Background A positive culture of non-tuberculous mycobacteria (NTM) is a key diagnostic criterion for NTM disease. Due to the slow growth rate of NTM, the turnaround time (TAT) for culture specimens is often lengthy, posing significant challenges for the diagnosis and treatment of related diseases. This study aimed to explore factors influencing TAT in NTM culture testing, assess its potential clinical value, and identify ways to expedite clinical decision-making. Methods NTM identified by HSP65 sequencing in a tertiary hospital from June 2022 to May 2024 were retrospectively included, and patients’ data were collected. TAT was defined as the time between specimen receipt and report issuance. Differences in TAT between groups were analyzed using the rank-sum test. Correlations were evaluated using Spearman’s correlation analysis, and a generalized linear model was applied to identify independent factors influencing TAT. Results A total of 289 NTM strains were finally enrolled in this study, including rapidly growing mycobacteria (RGM, n = 22) and slow-growing mycobacteria (SGM, n = 267). The median TAT for RGM was 7 days, while the median TAT for SGM was 11 days, indicating a statistically significant difference ( p 0.001). Representative species within RGM and SGM also showed significant TAT discrepancies. Patients with NTM pulmonary disease, bronchiectasis, or cavitation had shorter median TATs (8–9 days) than those without such findings ( p 0.05). TAT showed a negative correlation with acid-fast bacilli smear grades (correlation coefficient: −0.490, p 0.001), and the acid-fast bacilli smear result was confirmed as the only determinant of TAT in the final regression model (Wald χ 2 = 39.71, p 0.001). Conclusion TAT for NTM culture was significantly influenced by species category, with RGM showing shorter TATs than SGM. Variations in TAT were observed among different species within the same complex. Additionally, TAT was associated with clinical diagnoses and imaging findings. The acid-fast bacilli smear result was the only independent factor affecting TAT, which could help to guide clinical workflow optimization.
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