Nanocarbon or indocyanine green: Which is superior for gasless transaxillary endoscopic thyroidectomy to protect the parathyroid gland?
[BACKGROUND] Damage to the parathyroid glands remains a frequent complication after thyroidectomy, often resulting in hypoparathyroidism.
APA
Ye Z, Wu K, et al. (2022). Nanocarbon or indocyanine green: Which is superior for gasless transaxillary endoscopic thyroidectomy to protect the parathyroid gland?. Frontiers in surgery, 9, 1035840. https://doi.org/10.3389/fsurg.2022.1035840
MLA
Ye Z, et al.. "Nanocarbon or indocyanine green: Which is superior for gasless transaxillary endoscopic thyroidectomy to protect the parathyroid gland?." Frontiers in surgery, vol. 9, 2022, pp. 1035840.
PMID
36439530
Abstract
[BACKGROUND] Damage to the parathyroid glands remains a frequent complication after thyroidectomy, often resulting in hypoparathyroidism. Accordingly, identifying the parathyroid glands during thyroid surgical procedures is indispensable to prevent accidental surgical removal.
[METHODS] The participants were randomly divided into three groups (indocyanine green [ICG], nanocarbon [NC], and control group). To identify and protect parathyroid glands during neck lymph node dissection in patients with thyroid cancer, IG was intravenously administered to the ICG group, whereas the NC group received an intra-thyroid injection of the NC suspension before dissection. IG was intravenously administered to each group after dissection. Subsequently, we analyzed surgical outcomes, including operative time, number of lymph nodes, serum calcium, and number of parathyroid glands.
[RESULTS] We included 30 patients who underwent gasless transaxillary endoscopic thyroidectomy for thyroid cancer. Based on our findings, a greater number of parathyroid glands (< 0.01) and higher postoperative parathyroid hormone (PTH) levels were detected in the NC and ICG groups than those in the control group ( < 0.01). The number of parathyroid glands and postoperative PTH levels in the NC group were higher than those in the ICG group (< 0.01).
[CONCLUSIONS] Gasless transaxillary endoscopic thyroidectomy with NC and ICG for thyroid cancer could effectively protect the parathyroid gland and afford satisfactory clinical efficacy. NC could offer an advantage over ICG for protecting the parathyroid gland.
[METHODS] The participants were randomly divided into three groups (indocyanine green [ICG], nanocarbon [NC], and control group). To identify and protect parathyroid glands during neck lymph node dissection in patients with thyroid cancer, IG was intravenously administered to the ICG group, whereas the NC group received an intra-thyroid injection of the NC suspension before dissection. IG was intravenously administered to each group after dissection. Subsequently, we analyzed surgical outcomes, including operative time, number of lymph nodes, serum calcium, and number of parathyroid glands.
[RESULTS] We included 30 patients who underwent gasless transaxillary endoscopic thyroidectomy for thyroid cancer. Based on our findings, a greater number of parathyroid glands (< 0.01) and higher postoperative parathyroid hormone (PTH) levels were detected in the NC and ICG groups than those in the control group ( < 0.01). The number of parathyroid glands and postoperative PTH levels in the NC group were higher than those in the ICG group (< 0.01).
[CONCLUSIONS] Gasless transaxillary endoscopic thyroidectomy with NC and ICG for thyroid cancer could effectively protect the parathyroid gland and afford satisfactory clinical efficacy. NC could offer an advantage over ICG for protecting the parathyroid gland.
같은 제1저자의 인용 많은 논문 (5)
- Decoding the mitochondrial metabolic engine for tumor metastasis and clinical therapeutic opportunities.
- Single-Cell Transcriptomic Landscape of Right-Sided Colon Cancer Reveals Cellular and Molecular Features of Metastatic Potential.
- Nanomedicine strategies for disulfidptosis activation in SLC7A11-high tumors.
- Genome-wide analysis highlights epigenetic link to age at menarche.
- HAMIL: Hierarchical Attention Multi-Instance Learning for Label-Free Colorectal Cancer Typing.