Nerve identification in open inguinal hernioplasty: A meta-analysis
1Department of General Surgery, All India Institute of Medical Sciences, Bhubaneswar, India
2Department of Physical Medicine and Rehabilitation, All India Institute of Medical Sciences, Bhubaneswar, India
3 Department of Anatomy, All India Institute of Medical Sciences, Bhubaneswar, India
Objective: In open inguinal hernioplasty, three inguinal nerves are encountered in the surgical field. It is advisable to identify these nerves as careful dissection reduces the chances of debilitating post-operative inguinodynia. Recognizing nerves during surgery can be challenging. Limited surgical studies have reported on the identification rates of all nerves. This study aimed to calculate the pooled prevalence of each nerve from these studies.
Material and Methods: We searched PubMed, CENTRAL, CINAHL, ClinicalTrials.gov and Research Square. We selected articles that reported on the prevalence of all three nerves during surgery. A meta-analysis was performed on the data from eight studies. IVhet model from the software MetaXL was used for preparing the forest plot. Subgroup analysis was performed to understand the cause of heterogeneity.
Results: The pooled prevalence rates for Ilioinguinal nerve (IIN), Iliohypogastric nerve (IHN), and genital branch of genitofemoral nerve (GB) were 84% (95% CI 67-97%), 71% (95% CI 51-89%) and 53% (95% CI 31-74%), respectively. On subgroup analysis, the identification rates were higher in single centre studies and studies with a single primary objective as nerve identification. The heterogeneity was significant in all pooled values, excluding the subgroup analysis of IHN identification rates in single-centre studies.
Conclusion: The pooled values indicate low identification rates for IHN and GB. Significant heterogeneity and large confidence intervals reduce the importance of these values as quality standards. Better results are observed in single-centre studies and studies which are focused on nerve identification.
Keywords: Hernioplasty, inguinal hernia, peripheral nerves
Chronic inguinal pain is a known complication of groin hernia surgery. Mild to moderate inguinodynia is common, but some patients may experience severe pain (1). The etiology of pain is poorly understood, and injury to inguinal nerves may contribute to it (2,3). There is a need for meticulous dissection and identification of all inguinal nerves during surgery, which was first stressed by Amid 2004 from the Lichtenstein Institute (4). Subsequently, it was also endorsed by the European Hernia Society guidelines on the treatment of inguinal hernia and the international guidelines for groin hernia management (5,6).
Recognizing nerves during surgery can be challenging. Their numbers and positions vary, and one of the nerves (the genital branch of the genitofemoral nerve) is thin and inconspicuous. Studies have reported wide variations in nerve identification rates, making compliance with recommendations difficult. We need to calculate the pooled estimates from the available literature and search for the causes of variations, which will, in turn, increase our understanding of traditional hernioplasty surgery.
Material and Methods
Aim of the Study
The aim of the study was to calculate the pooled prevalence of nerve identification in open hernioplasty surgery and evaluate the effect of the study methodology on it. We also wanted to study the course of the nerves.
We searched the electronic database of PubMed/Medline, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov and Research Square in March 2022. The database of PubMed was searched with the following search strategies: Hernia, inguinal [Mesh] and peripheral nerves [Mesh], inguinal hernia [tiab] and nerves [tiab] and Lichtenstein repair [tiab]. We searched the database of CINAHL (EBSCO) with the following search strategy: inguinal hernia repair and inguinal nerves, keeping the search field optional. We searched the CENTRAL database with the terms inguinal hernia and inguinal nerves in the “title abstract keyword”. We manually searched the references list of some of the review articles with the help of google scholar.
Inclusion and Exclusion Criteria
The articles on open inguinal hernia surgery that reported on all three inguinal nerves were included in the study. Prospective studies of all types (prospective comparative cohort, prospective non-comparative cohort and randomized controlled trials) were included. We excluded articles in which a report on any of the three inguinal nerves was missing.
Retrospective studies, case reports, editorials, conference proceedings and reviews were excluded. We excluded articles on ultrasound-guided nerve blocks or plane identification as they added bias to the objectives. The studies on cadavers, pediatric patients, and laparoscopic hernia surgeries were also excluded. The duplicates from the electronic search were removed manually.
Selection of Studies and Data Extraction
Based on inclusion and exclusion criteria, two authors, AB and PRT, independently identified the articles as included, excluded and uncertain. For uncertain articles, the full text was obtained and then reviewed. The consensus on included articles was reached through the involvement of author MKS.
Following Cochrane guidelines, a standard data collection sheet was prepared. The authors AB and MKS went through all the selected articles and collected data on the author, publication year, country, study type, sample size, objectives, methodology and results. The consensus was reached for any discrepancy in data by involving the author PRT.
Quality Assessment of the Included Studies
The included studies were separated into different types. Quality assessment of the randomized controlled trial was performed with software review Manager 5.4 (9). We assessed comparative cohort studies with the Newcastle Ottawa scale (NOS) and cohort studies without a comparison arm with JBI critical appraisal checklist for the case series (10,11). The authors AB and PRT independently performed quality assessment. The involvement of author MKS resolved any disputes.
Data on nerve identification rates were extracted from the included studies. Binomial pooled prevalence was calculated, and forest plots were constructed using the Meta XL software. Statistical heterogeneity was measured with Cochrane’s Q and I2 statistics. The significance of heterogeneity was measured with the p-value. The funnel plots and the DOI plots were examined for asymmetry. We conducted a leave-one-out sensitivity analysis to understand the cause of heterogeneity. Subgroup analysis was conducted for objectives (single primary and multiple primaries) and the number of study centers (multi-centric and single center). An unweighted multiple regression analysis was conducted to identify the degree to which sample size, objectives and number of study centers were associated with nerve identification rates. SPSS 26.0 was used for regression analysis. The description of the course of the nerves was according to the source article.
The Outcome of Electronic Search
The PRISMA flow diagram of the study selection process is given in Figure 1. The initial search yielded 1214 articles, out of which 578 were duplicates, and 401 were ineligible for inclusion from titles/abstracts. The remaining 35 articles were searched for full text, and 32 articles were retrieved. Based on inclusion and exclusion criteria, the articles were further analyzed. After a careful review, only eight articles were selected for quantitative synthesis and systematic review (12-14).
Characteristics of the Included Studies
Characteristics of the included studies are presented in Table 1. The studies belonged to the period from 2006 to 2020. Two studies were from Brazil, and the remaining six were from Europe. The sample range was 29 to 973, with a median of 144. A total of 2118 surgical dissections were reported on nerve identification (15-22). The objectives of Lange 2009, Grossi 2015 and Mendes 2016 were centered on the intraoperative identification of the nerves only. There was more than one primary objective in other studies. The studies of Alfieri 2006, Lange 2009 and Sanders 2014 were multi-centric. Lange 2009 also studied the course of the nerves.
Qualitative Analysis of the Included Studies
Three comparative cohort studies, one randomized controlled trial and four non-comparative cohort studies were evaluated for quality. The result is presented in Table 2. All of the included studies were of good to excellent quality.
Meta-Analysis of Nerve Identification Rates
Ilioinguinal Nerve (IIN)
The forest plot of binomial pooled prevalence was constructed using the IVhet model (fixed effect, heterogeneity), as shown in Figure 2. In prevalence analysis, the IVhet model is preferred over the random effect model when the heterogeneity is significant, as seen in our study. It gives a more reliable coverage probability and exhibits lesser variance (23,24). We avoided the quality effect model as the methodology of included studies was heterogeneous (Table 2). The pooled prevalence rate of IIN was 84% (95% CI 67-97%). Statistical heterogeneity was significant (Cochrane’s Q 228.21, I2 97%, p< 0.001). On leave one out sensitivity analysis, the pooled prevalence varied from 81% to 91%. We analyzed the studies’ funnel and DOI plots. We detected major asymmetry in these (Figure 3). An unweighted multiple regression analysis was performed with IIN identification rate as a dependent variable and sample size, centers of study and objectives as independent variables. We found that none of the independent variables significantly affected the outcome [model summary: R2 = 0.50, p= 0.37; coefficient: sample size (β= -0.19, p= 0.77), center (β= -0.59, p= 0.31), objective (β= 0.16, p= 0.75)].
We performed the subgroup analysis of pooled prevalence for studies with a single primary objective vs studies with more than one primary objective and multicenter studies vs single center studies. The pooled prevalence in studies with a single primary objective was 0.88 (0.69-1.00). It was nearly the same in studies with more than one objective (0.84; 0.66-0.98) (Table 3A). The pooled prevalence in multicenter and single-center studies were 0.78 (0.58-0.95) and 0.95 (0.88-1.00), respectively (Table 3B).
Iliohypogastric Nerve (IHN)
The forest plot was constructed using the IVhet model (fixed effect, heterogeneity), as shown in Figure 2B. The pooled prevalence rate of IHN was 67% (95% CI 49-83%). Statistical heterogeneity was significant (Cochrane’s Q 244.15, I2 97%, p< 0.001). On leave one out sensitivity analysis, the pooled prevalence varied from 69% to 79%. We analyzed the studies’ funnel and DOI plots and detected major asymmetry. On multiple regression analysis, we found that none of the independent variables-sample size, centers of study and objectives significantly affected the IHN identification rates [model summary: R2 = 0.84, p= 0.14; coefficient: sample size (β= -0.55, p= 0.31), center (β= -0.13, p= 0.76), objective (β= 0.30, p= 0.46)].
On subgroup analysis, the pooled prevalence in studies with a single primary objective was 0.94 (0.85-1.00). It was 0.69 (0.49-0.88) in studies with more than one primary objective (Table 3A). The heterogeneity was not significant when two types of objectives were compared. This indicates that focused studies yield better identification rates for IHN. The pooled prevalence in multicenter and single-center studies were 0.54 (0.40-0.68) and 0.51 (0.12-0.90), respectively (Table 3B).
Genital Branch of Genitofemoral Nerve (GB)
The forest plot was constructed using the IVhet model (fixed effect, heterogeneity), as shown in the Figure 2C. The pooled prevalence rate of GB was 53% (95% CI 31-74%). Statistical heterogeneity was significant (Cochrane’s Q 256.15, I2 97%, p< 0.001). The pooled prevalence varied from 49% to 57% on leave one out sensitivity analysis. We analyzed the studies’ funnel and DOI plots and detected major asymmetry. On multiple regression analysis, we found that none of the independent variables-sample size, centers of study and objectives significantly affected the GB identification rates [model summary: R2 = 0.31, p= 0.64; coefficient: sample size (β= -0.26, p= 0.74), center (β= 0.27, p= 0.68), objective (β= -0.39, p= 0.53)].
On subgroup analysis, the pooled prevalence in studies with a single primary objective was 0.77 (0.52-0.97). It was 0.52 (0.30- 0.73) in studies with more than one primary objective (Table 3A). The pooled prevalence in multicenter and single-center studies were 0.54 (0.40-0.68) and 0.51 (0.12-0.90), respectively (Table 3B).
Studies with Nerve Identification as a Single Primary Objective vs Other Studies ( Table 3A)
We found three articles where identifying nerves was the only primary objective. This subgroup included Lange 2009, Grossi 2015 and Mendes 2016. The sample size was small in each of the studies, with the largest being 40 in the study of Lange 2009. The identification rates were over 85% for all nerves except for IIN in Lange 2009 and GB in Grossi 2015 (75% and 52.6%, respectively). The pooled prevalence rates in this subgroup were 88%, 94% and 77% for IIN, IHN and GB, respectively. Heterogeneity was insignificant in the pooled value of IHN (p= 0.06) only. The identification rate of IHN was 94%, indicating a uniform identification in focused studies.
In five articles, there was more than one primary objective. This subgroup included Alfieri 2006, Bartlett 2007, Bischoff 2012, Sanders 2014 and Cirocchi 2020. The sample size ranged from 115 to 973. Alfieri 2006 reported poor identification rates for all nerves. Sanders 2014 reported low identification for IHN and GB (66.8% and 47.7%). Bischoff 2012 and Cirocchi 2020 observed a low prevalence of GB. The pooled prevalence in this subgroup was 84%, 69% and 52% for IIN, IHN and GB, respectively. Identification of IHN and GB was low by more than 20% compared to the other subgroup (94% & 77% vs 65% & 52%). The IIN rates differed only marginally in the two subgroups.
Multicenter vs Single Center Studies ( Table 3B)
The studies of Alfieri 2006, Lange 2009 and Sanders 2014 were multi-centric. The sample size in the study of Lange 2009 was small. The other two studies were extensive. The nerve identification rate in single-center studies was 78%, 63% and 54% for IIN, IHN and GB, respectively. Heterogeneity was significant for all of the nerves.
Studies by Bartlett 2007, Bischoff 2012, Grossi 2015, and Mendes 2016 were conducted at a single center. The sample size ranged from 29 to 244. The pooled values for IIN, IHN and GB were 95%, 89% and 51%, respectively. More than a 20% increase in the identification of IIN and IHN was observed com pared to the other subgroup. However, the heterogeneity was significant for all nerves in this subgroup, as well.
Studies Detailing the Course of All Three Nerves During Surgery ( Table 3C)
Lange et al. tried identifying the course of all three nerves during the surgery. The course of the nerves was recorded as standard anatomy or the variations. The surety of nerve identification was classified as: sure, probably sure, maybe, and probably not. They concluded that it is possible to identify IIN and IHN in most cases and significant anatomical variations are not observed. GB was difficult to recognize in at least 25% of the cases. The surgeons, in these cases, were unsure of the structure as a nerve or could not locate the blue vein near it. In an additional 12.5% (5/40) of the cases, they failed to identify it. They reported variations in the course of IIN in 15% (6/40) of the patients. Early branching over the spermatic cord was observed in these cases.
The pooled prevalence of IIN, IHN and GB was 81% (95% CI 64-96%), 67% (95% CI 49-83%) and 57% (95% CI 38-76%), respectively. There was significant heterogeneity in the pooled values. We evaluated a possible association of study sample size, centers of study and number of primary objectives with nerve identification rates but failed to find any. On subgroup analysis, poor identification rates of IIN were observed in multi-centric studies. A similar effect was seen on IHN in multi-centric studies and studies with more than one primary objective. GB was better recognized in studies with a single primary objective. The identification of IHN in studies with a single primary objective was the only subgroup where hetero-geneity was not significant. These results indicate an acceptable good identification rate for IIN. The identification of IHN is adversely affected by the multicentricity and dilution in the focus of the study. The identification of GB is most difficult and probably unpredictable.
The anatomical location of inguinal nerves in the surgical field may explain some difficulties in their identification. The IIN lies on the spermatic cord. It may lie on the sac of an indirect (lateral) hernia or get displaced with the cord structures in a direct (medial) hernia. The nerve is frequently in the center of the surgical field, making identification easy. The IHN may be the most crucial regional nerve in respect to nerve entrapment during mesh fixation in open hernia repairs (25). It lies on the internal oblique muscle and its aponeurosis within the area of surgery. Its visualization needs retraction of the overlying external oblique aponeurosis. Its identification is difficult in comparison to IIN. Cirrochi 2018 also reported lower identification rates of IHN in their metanalysis (26). The GB is thin compared to two other nerves and lies posteriorly in the spermatic cord. Its visualization requires lifting and twisting of the cord. The difficult identification of GB is well-reported in the surgical literature (18,19,21,22).
The anatomical studies on cadavers report better identification of nerves. Cirrochi 2018 conducted a meta-analysis that included cadaveric and surgical studies. They have calculated 87% and 76.3% for IIN and IHN as the pooled prevalence. On subgroup analysis, the identification of IIN and IHN in cadavers was 98% and 99% (26), which indicates that the identification of nerves during surgery is more challenging than that on the cadavers. Multiple factors may play a role in this. The surgical field is blood-tinged, and the surgeon is more concerned about identifying and separating the hernia sac in the early steps. Lack of proper anatomical knowledge makes identifying the nerves in the inguinal region complex. This is especially true for IHN and GB, which are not in the center of the surgical field (27). The use of synthetic Mesh has made the surgery simple, and surgeons do not spare more time searching for a nerve.
Limited studies have reported the course of inguinal nerves during surgery. Lange 2009 found that the course of IHN was classical in all cases. They also said the course of IIN was classical in 75% of the cases. They could identify both these nerves in all cases (17). The course of IIN and IHN was also studied by Al-dabbagh 2002 and Emeksiz 2016. They reported the course as classical in only 50% of the cases. Their observations were based on a larger sample size (13,14). The anatomical studies on cadavers also report massive variation in the course of IHN and IIN (28,29).
The identification of GB is the most challenging. In the study by Cirrochi 2018, the pooled prevalence was 48.2% (26). Bischoff has identified this nerve in only 21.3% of the cases (18). This nerve runs close to the external spermatic vein and is called the blue vein. In case of difficulty, the nerve is presumed to be identified once the external spermatic vein is seen. This technique is seen in the study of Lange 2009 who identified GB in 35 out of 40 cases. They reported that they were unsure of the finding in at least 10 cases.
The values of pooled prevalence of the nerves are not suitable as the quality standard for hernia surgery. The presence of significant heterogeneity reduces the quality of pooled values. In our study, on subgroup analysis, better identification rates were observed for IIN and IHN in single-center studies. Further, in one subgroup with a single primary objective as nerve identification, heterogeneity was low for IHN identification. The pooled prevalence in this subgroup was 94%. This all suggests a possibility of better nerve identification with focused and motivated centers. Even if we use IIN as a quality standard, there is a probability of missing the nerve in 16% of the surgeries. The identification rates of the other two nerves, IHN and GB, are poor. We should continue identifying the nerves as this practice probably reduces the chances of debilitating chronic inguinodynia.
The objectives of our study were focused. We excluded studies on cadaveric dissection and studies that failed to report on all three nerves. The selected studies were recent, and their methodological quality was good to excellent. Nerve identification was the primary objective in all articles. The pooled findings indicate that higher identification rates of cadaveric studies are challenging to reproduce.
There are a few limitations of this study. The number of included studies was small, and they belonged to Europe or North America only. The study methodology was not uniform and included randomized controlled trials, prospective comparative cohort studies and prospective non-comparative cohort studies. Methodological quality assessment used three different tools. The detection of publication bias with funnel plot was unreliable as the number of included studies was less than ten (30). Due to the scarcity of data, we could not analyze the effect of some variables such as, body mass index, anthropometry and emergency surgery, on nerve identification rates.
More studies are needed that describe the course of inguinal nerves at the time of surgery. The studies should aim at simplifying the types of possible variation in the course of nerves. Further research is also needed to understand the feasibility of nerve identification in emergency surgeries.
This was a systematic review and meta-analysis of articles reporting the identification of all three inguinal nerves in open hernia surgery. The identification rates of none of the nerves were near 90% in the pooled estimates. It was even less in multi-centric studies and studies with more than one primary objective. The lowest identification rate was observed for the genital branch of the genitofemoral nerve. A comprehensive description of the course of the nerves was not seen in most of the studies. Based on nerve identification rates from this pool of studies, it is difficult to suggest a benchmark for the quality assessment of hernia surgery.
Cite this article as: Sinha MK, Barman A, Tripathy PR, Shetta A. Nerve identification in open inguinal hernioplasty: A meta-analysis. Turk J Surg 2022; 38 (4): 315-326.
This study was approved by All India of Medical Sciences Bhubaneswar Intstitutional Ethics Committee (Reference no: T/IM-NF/Surg/21/148, Date: 07.02.2022).
Concept – All of authors; Design – All of authors; Supervision – MKS; Data Collection and/ or Processing – MKS, PRT, AB; Analysis and/or Interpretation – MKS, PRT, AB; Literature Search – All of authors; Writing Manuscript – All of authors; Critical Reviews – MKS, AB, PRT.
The authors have no conflicts of interest to declare.
The authors declared that this study has received no financial support.
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