals crossing the null value, indicating insufficient evidence to support a statistically significant functional advantage of OO. These findings suggest that postoperative functional recovery in AO/OTA type C distal humerus fractures may depend more on the quality of fracture reduction, stability of internal fixation, and postoperative rehabilitation protocols than on the choice of surgical approach alone.
Similarly, no statistically significant differences were observed among the posterior approaches with respect to operative time. Although OO ranked relatively higher in SUCRA analysis, potentially reflecting the benefit of improved exposure in certain surgical scenarios [27], operative time is inherently influenced by multiple factors, including surgeon experience, team coordination, fracture complexity, and fixation strategy [28]. The present results therefore indicate that differences in operative efficiency among posterior approaches are generally modest and unlikely to represent consistent or reproducible advantages.
With respect to intraoperative blood loss, the TS approach showed a higher SUCRA ranking, suggesting a potential trend toward reduced blood loss. From a technical perspective, TS avoids olecranon osteotomy and may reduce bony and soft tissue dissection, which could theoretically contribute to lower intraoperative bleeding [29]. However, none of the relevant comparisons reached statistical significance, and substantial between-study heterogeneity was observed for this outcome. Such heterogeneity may be attributable to differences in surgical technique, perioperative hemostatic strategies, and surgeon experience across studies. Consequently, the available evidence does not support a definitive conclusion regarding the superiority of any posterior approach in minimizing intraoperative blood loss.
In terms of safety, the present analysis demonstrated a statistically significant reduction in overall complication rates for the TRA compared with the OO approach. This finding is biologically plausible, as the TRA avoids olecranon osteotomy and preserves the extensor mechanism, thereby potentially reducing osteotomy-related complications and soft tissue disruption [30–32]. In contrast, OO requires osteotomy and subsequent fixation of the olecranon, which may increase the risk of delayed union, nonunion, implant irritation, and postoperative elbow stiffness [31, 32]. Nevertheless, it should be noted that the number of included studies reporting complication outcomes was limited, and methodological shortcomings—particularly related to randomization procedures and blinding—were present in some trials. Therefore, although this finding is statistically significant, it should be interpreted cautiously and confirmed by larger, high-quality randomized controlled studies.
Overall, no single posterior approach demonstrated consistent superiority across all efficacy and safety outcomes. Instead, different approaches exhibited varying probability trends across different outcome domains, reflecting the heterogeneity and inconsistency of conclusions reported in previous studies. While some investigations have emphasized the importance of articular exposure and reduction quality [33, 34], others have focused on soft tissue preservation and complication avoidance [35]. By integrating both direct and indirect evidence, the present network meta-analysis provides a more comprehensive and balanced comparison of commonly used posterior approaches, offering clinically relevant evidence to support individualized surgical decision-making.
Several limitations of this study should be acknowledged. First, the number of included randomized controlled trials was relatively small, and some comparisons—particularly those involving the TT approach—were based on limited sample sizes, which may reduce the precision of effect estimates. Second, variability among studies in fracture subclassification, surgical technique, surgeon experience, and postoperative rehabilitation protocols may have contributed to clinical heterogeneity. Although random-effects models were applied to account for between-study variability, residual heterogeneity cannot be completely excluded. Third, follow-up durations for some outcomes were relatively short, limiting the assessment of long-term functional recovery and late complications. Finally, as emphasized above, SUCRA rankings reflect relative probability trends rather than definitive evidence and should be interpreted in conjunction with effect sizes, confidence intervals, and clinical context.
Conclusion
This network meta-analysis compared the efficacy and safety of four posterior surgical approaches—olecranon osteotomy (OO), triceps-reflecting approach (TRA), triceps splitting approach (TS), and triceps tongue approach (TT)—for the treatment of AO/OTA type C distal humerus fractures. Overall, none of the major outcome measures demonstrated statistically significant differences in effect size, indicating that the four approaches provide comparable overall clinical efficacy.SUCRA ranking probabilities suggested that OO ranked relatively higher for the rate of excellent or good postoperative functional outcomes and operative time, TRA had the highest probability of being associated with a lower overall complication risk, TS showed higher probability rankings for intraoperative blood loss and MEPS, whereas TT tended to rank lower across most outcomes. As SUCRA rankings reflect relative probability trends rather than definitive evidence of superiority, these findings should be interpreted with caution.In summary, each posterior approach has distinct characteristics, and no single technique can be considered universally superior. Surgical approach selection should therefore be individualized, taking into account fracture pattern, soft tissue conditions, and surgeon experience.
Author contributions
This network meta-analysis was primarily written by Huacan Yao, who also covered all publication-related expenses. Wenjie Chen and Zhen Lin contributed to data organization, statistical analysis, figure preparation, and language editing. As the corresponding author, Hui Cao was responsible for overall coordination, manuscript revision, and submission. Huacan Yao and Wenjie Chen contributed equally to this work. Zhen Lin is the third author. Hui Cao is the corresponding author.
Funding
This study was funded by the Medical Key Specialty Construction Project under the 14th Five-Year Plan of Foshan.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethical approval and consent to participate
This study was reviewed and approved by the Ethics Committee of The Affiliated Shunde Hospital of Jinan University, Foshan, Guangdong Province, China, and complies with ethical requirements.
Consent to publish
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Huacan Yao and Wenjie Chen contributed equally to this work. Zhen Lin is the third author. Hui Cao is the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.