Advertisement for orthosearch.org.uk
Results 1 - 2 of 2
Results per page:
Bone & Joint Open
Vol. 3, Issue 8 | Pages 607 - 610
1 Aug 2022
Wellington IJ Hawthorne BC Dorsey C Connors JP Mazzocca AD Solovyova O

Aims

Tissue adhesives (TAs) are a commonly used adjunct to traditional surgical wound closures. However, TAs must be allowed to dry before application of a surgical dressing, increasing operating time and reducing intraoperative efficiency. The goal of this study is to identify a practical method for decreasing the curing time for TAs.

Methods

Six techniques were tested to determine which one resulted in the quickest drying time for 2-octyle cyanoacrylate (Dermabond) skin adhesive. These were nothing (control), fanning with a hand (Fanning), covering with a hand (Covering), bringing operating room lights close (OR Lights), ultraviolet lights (UV Light), or prewarming the TA applicator in a hot water bath (Hot Water Bath). Equal amounts of TA were applied to a reproducible plexiglass surface and allowed to dry while undergoing one of the six techniques. The time to complete dryness was recorded for ten specimens for each of the six techniques.


Bone & Joint Open
Vol. 1, Issue 6 | Pages 175 - 181
2 Jun 2020
Musowoya RM Kaonga P Bwanga A Chunda-Lyoka C Lavy C Munthali J

Aims

Sickle cell disease (SCD) is an autosomal recessive inherited condition that presents with a number of clinical manifestations that include musculoskeletal manifestations (MM). MM may present differently in different individuals and settings and the predictors are not well known. Herein, we aimed at determining the predictors of MM in patients with SCD at the University Teaching Hospital, Lusaka, Zambia.

Methods

An unmatched case-control study was conducted between January and May 2019 in children below the age of 16 years. In all, 57 cases and 114 controls were obtained by systematic sampling method. A structured questionnaire was used to collect data. The different MM were identified, staged, and classified according to the Standard Orthopaedic Classification Systems using radiological and laboratory investigations. The data was entered in Epidata version 3.1 and exported to STATA 15 for analysis. Multiple logistic regression was used to determine predictors and predictive margins were used to determine the probability of MM.