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Systematic Review and Meta-analysis
ARTICLE IN PRESS
doi:
10.25259/JASSM_8_2026

Learning curves in arthroscopic surgery: A scoping review of knee, shoulder, and hip procedures

Department of Orthopedic Surgery, Post Graduate Institute of Medical Education and Research Center, Chandigarh, India.

*Corresponding author: Akshay A. Shreegan, Department of Orthopedic Surgery, Post Graduate Institute of Medical Education and Research Center, Chandigarh, India. akshayshreegan111@gmail.com

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Kumar V, Shreegan AA. Learning curves in arthroscopic surgery: A scoping review of knee, shoulder, and hip procedures. J Arthrosc Surg Sports Med. doi: 10.25259/JASSM_8_2026

Abstract

Background and aims:

Arthroscopic surgery is a technically demanding modality with outcomes closely linked to surgeon experience. Learning curves vary across joints due to differences in anatomy, access, and procedural complexity. Understanding these learning trajectories is essential to optimize training, patient safety, and early independent practice. The purpose of the study is to systematically map existing evidence on learning curves in knee, shoulder, and hip arthroscopy, with emphasis on operative efficiency, clinical outcomes, complication rates, and the influence of surgeon experience and practice environment.

Materials and Methods:

This study was conducted as a scoping review in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. PubMed/MEDLINE and Embase were searched for peer-reviewed clinical studies published over the past 25 years evaluating learning curve metrics. Surgeons were categorized as novice (<30 cases) or experienced (≥30 cases).

Results:

Knee arthroscopy demonstrated a relatively short learning curve, with early gains in technical efficiency. Shoulder arthroscopy showed progressive reductions in operative time and retear rates, with meaningful improvements observed beyond 50–100 cases. Hip arthroscopy exhibited the steepest learning curve, with significant reductions in operative/traction times and complication rates occurring after approximately 70–110 cases. Practice in tertiary care settings was consistently associated with improved efficiency and safety profiles.

Conclusion:

Learning curves in arthroscopy are joint-specific and most pronounced in hip and complex shoulder procedures. Structured training, mentorship, and early practice within high-volume tertiary care centers play a critical role in flattening the learning curve.

Keywords

Arthroscopy
Experience
Hip
Knee
Learning curve
Shoulder
Surgical education
Tertiary care center

INTRODUCTION

Arthroscopic surgery has revolutionized the management of numerous joint disorders by enabling minimally invasive access to joint spaces for both diagnostic and therapeutic procedures. Beginning with early work by pioneers such as Takagi, arthroscopy has evolved into a cornerstone in orthopedic practice for knee, hip, and shoulder pathology, offering benefits in terms of reduced soft-tissue trauma, faster rehabilitation times, and improved patient satisfaction compared with open techniques. The knee was one of the first joints widely adopted for arthroscopy, followed by rapid expansion into shoulder and hip procedures.[1]

The concept of the surgical learning curve describes the progressive improvement in technical performance and outcomes as a surgeon gains experience with a particular procedure. Arthroscopic procedures differ markedly by joint anatomy, access difficulty, and procedural demand factors that can influence learning trajectories across knee, hip, and shoulder arthroscopy.[2]

Knee arthroscopy is often perceived as a procedure with a less steep learning curve, partly because of the relative ease of joint access and a more forgiving anatomical compartment. Formal assessments using cumulative sum statistical techniques demonstrate measurable improvements in performance after approximately 14–20 diagnostic knee arthroscopies. Nevertheless, technical precision for therapeutic tasks like meniscectomy often extends the learning process beyond basic diagnostic proficiency.[3]

Learning curves for shoulder arthroscopy, particularly procedures such as arthroscopic Bankart repair, reflect both a reduction in operative time and a decline in complication rates with experience.[4] Earlier studies evaluating arthroscopic rotator cuff repair (RCR) reported decreasing operative time within the first 10–20 cases, which illustrates rapid early learning in technical execution, although comprehensive mastery usually requires more extensive experience.[5]

In contrast, the learning curve for hip arthroscopy has been repeatedly described as more challenging relative to knee and shoulder procedures. Anatomical constraints of the hip joint, including its deeper location and thick soft-tissue envelope, make instrument navigation and portal placement technically demanding.[6] Beyond joint-specific variability, surgeon experience has been linked to complication profiles and long-term outcomes. Novice surgeons are more likely to encounter technical challenges such as portal-related injuries or extended operative durations, which may adversely impact outcomes during early practice.[7]

The primary objective of this scoping review is to systematically map the existing evidence on learning curves associated with arthroscopic procedures of the knee, hip, and shoulder joints, with a focus on comparing performance outcomes between novice (<30 cases) and experienced (≥30 cases) surgeons. In addition, we examine the influence of surgical context, such as tertiary care center exposure, on learning curve progression.

MATERIALS AND METHODS

Study design and framework

This scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A detailed search and screening strategy was developed to identify peer-reviewed studies reporting learning curve metrics for knee, hip, or shoulder arthroscopy.

Information sources and search strategy

Databases searched: PubMed/MEDLINE, Embase

Search terms included “Arthroscopy,” “Learning Curve,” “Knee,” “Shoulder,” “Hip,” “Surgical education,” “Experience,’’ and “Tertiary care center.”

Eligibility criteria

Inclusion criteria were (1) original clinical studies involving knee, hip, or shoulder arthroscopic procedures; (2) studies reporting measurable learning curve outcomes (e.g., operative time, complication rate); (3) comparisons of surgeon experience (novice vs. experienced); and (4) publication in peer-reviewed journals within the past 25 years. Exclusion criteria included simulation-only studies without clinical outcome data, non–peer-reviewed reports, and studies focused on unrelated surgical domains.

Exclusion

  • (1) Simulation-only studies without clinical outcomes;

  • (2) Cadaveric-only studies;

  • (3) non-arthroscopic procedures;

  • (4) Reviews, editorials, case reports.

A total of 1800 records were identified. After duplicate removal and screening, 20 studies were included:

  • Knee arthroscopy: 6

  • Shoulder arthroscopy: 7

  • Hip arthroscopy: 7.

PRISMA Framework

The Study Selection process conducted in accordance with PRISMA guidlines, including identification, screening, eligibility and inclusion stages as illustated in flow diagram [Figure 1].

PRISMA framework.
Figure 1:
PRISMA framework.

Operational definitions

To allow synthesis across studies, surgeon experience categories were defined based on common cutoffs in the literature:

  • Novice/early experience: Surgeons who have performed fewer than 30 arthroscopic procedures for a given joint

  • Experienced: Surgeons who have performed ≥30 procedures

  • The 30-case threshold was selected as a pragmatic comparative reference point based on frequently cited early learning curve cutoffs in arthroscopic literature. However, this threshold does not represent definitive procedural mastery. True proficiency thresholds vary by joint and procedure, with hip arthroscopy often requiring substantially higher case volumes.

Study characteristics

Table 1 summarizes the included studies by author, year, joint, sample size, primary learning metric, and identified proficiency threshold. We included both clinical and simulation-based studies. Evidence for knee arthroscopy learning curves was predominantly derived from simulator-based and training-focused studies, whereas shoulder and hip arthroscopy conclusions were primarily based on clinical outcome investigations. Designs varied: Several were prospective series (e.g. Hodgins et al. 2014, Guttmann et al. 2005, You et al. 2020, Haipeng et al. 2021), [3,5-7] while others were retrospective analyses (e.g. Elkins et al. 2020, Dumont et al. 2020, Westermann, 2023). [8-10] Most were single-surgeon series or small cohorts, except Hodgins et al. [3] (multiple trainees) and Go et al. [11] (systematic review of 13 hip studies).

Table 1: Summery of included studies evaluating learning curves in arthroscopic procedures.
Author (Ref) Year Joint Sample (cases) Learning metric Proficiency threshold (approx.)
Hodgins et al.[3] 2014 Knee 20 trainees (340 arthroscopies) LCCUSUM for diagnostic accuracy Competency ~16 cases03
Guttmann et al.[5] 2005 Shoulder 100 patients (rotator cuff repair [RCR]) Repair time (RCRtime); operative time Plateau after ~10–20 cases
Elkins et al.[8] 2020 Shoulder 1600 arthroscopic RCRs Operative time; retear rate Time plateau ~450 cases
Dumont et al.[10] 2020 Hip 225 hip arthroscopies (FAI/labrum) Total room and surgical time Major time drop after 75 cases
You et al.[7] 2020 Hip 190 FAI cases (168 with 2-year f/u) Procedure and traction time; PROs Procedure time decreased after approximately 70 cases; traction time decreased until approximately 110 cases
Go et al.[11] 2020 Hip Systematic review (13 studies) Complication and reoperation rates; time Reported thresholds 30–519 cases (varied)
Westermann[9] 2023 Hip 1000 cases (PRO analysis) 1-year HOOS (patient-reported outcomes) HOOS improvements plateau by ~250 cases
Lim et al.[13] 2021 Shoulder 200 Shoulder arthroscopies Retear rate and clinical outcomes Proficiency improvement after ~100 cases
Putzer et al.[12] 2022 Knee 40 (VR simulator: 24 students, 16 residents) Simulator task time Steeper gains for novices; no fixed “cases”

LC-CUSUM: Learning curve cumulative sum, VR: Virtual reality, FAI: Femoral acetabulam impingment, PROs : Patient reported outcomes HOOS : Hip disability and osteoarthritis outcome score

Joint-specific outcomes, risks, and case thresholds

Table 2 summarizes common complications, risk factors, and approximate case thresholds by joint. These entries combine findings from the above studies and established literature.

Table 2: Joint-Specific complications, risk factors and approximate learning curve thresholds in arthroscopy.
Joint Main complications Key risk factors Approx. cases for competence
Knee Rare (e.g., infection, DVT)[3] None specific to learning; patient factors (age, comorbidities)[3] ~16 cases for basic diagnostic skill[3]
Shoulder (rotator cuff repair) Rotator-cuff retear (~10–15% rate)[8] Large tear size, older age, low surgeon experience[8] Approximately 100–450 cases for proficiency, with an operative time plateau observed at approximately 450 cases[8]
Hip Neuropraxia (2–5%) and iatrogenic cartilage/labrum injury[6,7] Prolonged traction, surgeon inexperience[6,8] ~70–110 cases for efficiency (procedure/traction times);[7]~250 for optimal patient-reported outcomes[9]

DVT: Deep vein thrombosis

Knee

Competency in diagnostic knee arthroscopy was typically reached by ~16 cases; serious complications (infection, deep vein thrombosis) are exceedingly rare in arthroscopy, and no specific “experience” risk factors are reported in these studies.

Shoulder

The dominant complication is tendon retear. Elkins et al. [8] found a 13% retear rate overall and identified larger tears, fewer prior cases (surgeon inexperience), older age, and full-thickness tears as independent risk factors for retears. The learning curve for operative efficiency flattened only after hundreds of cases (operative time plateau at ≈450 RCRs).

Hip

Common early complications include traction-related nerve injuries (e.g., pudendal neurapraxia) and iatrogenic chondral or labral damage during portal placement. Inexperience is implied (early cases had more portal errors). Other known risk factors in the literature (not directly cited here) include female sex and high body mass index. Efficiency in hip arthroscopy improved with volume: You et al. [7] showed procedure time significantly decreased after ~70 cases and traction time until ~110 cases. Patient outcomes (HOOS) continued to improve into the 200s–1000s of cases, indicating a very long learning curve.

Considerable methodological heterogeneity exists across included studies, including variability in design (prospective vs. retrospective), surgeon setting (single-surgeon vs. multi-center), outcome metrics (operative time, complication rates, and PROs), and reported proficiency thresholds (16–>450 cases). Given this methodological diversity, direct quantitative comparison across joints is not appropriate, thereby reinforcing the suitability of a scoping review framework rather than meta-analysis. Table 3 summarizes this methodological heterogeneity across included studies.

Table 3: Summary of methodological heterogeneity across included studies.
Author Year Joint Study design Surgeon setting Sample size Primary learning metric Proficiency threshold reported Heterogeneity domain
Hodgins et al.[3] 2014 Knee Prospective Multiple trainees 340 arthroscopies LC-CUSUM diagnostic accuracy ~16 cases Multi-surgeon variability
Putzer et al.[12] 2022 Knee Prospective (simulation) Trainees’ versus residents 40 participants Simulator task time No fixed case number Simulation versus clinical heterogeneity
Loisel et al.[17] 2015 Knee Prospective Mixed trainees Not specified LC-CUSUM skill tracking Variable Statistical methodology variation
Guttmann et al.[5] 2005 Shoulder Retrospective Single- surgeon 100 rotator cuff repair cases Operative time 10–20 cases Single-surgeon bias
Lim et al.[13] 2021 Shoulder Retrospective Single- surgeon 200 cases Retear rate ~100 cases Structural outcome metric
Elkins et al.[8] 2020 Shoulder Retrospective Multi- surgeon 1,600 cases Operative time; retear rate ~450 cases Large database variability
Shin et al.[14] 2018 Shoulder Retrospective database Multi- centers American Board of Orthopedic Surgery database Complication rates Not case- specific Registry-based heterogeneity
Takeda et al.[4] 2009 Shoulder Prospective Single- surgeon 119 cases Operative time, number of used anchors 100 cases Single-surgeon bias
Dumont et al.[10] 2020 Hip Retrospective Single- surgeon 225 cases Total room/surgical time ~75 cases Single-surgeon design
You et al.[7] 2020 Hip Prospective Single- surgeon 190 cases Procedure and traction time; PROs 70–110 cases Prospective efficiency metric
Haipeng et al.[6] 2021 Hip Prospective Single- surgeon 50 cases Portal setup time ~30 cases Technical skill focus
Westermann[9] 2023 Hip Retrospective Multi- surgeon 1000 cases 1-year HOOS PROs ~250 cases PRO-based heterogeneity
Go et al.[11] 2020 Hip Systematic review Multi- study 13 studies Complication and reoperation rates 30–519 cases Wide threshold variability
Neufeld et al.[15] 2025 Hip Retrospective Multi- surgeon 740 cases Operative and idle time Volume- based Annual volume effect
Sadjadi et al.[24] 2024 Shoulder Retrospective Nationwide multi- surgeon 1,489 surgeons Outcomes versus volume Volume- dependent National database
Frank et al.[16] 2014 Knee Prospective (simulation) Trainees Not specified Simulator performance No fixed threshold Non-clinical endpoint
Martin et al.[19] 2016 Shoulder Prospective (simulation) Trainees Not specified Skill acquisition Not case-based Simulation environment
James et al.[20] 2020 Mixed (knee and Hip) Prospective (cadaveric) Residents Not specified Procedural laboratory training Not case-based Cadaveric variability
Vaishya et al.[21] 2021 Mixed (knee and Hip) Narrative review Multiple Not applicable Learning curve review Variable Secondary literature
Schopper et al.[22] 2023 Knee (robotic) Retrospective Mentorship setting Not specified Operative time Flattened with mentorship Supervision effect

LC-CUSUM: Learning curve cumulative sum, PROs: Patient reported outcomes, HOOS : Hip disability and osteoarthritis outcome score

RESULTS

Knee arthroscopy

Direct clinical comparisons of knee arthroscopy outcomes between novice and experienced groups are scarce. However, training studies show improved technical performance with repetition. Residents generally show faster task completion and fewer unintentional camera movements than novices, indicating skill acquisition that may translate to better clinical performance. While specific clinical operative time differences are not well-quantified by a set case threshold, simulator-based assessments consistently demonstrate that operative efficiency improves with repetition.[12]

Shoulder arthroscopy

For arthroscopic RCR, clinical outcomes improve with increasing surgeon experience. In a study comparing the first 100 consecutive cases to a later set of 100 cases, retear rates decreased from ~18% to ~8% as experience increased.[13] Operative times also decline; in one large analysis, mean operative time decreased from ~35 min in early cases to ~20 min after substantial experience.[8] General complication rates for shoulder arthroscopy are approximately 7.9%, with stiffness and residual pain being most common.[14]

Hip arthroscopy

Hip arthroscopy exhibited the steepest learning curve. Prospective evaluations indicate significant reductions in procedure and traction times after approximately 70–110 cases, with maximum efficiency often achieved past this threshold.[7] A systematic review also showed that the quality of outcomes improved significantly after approximately 250 cases, with PROs continuing to improve beyond even larger case volumes, suggesting that extended experience enhances final clinical results.[9] A study comparing three sequential groups of cases found that the initial 75 procedures required significantly longer surgical times than later cases, reflecting operative efficiency improvements as surgeons progress along the learning curve.[10] In addition, studies report that surgeons performing >25 hip arthroscopies per year had shorter idle/operative components than lower-volume surgeons, reinforcing that increasing procedural volume correlates with greater efficiency.[15] Hip arthroscopy complication rates decrease as surgeons gain experience. A systematic review of studies on learning curves found that measures such as complication rates and reoperation rates reduced with increasing surgeon experience. Specifically, complication rates ranged widely among early cases but trended downward in later cases, with some studies noting reductions from higher early percentages to lower rates with accumulated experience.[11]

DISCUSSION

This scoping review synthesized evidence on learning curves in arthroscopic surgery, focusing on clinical outcomes, operative time, and complication rates as surrogate measures of procedural proficiency.

Clinical outcomes and surgeon experience

Arthroscopic RCR, a common shoulder procedure, demonstrates improved clinical outcomes with increasing surgeon experience. In a study comparing the first 100 consecutive cases to a later set of 100 cases performed by the same surgeon, retear rates decreased from ~18% to ~8% as experience increased, demonstrating improved structural outcomes with experience.[13] One systematic analysis suggested that functional outcomes improved after around 250 cases of hip arthroscopy, indicating that clinical improvement may extend beyond initial procedural efficiency gains.[2]

Operative time trends

Knee arthroscopy simulation studies also support improvements in task performance time with repeated practice, although robust clinical series documenting operative time differences stratified by case experience remain limited. Simulation evidence shows that trainees achieve reduced task completion time with repetition.[16] For hip arthroscopy, operative and traction times have been reported to decrease with increasing surgeon experience. Systematic reviews frequently use 30 cases as a pragmatic threshold differentiating early from late experience, with significant operative time reductions noted beyond this point.[2] In shoulder arthroscopy, large cohort studies show that operative times decline progressively with experience, with early case series having longer mean surgical times that steadily reduce as surgical proficiency increases. Although specific numeric values differ by study, the general trend is consistent.[17] In one large analysis, the mean operative time decreased over a series of 1,600 arthroscopic repairs, with early cases averaging around 35 min and later cases ~20 min after substantial experience. This suggests a progressive learning curve in operative efficiency as cumulative experience increases.[8]

Complication rate and safety outcomes

For knee arthroscopy, detailed published data on experience-specific complication rates are limited, but improved technical skill in simulator and training contexts likely correlates with fewer procedural misadventures and improved intraoperative judgment.[17] In shoulder arthroscopy, complications such as stiffness or residual pain tend to become less frequent with increasing surgeon experience.[14] Hip arthroscopy learning curve studies indicate that portal-related complications are more frequent among early cases and decline with experience, reflecting improved technique and familiarity with complex three-dimensional anatomy. Surgeons with higher cumulative experience achieve better tissue handling, reduced inadvertent damage, and fewer technical errors.[2]

Learning progression in arthroscopy may be conceptualized hierarchically. Initial improvements are typically observed in technical efficiency, reflected by reductions in operative time. This is followed by enhanced procedural safety, demonstrated by decreasing complication and reoperation rates. Structural success metrics, such as tendon integrity or labral preservation, improve thereafter, while optimization of patient-reported outcomes represents the most advanced stage of surgical proficiency. Therefore, operative time alone should not be equated with true surgical mastery.

Advantages of the tertiary care center for the new surgeon

Advanced instrumentation and technology

Modern arthroscopic towers, 4k visualization, and specialized hand tools (such as sophisticated suture passers, motorized shavers with specialized burs, and advanced radiofrequency probes) are commonly available at tertiary care centers. During the early learning curve, better visualization is directly correlated with less iatrogenic chondral damage.[18]

Consultant backup and the safety ceiling

The most important element in preserving a stable safety profile during the early period is the availability of senior consultant backup. Having a senior colleague on hand for “bail-out” maneuvers, such as managing a difficult femoral tunnel during anterior cruciate ligament reconstruction or passing a difficult suture in a constrained subacromial space, prevents minor technical issues from progressing into serious complications

Management of complex comorbidities

Surgeons can perform Procedures on “High Risk” patients (American Society of anesthesiologists classification [ASA]) III/IV) that would not be possible in an individual surgical center because a tertiary care center has intensive care units and round-the-clock anesthesia support. This enables the surgeon to work with a variety of patients at an early stage of their career.

Disadvantages

Higher complication rate

Higher complication or reoperation rates reported in tertiary centers may reflect referral bias and increased case complexity rather than surgeon inexperience alone.[19]

Elevated reoperations

This is mainly seen in high-volume centers, possibly due to referrals of tougher cases.[20]

Intense workload and physical strain

Tertiary centers, which demand long hours and prolonged standing, may increase the risk of musculoskeletal disorders.[21]

Future strategies to flatten the learning curve in tertiary care centers

Tertiary care centers play a key role in musculoskeletal training, patient volume, and specialized surgical education. To support early arthroscopy surgeons and reduce the steepness of learning curves (especially for hip, knee, and shoulder arthroscopy), the literature suggests several effective strategies – both educational and structural that can be adopted and optimized within tertiary care settings.

Structured simulation-based training

Simulation courses provide trainees with safe opportunities to practice arthroscopic skills without patient risk. These are especially valuable in tertiary centers where simulation laboratories and educator resources are available. This improves baseline proficiency before real surgical cases. Simulator-based instruction is supported by orthopedic training programs as a means to enhance visual-spatial skills, anatomic recognition, and operative efficiency, all of which contribute to flattening early learning curves.[22]

Cadaveric and procedural laboratories integrated with clinical mentorship

Cadaveric laboratories offer a bridge between simulation and actual surgery by allowing trainees to perform steps of procedures in realistic anatomic environments. With direct supervision from subspecialist faculty, trainees benefit from real-time guidance and iterative practice of surgical steps – a powerful component of flattening the learning curve in complex arthroscopic procedures.[23]

Objective performance monitoring and feedback

Using validated objective measures such as motion-tracking or structured assessment tools gives trainees actionable feedback which is essential for deliberate practice. In tertiary care settings, integrating skill tracking into the curriculum ensures trainees receive individualized feedback and can adjust their training based on measurable performance indicators. Examples include standardized performance scores or simulator-generated metrics that reflect efficiency and precision beyond simple case counts.[24]

Mentorship-focused case supervision

The presence of senior, experienced surgeons actively mentoring junior surgeons in the operating room has been shown to flatten learning curves dramatically. In studies of robotic-assisted knee arthroplasty, surgical teams working with an experienced surgeon demonstrated significantly faster improvements in operative times compared with teams without consistent expert assistance, highlighting the value of mentorship. This “co-teaching” or mentorship pairing model can be particularly impactful in tertiary care centers, where expert faculty can supervise initial procedures, reducing early errors and promoting safe progression.[25]

CONCLUSION

This scoping review highlights that arthroscopic learning curves vary substantially across the knee, shoulder, and hip, reflecting differences in anatomical complexity, portal access, and technical demands. Knee arthroscopy allows relatively rapid acquisition of basic competence, whereas shoulder and particularly hip arthroscopy require prolonged experience before consistent efficiency and safety are achieved. Across joints, increasing surgeon experience is associated with reduced operative time, lower complication rates, and improved procedural reliability. Importantly, the early learning phase can be safely navigated through structured mentorship, access to advanced instrumentation, and practice within tertiary care centers that provide supervisory support and adequate case volume. These findings underscore the need for competency-based training pathways and staged independence to optimize outcomes and protect patient safety in early arthroscopic practice.

Author contributions: VK: Conceptualized the article, final editing and approval of the article; AS: Literature review and wrote the article.

Declarations

Ethical approval:

Institutional Review Board approval is not required.

Declaration of patient consent:

The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient has given consent for clinical information to be reported in the journal. The patient understands that the patient’s names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Conflicts of interest:

There are no conflicts of interest.

Use of artificial intelligence (AI)-assisted technology for manuscript preparation:

The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.

Availability of data and materials:

All data generated or analyzed during this study are included in this article. No additional datasets were generated.

Financial support and sponsorship: Nil.

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