Three-dimensional (3D) printing has become more frequently used in surgical specialties in recent years. Orthopaedic surgery is particularly well-suited to 3D printing applications, and thus has seen a variety of uses for this technology. These uses include pre-operative planning, patient-specific instrumentation (PSI), and patient-specific implant production. As with any new technology, it is important to assess the clinical impact, if any, of three-dimensional printing. The purpose of this review was to answer the following questions:
What are the current clinical uses of 3D printing in orthopaedic surgery? Does the use of 3D printing have an effect on peri-operative outcomes? Four electronic databases (Embase, MEDLINE, PubMed, Web of Science) were searched for Articles discussing clinical applications of 3D printing in orthopaedics up to November 13, 2018. Titles, abstracts, and full texts were screened in duplicate and data was abstracted. Descriptive analysis was performed for all studies. A meta-analysis was performed among eligible studies to compare estimated blood loss (EBL), operative time, and fluoroscopy use between 3D printing cases and controls. Study quality was assessed using the Methodological Index for Non-Randomized Studies (MINORS) criteria for non-randomized studies and the Cochrane Risk of Bias Tool for randomized controlled trials (RCTs). This review was prospectively registered on PROSPERO (Registration ID: CRD42018099144). One-hundred and eight studies were included, published between 2012 and 2018. A total of 2328 patients were included in these studies, and 1558 patients were treated using 3D printing technology. The mean age of patients, where reported, was 47 years old (range 3 to 90). Three-dimensional printing was most commonly reported in trauma (N = 41) and oncology (N = 22). Pre-operative planning was the most common use of 3D printing (N = 63), followed by final implants (N = 32) and PSI (N = 22). Titanium was the most commonly used 3D printing material (16 studies, 27.1%). A wide range of costs were reported for 3D printing applications, ranging from “less than $10” to $20,000. The mean MINORS score for non-randomized studies was 8.3/16 for non-comparative studies (N = 78), and 17.7/24 for non-randomized comparative studies (N = 19). Among RCTs, the most commonly identified sources of bias were for performance and detection biases. Three-dimensional printing resulted in a statistically significant decrease in mean operative time (−15.6 mins, p < .00001), mean EBL (−35.9 mL, p<.00001), and mean fluoroscopy shots (−3.5 shots, p < .00001) in 3D printing patients compared to controls. The uses of 3D printing in orthopaedic surgery are growing rapidly, with its use being most common in trauma and oncology. Pre-operative planning is the most common use of 3D printing in orthopaedics. The use of 3D printing significantly reduces EBL, operative time, and fluoroscopy use compared to controls. Future research is needed to confirm and clarify the magnitude of these effects.
Since the recall of some metal on metal (MoM) THR bearings, surgeons have seen patients with pain, elevated Co and Cr levels and adverse local tissue reactions (ALTR). While many variables may contribute to THR MoM failures, many times these variables are not present in patients who present with symptoms. We investigate the possible genetic predilection of a group of patients who were revised after MoM THR surgery for pain, high Co/Cr levels and ALTR. IRB approval was obtained prior to our study. We have analyzed 19 control (asymptomatic MoM THR patients > 6 years after surgery) and 19 disease (revised MoM THR for high metal ions and ALTR). The 38 sample intensity files were subject to sample Quality Control (QC) using Contrast QC (< 0.4) with an Affymetrix Genotyping Console. The resulting 38 sample files with genotype calls were loaded and further analyzed using the Association Workflow in Partek Genomics Suite 6.6 (Partek, Missouri). Hardy-Weinberg equilibrium test was performed on the single nucleotide polymorphism (SNP) level. The difference between the observed and expected frequencies of each allele at each locus were tested by Fisher's exact test and χ2 test. To get the working SNP list, two filters were used: (1) a SNP no-call rate should be less than 5%, and (2) minor allele frequency of a SNP should be greater than 5%. After filtering, association analysis of the SNPS with disease was done using Chi2 Test. In this study, χ2 statistic was used to assess the difference in allele frequencies between the control and disease samples. The value of χ2 statistic, degrees of freedom, and the associated p-value for each SNP were calculated. Dot Plot was used to visualize the genotypes of all samples. To measure the non-random association of alleles at different loci, Linkage Disequilibrium analysis was performed using the neighborhood size of 20 and statistic r2. The resulting correlations show the value of r2 for SNPs. The r2 = 1 means that two SNPs are tightly associated.INTRODUCTION
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