Cutaneous Nontuberculous Mycobacteria Infections Following Cosmetic Procedures: A Retrospective Study
Bibliographic record
Abstract
Rui Zeng,1,2,* Jingshu Xiong,1– 3,* Wei Gao,4 Jiayi Peng,1,2 Ying Shi,1– 3 Wenyue Zhang,1– 3 Haiqin Jiang,1– 3 Chaojiang Cheng,1,2 Gai Ge,5 Zhenzhen Wang,1,2 Youming Mei,1– 3 Zhiming Chen,6 Hongsheng Wang1– 3,7 1Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, People’s Republic of China; 2Department of Mycobacterium, Jiangsu Key Laboratory of Molecular Biology for Skin Diseases and STIs, Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, People’s Republic of China; 3National Center for Sexually Transmitted Disease and Leprosy Control, China Centers for Disease Control and Prevention, Nanjing, People’s Republic of China; 4Department of Dermatology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, People’s Republic of China; 5Department of Dermatology, Wuhan No 1 hospital, Wuhan, Hubei, People’s Republic of China; 6Genetic Skin Disease Center, Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, People’s Republic of China; 7Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hongsheng Wang, Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, 12 Jiangwangmiao St, Nanjing, Jiangsu, 210042, People’s Republic of China, Email whs33@vip.sina.comBackground: Reports of skin infections associated with nontuberculous mycobacteria (NTM) following cosmetic procedures are increasing. The diagnosis and treatment of these infections remain a significant challenge for clinicians.Objective: We examined the clinical characteristics, microbiology, histopathology, and treatment strategies of NTM infections following cosmetic procedures, including botulinum toxin injection, lipolysis injection, hyaluronic acid injection, mesotherapy, autologous fat grafting, and other related procedures.Methods: This retrospective study of cosmetology-related cutaneous NTM infections diagnosed based on culture or molecular identification was conducted at a tertiary dermatology hospital in China. Demographic, clinical, microbiological, pathological biopsy, management, and outcome data were also collected.Results: The series enrolled 28 patients, four diagnosed by molecular identification and histology, and 24 by positive culture. All 24 NTM cultures were rapid-growing mycobacteria, mainly Mycobacterium abscessus complex (75%), with a mean time to positive culture of 11.8 days. The mean incubation period for the lesions was three weeks, while the mean time to diagnosis was 9.8 weeks. Treatment typically requires long-term, multi-drug therapy. Surgical intervention may shorten the disease course.Conclusion: Cosmetology-related cutaneous NTM infections are frequently underrecognized and challenging to diagnose, leading to delayed treatment. We aimed to enhance clinician awareness of NTM infections to facilitate early detection and prompt treatment. Empirical therapy with clarithromycin and moxifloxacin may be considered in the absence of susceptibility results, but treatment decisions should be carefully guided by susceptibility testing results. Surgical intervention may be beneficial, and tigecycline is a viable option when resistant to clarithromycin.Keywords: nontuberculous mycobacteria, rapidly growing mycobacteria, skin, infections, cosmetic procedures, treatment
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".