Microfracture has historically been considered an acceptable method for treating cartilage defects. A substantial body of literature on this technique has accumulated over the past few decades. Citation metrics serve as a critical tool for assessing scholarly impact and prompting scientific developments. The aim of this study was to analyze the top 100 most‐cited articles in this field.

Accessible articles published from inception to 2023 were extracted from the Web of Science Core Collection database. The top 100 publications were identified and analyzed in terms of citation count, year of publication, authorship, citation density (citations per article age), journal, impact factor, geographic origin, evidence level, study design, and institutional affiliation.

Citation counts for the included articles ranged from 945 to 51, with citation densities between 49.7 and 2.9. Publication years spanned from 1999 to 2019. Randomized controlled trials were the most common study design, while Level Ⅳ represented the most frequent evidence level. “Autologous chondrocyte implantation,” “osteochondral autograft transplantation,” and “arthroscopic treatment” have emerged as current focal points in the field.

This study provides a comprehensive analysis of the top 100 most‐cited articles on microfracture. Compared with prior bibliometric studies in orthopedics, influential articles on microfracture showed a higher proportion of Level Ⅰ and Ⅱ evidence. These findings offer valuable insights into the development of microfracture research and may help clinicians efficiently identify the foundational literature in the field.

Traditional bibliometrics have been used to estimate the scientific impact of research across various fields. However, citation analysis is not without limitations. With the rapid development of social media, the Altmetric score has become popular for evaluating scientific work. This study aimed to determine whether the Altmetric score could replace traditional bibliometrics for assessing influential papers in pediatric robotic surgery.

The Web of Science database was searched for the 50 top‐cited publications in pediatric robotic surgery, and the characteristics of each article were recorded and identified. Conventional bibliometric variables included the citation count and impact factor (IF) of the publishing journal. The Altmetric score database was used to identify the Altmetric score and details for each article. Statistical analysis, including Spearman's correlation coefficients, was performed using Microsoft Excel and GraphPad PRISM.

The top 50 publications with the most citations were obtained and analyzed. A significant negative relationship was identified between the impact index and the Altmetric score (r = −0.42, p < 0.01, R² = 0.18), and no correlations were observed for the number of citations (r = −0.12, p = 0.40, R² = 0.01) and IF (r = −0.09, p = 0.53, R² = 0.01). X/Twitter (68%) was the most popular social media source for Altmetric score details.

This study did not identify a statistically significant correlation between Altmetric scores and conventional bibliometric variables in the 50 top‐cited publications. Furthermore, the Altmetric score is susceptible to manipulation because its calculation mechanism is unknown. Thus, the Altmetric score does not currently deliver an alternative approach to traditional bibliometrics. A combination of traditional bibliometrics and the Altmetric score can provide a more comprehensive method for evaluating influential articles in pediatric robotic surgery.