Lornoxicam 8mg tablets

BACKGROUND: Catheter-related bladder discomfort (CRBD is a painful complication of intraoperative urinary catheterization after anaesthesia. We conducted this study to compare the effect of tramadol and lornoxicam for the prevention of postoperative CRBD. METHODS: One-hundred twenty patients (aged 18-60 years, ASA physical status 1-2, undergoing elective uterine surgery requiring intraoperative urinary catheterization were randomly divided into three groups with 40 patients in each group. Group T received 1.5 mg/kg tramadol, group L received 8-mg lornoxicam, and group C received normal saline. The study drugs were administered intravenously at the end of the surgery. The incidence and severity of CRBD were reported at 0, 1, 2, and 6 h after arrival at the postanaesthesia care unit (PACU). RESULTS: The incidence of CRBD was significantly lower in groups T and L than in group C at 1, 2, and 6 h after surgery. The incidence of moderate to severe CRBD was also significantly lower in groups T and L than in group C at 0, 1, and 2 h after surgery. The severity of CRBD reported as mild, moderate, and severe was reduced in groups T and L compared with group C at most times after surgery. Group T had a higher incidence of nausea than group C, and there were no differences in dizziness, drowsiness, or vomit among the three groups. CONCLUSIONS: Tramadol and lornoxicam administered intravenously at the end of the surgery were both effective in preventing the incidence and severity of CRBD after uterine surgery. However, tramadol increased the incidence of nausea compared with saline, but there was no difference between tramadol and lornoxicam. TRIAL REGISTRATION: ChiCTR2100052003. Registered on 12/10/2021.

Abstract licence: CC BY

Abstract Osteoarthritis is a bone and joint condition characterized pathologically by articular cartilage degenerative damage and can develop into a devastating and permanently disabling disorder. This investigation aimed to formulate the anti-inflammatory drug lornoxicam (LOR) into bile salt–enriched vesicles loaded in an in situ forming hydrogel as a potential local treatment of osteoarthritis. This was achieved by formulating LOR-loaded bilosomes that are also loaded with superparamagnetic iron oxide nanoparticles (SPIONs) for intra-muscular (IM) administration to improve joint targeting and localization by applying an external magnet to the joint. A 3 1 .2 2 full factorial design was employed to develop the bilosomal dispersions and the optimized formula including SPION (LSB) was loaded into a thermosensitive hydrogel. Moreover, in vivo evaluation revealed that the IM administration of LSB combined with the application of an external magnet to the joint reversed carrageen-induced suppression in motor activity and osteoprotegerin by significantly reducing the elevations in mitogen-activated protein kinases, extracellular signal-regulated kinase, and receptor activator of nuclear factor kappa beta/osteoprotegerin expressions. In addition, the histopathological evaluation of knee joint tissues showed a remarkable improvement in the injured joint tissues. The results proved that the developed LSB could be a promising IM drug delivery system for osteoarthritis management. Graphical Abstract

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The present study aimed to evaluate the impact of ultrafine nanoemulsions on the transdermal delivery of lornoxicam (LOR) for management of the inflammation. The transdermal administration of LORNE could increase the efficacy of LOR with a reduction in side effects. Merging the beneficial properties of ultrafine nanoemulsions and their components (penetration enhancers) can lead to good solubilization, a small droplet size, and more effective LOR carriers. Therefore, this study aims to develop and evaluate the potential use of ultrafine nanoemulsions of LOR (LORNE) to elucidate their skin targeting for the treatment of inflammation. Based on solubility and pseudo ternary phase diagram tests, ultrafine LORNE composed of Labrafil M 2125 CS, Cremophor RH40, and Transcutol HP to deliver LOR was developed and characterized for its physicochemical properties, emulsification, and in vitro release. The selected LORNE was incorporated into carbopol gel (LORNE-Gel) and examined for ex vivo skin permeation, retention, dermatokinetics, anti-inflammatory efficacy, and skin irritation. The selected LORNE12-Gel could improve skin permeation, retention, and dermatokinetic results significantly (p < 0.05) with enhanced CSkin max and AUC0-48h compared to LOR-Gel. Moreover, LORNE12-Gel showed a remarkable anti-inflammatory effect compared to LOR-Gel after topical application. No signs of skin irritation were observed following treatment, indicating the safety of LORNE12-Gel. Thus, this study demonstrated that LOR-loaded LORNE12-Gel could be promising as an efficient transdermal nanocarrier for an anti-inflammatory alternative.

Abstract licence: CC BY-NC-ND

This paper investigates the application of Support Vector Regression with Quadratic Kernel (QSVR) for modeling the solubility of lornoxicam in supercritical carbon dioxide. The dataset comprises temperature (T) and pressure (P) as input variables, while the solubility (Y) of lornoxicam serves as the output variable entire the modeling. The temperature is measured in Kelvin (K), and the pressure is measured in bar as the inputs of models. To improve the predictive performance of the QSVR model, three distinct hyper-parameter optimization techniques, namely Genetic Algorithm (GA), Tabu Search (TS), and Bayesian Hyperparameter Optimization (BHO) are employed. These optimization methods are utilized to fine-tune the hyper-parameters of the QSVR model and enhance its predictive accuracy. The BHO-QSVR model achieved an impressive R2 score of 0.96725, indicating a strong fit between the predicted and actual solubility values. Additionally, it exhibited a Mean Absolute Error (MAE) of 1.75666E-05 and a maximum error of 3.02849E-05. Comparatively, the GA-QSVR and TS-QSVR models also performed well, achieving R2 scores of 0.95346 and 0.95882, respectively. The GA-QSVR model achieved an MAE of 1.56725E-05 and a maximum error of 4.92382E-05, while the TS-QSVR model exhibited an MAE of 1.84075E-05 and a maximum error of 5.02443E-05.

Abstract licence: CC BY-NC-ND