Frozen section is a recognised technique to assist in the diagnosis of infection and there are standards for reporting. Our aim of this review was to assess the value of frozen section in the diagnosis of infection, as well as other variables. We performed a retrospective review of all frozen sections for suspected infection in 2016. Patient demographics, histological and microbiological investigations, laboratory and bedside tests were recorded and analysed using statistical software. 46 patients had 55 frozen sections; the majority were for lower limb arthroplasty. No sections were reported as polymorphonuclear neutrophils per high-power field. Three sections showed signs of infection and one without evidence had positive cultures. One uncertain section did not grow organisms. 10 patients had two-stage procedures, four of these were intended to be determined by frozen section but only two had evidence of infection on analysis. Evidence of infection on frozen section does correlate with microbiological growth but does not relate to intention to stage procedures in half of patients. The effect of new tests such as Synovasure is highlighted by this review. Frozen section analysis is reported subjectively but is a good predictor of infection. Clinical assessment is accurate in diagnosing infection. Histological, microbiological and additional investigations should be considered in relation to their cost-effectiveness.
Plots are an elegant and effective way to represent
data. At their best they encourage the reader and promote comprehension.
A graphical representation can give a far more intuitive feel to
the pattern of results in the study than a list of numerical data,
or the result of a statistical calculation. The temptation to exaggerate differences or relationships between
variables by using broken axes, overlaid axes, or inconsistent scaling
between plots should be avoided. A plot should be self-explanatory and not complicated. It should
make good use of the available space. The axes should be scaled
appropriately and labelled with an appropriate dimension. Plots are recognised statistical methods of presenting data and
usually require specialised statistical software to create them.
The statistical analysis and methods to generate the plots are as
important as the methodology of the study itself. The software,
including dates and version numbers, as well as statistical tests
should be appropriately referenced. Following some of the guidance provided in this article will
enhance a manuscript. Cite this article:
