BACKGROUND As the use of injectable skin fillers increase in popularity, an increase in the reported adverse events is expected. OBJECTIVE This systematic review supports the development of American Society for Dermatologic Surgery practice guideline on the management of adverse events of skin fillers. METHODS AND MATERIALS Several databases for studies on risk factors or treatments of injection-related visual compromise (IRVC), skin necrosis, inflammatory events, and nodules were searched. Meta-analysis was conducted when feasible. RESULTS The review included 182 studies. However, IRVC was very rare (1–2/1,000,000 patients) but had poor prognosis with improvement in 19% of cases. Skin necrosis was more common (approximately 5/1,000) with better prognosis (up to 77% of cases showing improvement). Treatments of IRVC and skin necrosis primarily depend on hyaluronidase injections. Risk of skin necrosis, inflammatory events, and nodules may be lower with certain fillers, brands, injection techniques, and volume. Treatment of inflammatory events and nodules with antibiotics, corticosteroids, 5-FU, and hyaluronidase was associated with high response rate (75%–80%). Most of the studies were small and noncomparative, making the evidence certainty very low. CONCLUSION Practitioners must have adequate knowledge of anatomy, elicit history of skin filler use, and establish preemptive protocols that prepare the clinical practice to manage complications.

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OBJECTIVE Awake transforaminal lumbar interbody fusion (TLIF) is a novel technique for performing spinal fusions in patients under conscious sedation. Whether awake TLIF can reduce operative times and decrease the hospital length of stay (LOS) remains to be shown. In this study, the authors sought to assess the differences in clinical outcomes between patients who underwent awake TLIF and those who underwent TLIF under general anesthesia by using institutional experience at the Mayo Clinic and the National Surgical Quality Improvement Program (NSQIP) database. METHODS Chart review was performed for a consecutive series of patients who underwent single-level minimally invasive surgery (MIS)–TLIF performed by a single surgeon (K.A.I.) at a single institution. Additionally, the NSQIP database was queried from 2016 to 2019 for patients who underwent awake TLIF as well as propensity score–matched patients who underwent TLIF under general anesthesia. RESULTS A total of 20 patients at Mayo Clinic underwent awake single-level MIS-TLIF. The mean operative time was 122 ± 16.68 minutes, and the mean estimated blood loss was 39 ± 30.24 ml. No intraoperative complications were reported. A total of 96 patients who underwent TLIF (24 awake and 72 under general anesthesia) were analyzed from the NSQIP database. The mean LOS was less in the awake cohort (1.4 ± 1.381 days) than the general anesthesia cohort (3 ± 2.274 days) (p = 0.002). CONCLUSIONS Evidence from the authors’ institutional experience and national analysis has demonstrated that awake MIS-TLIF is efficient and can reduce hospital LOS.

Study Design Comparative Analysis and Narrative Review. Objective To assess and compare ChatGPT’s responses to the clinical questions and recommendations proposed by The 2011 North American Spine Society (NASS) Clinical Guideline for the Diagnosis and Treatment of Degenerative Lumbar Spinal Stenosis (LSS). We explore the advantages and disadvantages of ChatGPT’s responses through an updated literature review on spinal stenosis. Methods We prompted ChatGPT with questions from the NASS Evidence-based Clinical Guidelines for LSS and compared its generated responses with the recommendations provided by the guidelines. A review of the literature was performed via PubMed, OVID, and Cochrane on the diagnosis and treatment of lumbar spinal stenosis between January 2012 and April 2023. Results 14 questions proposed by the NASS guidelines for LSS were uploaded into ChatGPT and directly compared to the responses offered by NASS. Three questions were on the definition and history of LSS, one on diagnostic tests, seven on non-surgical interventions and three on surgical interventions. The review process found 40 articles that were selected for inclusion that helped corroborate or contradict the responses that were generated by ChatGPT. Conclusions ChatGPT’s responses were similar to findings in the current literature on LSS. These results demonstrate the potential for implementing ChatGPT into the spine surgeon’s workplace as a means of supporting the decision-making process for LSS diagnosis and treatment. However, our narrative summary only provides a limited literature review and additional research is needed to standardize our findings as means of validating ChatGPT’s use in the clinical space.