BACKGROUND Cranioplasty is a ubiquitous neurosurgical procedure consisting of reconstruction of a pre-existing calvarial defect. Many materials are available, including polymethylmethacrylate in hand-moulded (hPMMA) and prefabricated (pPMMA) form, hydroxyapatite (HA), polyetheretherketone (PEEK) and titanium (Ti). OBJECTIVE To perform a network meta-analysis (NMA) to assess the relationship between materials and complications of cranioplasty. METHODS PubMed/MEDLINE, Google Scholar, EMBASE, Scopus, and The Cochrane Library were searched from January 1, 1990 to February 14, 2021. Studies detailing rates of any of infections, implant exposure, or revision surgery were included. A frequentist NMA was performed for each complication. Risk ratios (RRs) with 95% CIs were calculated for each material pair. RESULTS A total of 3620 abstracts were screened and 31 full papers were included. Surgical revision was reported in 18 studies and occurred in 316/2032 cases (14%; 95% CI 11-17). PEEK had the lowest risk of re-operation with a rate of 8/157 (5%; 95% CI 0-11) in 5 studies, superior to autografts (RR 0.20; 95% CI 0.07-0.57), hPMMA (RR 0.20; 95% CI 0.07-0.60), Ti (RR 0.39; 95% CI 0.17-0.92), and pPMMA (RR 0.14; 95% CI 0.04-0.51). Revision rate was 131/684 (19%; 95% CI 13-25; 10 studies) in autografts, 61/317 (18%; 95%CI 9-28; 7 studies) in hPMMA, 84/599 (13%; 95% CI 7-19; 11 studies) in Ti, 7/59 (9%; 95% CI 1-23; 3 studies) in pPMMA, and 25/216 (12%; 95% CI 4-24; 4 studies) in HA. Infection occurred in 463/4667 (8%; 95% CI 6-11) and implant exposure in 120/1651 (6%; 95% CI 4-9). CONCLUSION PEEK appears to have the lowest risk of cranioplasty revision, but further research is required to determine the optimal material.

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Biomarkers such as calcium channel binding protein S100 subunit beta (S100B), glial fibrillary acidic protein (GFAP), ubiquitin c-terminal hydrolase L1 (UCH-L1) and neuron-specific enolase (NSE) have been proposed to aid in screening patients presenting with mild traumatic brain injury (mTBI). As such, we aimed to characterise their accuracy at various thresholds. MEDLINE, SCOPUS and EMBASE were searched, and articles reporting the diagnostic performance of included biomarkers were eligible for inclusion. Risk of bias was assessed using the QUADAS-II criteria. A meta-analysis was performed to assess the predictive value of biomarkers for imaging abnormalities on CT. A total of 2939 citations were identified, and 38 studies were included. Thirty-two studies reported data for S100B. At its conventional threshold of 0.1 μg/L, S100B had a pooled sensitivity of 91% (95%CI 87-94) and a specificity of 30% (95%CI 26-34). The optimal threshold for S100B was 0.72 μg/L, with a sensitivity of 61% (95% CI 50-72) and a specificity of 69% (95% CI 64-74). Nine studies reported data for GFAP. The optimal threshold for GFAP was 626 pg/mL, at which the sensitivity was 71% (95%CI 41-91) and specificity was 71% (95%CI 43-90). Sensitivity of GFAP was maximised at a threshold of 22 pg/mL, which had a sensitivity of 93% (95%CI 73-99) and a specificity of 36% (95%CI 12-68%). Three studies reported data for NSE and two studies for UCH-L1, which precluded meta-analysis. There is evidence to support the use of S100B as a screening tool in mild TBI, and potential advantages to the use of GFAP, which requires further investigation.