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Purpose: To assess the effect of different intensity standardisation techniques (ISTs) and ComBat batch sizes on radiomics survival model performance and stability in a heterogenous, multi-centre cohort of patients with glioblastoma (GBM)., Methods: Multi-centre pre-operative MRI acquired between 2014 and 2020 in patients with IDH-wildtype unifocal WHO grade 4 GBM were retrospectively evaluated. WhiteStripe (WS), Nyul histogram matching (HM), and Z-score (ZS) ISTs were applied before radiomic feature (RF) extraction. RFs were realigned using ComBat and minimum batch size (MBS) of 5, 10, or 15 patients. Cox proportional hazards models for overall survival (OS) prediction were produced using five different selection strategies and the impact of IST and MBS was evaluated using bootstrapping. Calibration, discrimination, relative explained variation, and model fit were assessed. Instability was evaluated using 95% confidence intervals (95% CIs), feature selection frequency and calibration curves across the bootstrap resamples., Results: One hundred ninety-five patients were included. Median OS = 13 (95% CI: 12-14) months. Twelve to fourteen unique MRI protocols were used per MRI sequence. HM and WS produced the highest relative increase in model discrimination, explained variation and model fit but IST choice did not greatly impact on stability, nor calibration. Larger ComBat batches improved discrimination, model fit, and explained variation but higher MBS (reduced sample size) reduced stability (across all performance metrics) and reduced calibration accuracy., Conclusion: Heterogenous, real-world GBM data poses a challenge to the reproducibility of radiomics. ComBat generally improved model performance as MBS increased but reduced stability and calibration. HM and WS tended to improve model performance., Key Points: Question ComBat harmonisation of RFs and intensity standardisation of MRI have not been thoroughly evaluated in multicentre, heterogeneous GBM data. Findings The addition of ComBat and ISTs can improve discrimination, relative model fit, and explained variance but degrades the calibration and stability of survival models. Clinical relevance Radiomics risk prediction models in real-world, multicentre contexts could be improved by ComBat and ISTs, however, this degrades calibration and prediction stability and this must be thoroughly investigated before patients can be accurately separated into different risk groups., Competing Interests: Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is Stuart Currie. Conflict of interest: A.F.S. is a member of the Scientific Editorial Board (section: nuclear medicine and molecular imaging) of European Radiology. They have not taken part in the review or selection processes of this article. The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. Statistics and biometry: One of the authors has significant statistical expertise. H.M. is a career statistician. Informed consent: Written informed consent was waived by the Institutional Review Board due to the retrospective nature of the study. Ethical approval: Institutional Review Board approval was obtained. Ethical approval and institutional data access were approved via the local ethical review committee (REC ref: 19/YH/0300, IRAS project ID: 255585). Study subjects or cohorts overlap: Some study subjects have been previously reported in: Currie et al [36]. Imaging spectrum of the developing glioblastoma: a cross-sectional observation study. Current Oncology. 30(7):6682–6698. Fatania et al [19]. The current study focuses on radiomics modelling, intensity standardisation of MRI, and radiomic feature realignment with ComBat. None of these were investigated in the above publications. Methodology: Retrospective Observational Performed at multiple institutions, (© 2024. The Author(s).)

Background: The aim was to predict survival of glioblastoma at 8 months after radiotherapy (a period allowing for completing a typical course of adjuvant temozolomide), by applying deep learning to the first brain MRI after radiotherapy completion., Methods: Retrospective and prospective data were collected from 206 consecutive glioblastoma, isocitrate dehydrogenase -wildtype patients diagnosed between March 2014 and February 2022 across 11 UK centers. Models were trained on 158 retrospective patients from 3 centers. Holdout test sets were retrospective (n = 19; internal validation), and prospective (n = 29; external validation from 8 distinct centers). Neural network branches for T2-weighted and contrast-enhanced T1-weighted inputs were concatenated to predict survival. A nonimaging branch (demographics/MGMT/treatment data) was also combined with the imaging model. We investigated the influence of individual MR sequences; nonimaging features; and weighted dense blocks pretrained for abnormality detection., Results: The imaging model outperformed the nonimaging model in all test sets (area under the receiver-operating characteristic curve, AUC P = .038) and performed similarly to a combined imaging/nonimaging model (P > .05). Imaging, nonimaging, and combined models applied to amalgamated test sets gave AUCs of 0.93, 0.79, and 0.91. Initializing the imaging model with pretrained weights from 10 000s of brain MRIs improved performance considerably (amalgamated test sets without pretraining 0.64; P = .003)., Conclusions: A deep learning model using MRI images after radiotherapy reliably and accurately determined survival of glioblastoma. The model serves as a prognostic biomarker identifying patients who will not survive beyond a typical course of adjuvant temozolomide, thereby stratifying patients into those who might require early second-line or clinical trial treatment., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Published models inconsistently associate glioblastoma size with overall survival (OS). This study aimed to investigate the prognostic effect of tumour size in a large cohort of patients diagnosed with GBM and interrogate how sample size and non-linear transformations may impact on the likelihood of finding a prognostic effect. In total, 279 patients with a IDH-wildtype unifocal WHO grade 4 GBM between 2014 and 2020 from a retrospective cohort were included. Uni-/multivariable association between core volume, whole volume (CV and WV), and diameter with OS was assessed with (1) Cox proportional hazard models +/- log transformation and (2) resampling with 1,000,000 repetitions and varying sample size to identify the percentage of models, which showed a significant effect of tumour size. Models adjusted for operation type and a diameter model adjusted for all clinical variables remained significant ( p = 0.03). Multivariable resampling increased the significant effects ( p < 0.05) of all size variables as sample size increased. Log transformation also had a large effect on the chances of a prognostic effect of WV. For models adjusted for operation type, 19.5% of WV vs. 26.3% log-WV ( n = 50) and 69.9% WV and 89.9% log-WV ( n = 279) were significant. In this large well-curated cohort, multivariable modelling and resampling suggest tumour volume is prognostic at larger sample sizes and with log transformation for WV.

Glioblastoma (GBM) has the typical radiological appearance (TRA) of a centrally necrotic, peripherally enhancing tumor with surrounding edema. The objective of this study was to determine whether the developing GBM displays a spectrum of imaging changes detectable on routine clinical imaging prior to TRA GBM. Patients with pre-operative imaging diagnosed with GBM (1 January 2014-31 March 2022) were identified from a neuroscience center. The imaging was reviewed by an experienced neuroradiologist. Imaging patterns preceding TRA GBM were analyzed. A total of 76 out of 555 (14%) patients had imaging preceding TRA GBM, 57 had solitary lesions, and 19 had multiple lesions (total = 84 lesions). Here, 83% of the lesions had cortical or cortical/subcortical locations. The earliest imaging features for 84 lesions were T2 hyperintensity/CT low density ( n = 18), CT hyperdensity ( n = 51), and T2 iso-intensity ( n = 15). Lesions initially showing T2 hyperintensity/CT low density later showed T2 iso-intensity. When CT and MRI were available, all CT hyperdense lesions showed T2 iso-intensity, reduced diffusivity, and the following enhancement patterns: nodular 35%, solid 29%, none 26%, and patchy peripheral 10%. The mean time to develop TRA GBM from T2 hyperintensity was 140 days and from CT hyperdensity was 69 days. This research suggests that the developing GBM shows a spectrum of imaging features, progressing through T2 hyperintensity to CT hyperdensity, T2 iso-intensity, reduced diffusivity, and variable enhancement to TRA GBM. Red flags for non-TRA GBM lesions are cortical/subcortical CT hyperdense/T2 iso-intense/low ADC. Future research correlating this imaging spectrum with pathophysiology may provide insight into GBM growth patterns.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing., (© 2022. The Author(s).)

Objectives: Radiomics is a promising avenue in non-invasive characterisation of diffuse glioma. Clinical translation is hampered by lack of reproducibility across centres and difficulty in standardising image intensity in MRI datasets. The study aim was to perform a systematic review of different methods of MRI intensity standardisation prior to radiomic feature extraction., Methods: MEDLINE, EMBASE, and SCOPUS were searched for articles meeting the following eligibility criteria: MRI radiomic studies where one method of intensity normalisation was compared with another or no normalisation, and original research concerning patients diagnosed with diffuse gliomas. Using PRISMA criteria, data were extracted from short-listed studies including number of patients, MRI sequences, validation status, radiomics software, method of segmentation, and intensity standardisation. QUADAS-2 was used for quality appraisal., Results: After duplicate removal, 741 results were returned from database and reference searches and, from these, 12 papers were eligible. Due to a lack of common pre-processing and different analyses, a narrative synthesis was sought. Three different intensity standardisation techniques have been studied: histogram matching (5/12), limiting or rescaling signal intensity (8/12), and deep learning (1/12)-only two papers compared different methods. From these studies, histogram matching produced the more reliable features compared to other methods of altering MRI signal intensity., Conclusion: Multiple methods of intensity standardisation have been described in the literature without clear consensus. Further research that directly compares different methods of intensity standardisation on glioma MRI datasets is required., Key Points: • Intensity standardisation is a key pre-processing step in the development of robust radiomic signatures to evaluate diffuse glioma. • A minority of studies compared the impact of two or more methods. • Further research is required to directly compare multiple methods of MRI intensity standardisation on glioma datasets., (© 2022. The Author(s).)

Brain tumours are the biggest cancer killer in those under 40 and reduce life expectancy more than any other cancer. Blood-based liquid biopsies may aid early diagnosis, prediction and prognosis for brain tumours. It remains unclear whether known blood-based biomarkers, such as glial fibrillary acidic protein (GFAP), have the required sensitivity and selectivity. We have developed a novel in silico model which can be used to assess and compare blood-based liquid biopsies. We focused on GFAP, a putative biomarker for astrocytic tumours and glioblastoma multi-formes (GBMs). In silico modelling was paired with experimental measurement of cell GFAP concentrations and used to predict the tumour volumes and identify key parameters which limit detection. The average GBM volumes of 449 patients at Leeds Teaching Hospitals NHS Trust were also measured and used as a benchmark. Our model predicts that the currently proposed GFAP threshold of 0.12 ng ml -1 may not be suitable for early detection of GBMs, but that lower thresholds may be used. We found that the levels of GFAP in the blood are related to tumour characteristics, such as vasculature damage and rate of necrosis, which are biological markers of tumour aggressiveness. We also demonstrate how these models could be used to provide clinical insight.

Anti-1-amino-3- 18 fluorine-fluorocyclobutane-1-carboxylic acid ( 18 F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18 F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18 F-fluciclovine uptake, MRI findings, and tumour biology. 18 F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18 F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1-6) and grouped according to overall survival (OS)-short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18 F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18 F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18 F-fluciclovine uptake reflected biologically active tumour.

Background and Purpose: Magnetic Resonance Imaging (MRI) exhibits scanner dependent contrast, which limits generalisability of radiomics and machine-learning for radiation oncology. Current deep-learning harmonisation requires paired data, retraining for new scanners and often suffers from geometry-shift which alters anatomical information. The aim of this study was to investigate style-blind auto-encoders for MRI harmonisation to accommodate unpaired training data, avoid geometry-shift and harmonise data from previously unseen scanners., Materials and Methods: A style-blind auto-encoder, using adversarial classification on the latent-space, was designed for MRI harmonisation. The public CC359 T1-w MRI brain dataset includes six scanners (three manufacturers, two field strengths), of which five were used for training. MRI from all six (including one unseen) scanner were harmonised to common contrast. Harmonisation extent was quantified via Kolmogorov-Smirnov testing of residual scanner dependence of 3D radiomic features, and compared to WhiteStripe normalisation. Anatomical content preservation was measured through change in structural similarity index on contrast-cycling (δSSIM)., Results: The percentage of radiomics features showing statistically significant scanner-dependence was reduced from 41% (WhiteStripe) to 16% for white matter and from 39% to 27% for grey matter. δSSIM < 0.0025 on harmonisation and de-harmonisation indicated excellent anatomical content preservation., Conclusions: Our method harmonised MRI contrast effectively, preserved critical anatomical details at high fidelity, trained on unpaired data and allowed zero-shot harmonisation. Robust and clinically translatable harmonisation of MRI will enable generalisable radiomic and deep-learning models for a range of applications, including radiation oncology treatment stratification, planning and response monitoring., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

The International Subarachnoid Aneurysm Trial (ISAT) showed superiority for endovascular treatment of ruptured aneurysms and technology has since moved on rapidly. Many approaches and technology now exist for the endovascular management of ruptured and unruptured intracranial aneurysms, which reflects their varied nature - there is no one-size-fits-all technique. We aim to provide an overview of the various classes of device and the major developments over the past decade. Coiling is the oldest of the technology and continues to demonstrate high levels of occlusion and acceptable risks, making it the default treatment choice, particularly in the acutely ruptured aneurysm setting. Advances on coiling include the use of adjuncts such as balloons, stents and fully retrievable temporary neck-bridging devices, which have facilitated the treatment of more complex aneurysms. Flow divertors have also revolutionised complex aneurysm treatment with small added risk in acute aneurysm treatment and seek to remodel the aneurysm-vessel interface without accessing the aneurysm sac. The latest development and most promising avenue appears to be intrasaccular flow disrupting devices like WEB, Contour and Neqstent that provide excellent opportunities to treat wide neck complex aneurysm with minimal mortality and morbidity and good occlusion rates and may in future replace a significant number of stent-assisted coiling too.

Standard bolus-dosed antibiotic prophylaxis may not inhibit growth of antibiotic resistant colonic bacteria, a cause of SSIs after colorectal surgery. An alternative strategy is continuous administration of antibiotic throughout surgery, maintaining concentrations of antibiotics that inhibit growth of resistant bacteria. This study is a pilot comparing bolus-continuous infusion with bolus-dosed cefuroxime prophylaxis in colorectal surgery. This is a pilot randomised controlled trial in which participants received cefuroxime bolus-infusion (intervention arm) targeting free serum cefuroxime concentrations of 64 mg/L, or 1.5 g cefuroxime as a bolus dose four-hourly (standard arm). Patients in both arms received metronidazole (500 mg intravenously). Eligible participants were adults undergoing colorectal surgery expected to last for over 2 h. Results were analysed on an intention-to-treat basis. The study was successfully piloted, with 46% (90/196) of eligible patients recruited and 89% (80/90) of participants completing all components of the protocol. A trialled bolus-continuous dosing regimen was successful in maintaining free serum cefuroxime concentrations of 64 mg/L. No serious adverse reactions were identified. Rates of SSIs (superficial and deep SSIs) were lower in the intervention arm than the standard treatment arm (24% (10/42) vs. 30% (13/43)), as were infection within 30 days of operation (41% (17/43) vs 51% (22/43)) and urinary tract infections (2% (1/42) vs. 9% (4/43)). These infection rates can be used to power future clinical trials. This study demonstrates the feasibility of cefuroxime bolus-continuous infusion of antibiotic prophylaxis trials, and provides safety data for infusions targeting free serum cefuroxime concentrations of 64 mg/L. Trial registration: NCT02445859 .

Permanent pacemaker (PPM) implantation is an increasingly common procedure with complication rate estimated between 3% and 6%. Cardiac perforation by pacemaker lead(s) is rare, but a previous study has shown that it is probably an underdiagnosed complication. We are presenting a case of a patient who presented 5 days after PPM insertion with new-onset pleuritic chest pain. She had a normal chest X-ray (CXR), and acceptable pacing checks. However, a CT scan of the chest showed pneumopericardium and pneumothorax secondary to atrial lead perforation. The pain only settled by replacing the atrial lead. A repeat chest CT scan a few months later showed complete resolution of the pneumopericardium and pneumothorax. We believe that cardiac perforation can be easily missed if associated with normal CXR and acceptable pacing parameters. Unexplained chest pain following PPM insertion might be the only clue for such complication, although it might not always be present., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Advances in surgical technologies allowed safe laparoscopic pancreaticoduodenectomy (LPD). The aim of this study is to compare the oncologic outcomes of LPD to open pancreaticoduodenectomy (OPD) in terms of safety and recurrence rate., Materials and Methods: A cohort of 30 patients were matched for age, sex, American Society of Anaesthesiologists, tumor size, pancreatic duct diameter, and histopathologic diagnosis on a 1:1 basis (15 LPD, 15 OPD). Comparison between groups was performed on intention-to-treat basis. Survival following resection was compared using the Kaplan-Meier survival analysis., Results: The median operating time for LPD group was longer than for OPD group (470 vs. 310 min; P=0.184). However, estimated blood loss (300 vs. 620 mL; P=0.023), high dependency unit stay (2.0 vs. 6.0 d; P=0.013) and postoperative hospital stay (9.0 vs. 17.4 d; P=0.017) were significantly lower in the LPD group. There was no significant difference in postoperative rates of morbidity (40% vs. 67%; P=0.431) and mortality (0% vs. 6.7%; P=0.99). The surgical resection margins R0 status (87% vs. 73%; P=0.79) and the number of lymph nodes (18 vs. 20; P=0.99) in the resected specimens were comparable between the 2 groups. There was no significant difference in overall survival outcomes., Conclusions: In selected patients, the laparoscopic approach to pancreaticoduodenectomy in the hands of the experienced offers advantages over open surgery without compromising the oncologic resection.

Introduction: Side branch IPMN (SB-IPMN) of the pancreas has a malignancy rate between 10 and 20%. We hypothesized that surveillance at longer intervals on selected patients with SB-IPMN might be indicated., Methods: This is a retrospective study of prospectively collected data of 276 patients presenting from 2000 to 2010. After 2007, we opted to screen our patients with longer intervals, initially at 12 months then 24 months using MR if no "worrisome features" were present., Results: Complete data sets for 261 patients were analysed and patients were aged 78 (40-91) years. 232 patients had sole SB-IPMN while 92% were incidental (n = 209) and 8% were symptomatic (n = 24). Single SB-IPMN accounted for 84% (n = 195) of all cases; maximum diameter of 15.5 (5-60) mm. The median follow up duration was 46 (32-53) months. Short interval radiological surveillance (3-9 months) was 39% (n = 90), while long interval surveillance (12-36 months) was performed in 61% (n = 142). The rate of pancreatic resection, due to concern for the development of pancreatic cancer, in the short and long interval surveillance groups was 4.4% (n = 4) and 3.5% (n = 5) respectively; p = 0.78., Conclusion: Our data suggests no difference in outcome between long and short interval MR surveillance of SB-IPMN patients., (Copyright © 2016. Published by Elsevier Ltd.)

Objective: Gynecologists are reluctant to perform vaginal hysterectomy if the uterine size exceeds 12 weeks in the belief that complications could be higher in this group. The aim of this cohort control study was to compare demographics, surgical outcomes and safety of vaginal hysterectomy in women with non-prolapsed uteri weighing >280 g (>12 weeks size) to those with uteri weighing <280 g removed vaginally for similar indications., Study Design: In this study, classified as Canadian Task Force II (cohort-control), the index group comprised 41 women who underwent vaginal hysterectomy for non-prolapse indications with uterine enlargement >280 g (12 weeks), while the control group consisted of 66 women with uteri <280 g. Demographic data as well as duration of surgery, blood loss, intraoperative complications and readmission rates were compared., Results: Women in the two groups had statistically similar mean age, body mass index and parity (47.7 vs 44.9 yrs, 30.3 vs 32.4 kg m(-3) and 2.8 vs 2.4, respectively; p>0.05). The mean operative time was significantly longer in the index group (123.3±43.2 vs 85±32.1 min; p=1.47×10(-6)). Women with enlarged uteri had greater mean estimated blood loss (402.8±402.2 vs 160.8±123.2 ml; p<0.0001) but the mean length of stay was similar (45.4±28.7 vs 37.6±26.2 h; p>0.05). Two uteri weighing >1000 g were removed vaginally. Intra- and post-operative complications such as bladder injury, blood transfusion and pelvic sepsis were similar in both groups., Conclusions: Vaginal hysterectomy in larger non-prolapsed uteri takes longer (mean 38 min longer) and is associated with more blood loss (mean increase 242 ml) compared to normal-sized uteri but is not associated with a significant increase in complication rates., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Objective: To compare surgical outcomes in women with enlarged uteri >12 weeks' size who underwent vaginal hysterectomy compared to abdominal hysterectomy for non-prolapse indications., Study Design: Retrospective cohort study performed between 2007 and 2012 in a North London teaching hospital. The study group comprised 39 women who had vaginal hysterectomy (VH) with uteri >12 weeks size (200g) for non-prolapse indications. The next successive total abdominal hysterectomy (TAH) following the index case for similar indications (and with similar uterine weights) served as control (n=33). The groups were compared for pre- and post-operative demographic data, and main outcome measures were estimated blood loss, operation time, length of stay and complications., Results: Both VH and TAH groups had statistically similar pre-operative mean haemoglobin levels, age, body mass index, previous abdominal surgery, and American Society of Anesthesiologists (ASA) grade. Mean uterine weight (403.1±239.5 vs 460.5±236.2g) was comparable in both groups (both p>0.05). The mean duration of the procedure was similar (123.5±45.8 vs 119.8±44.9min, p=0.580) but women who had TAH lost 117ml more of blood (525.7±427.6 vs 408.2±411.8ml, p=0.039). Although overall complication rates were comparable between the groups (30.8% vs 36.4%, p=0.627), the mean post-operative stay was 55% shorter following VH (40.7±29.4 vs 90.7±46.2h, p<0.0001)., Conclusion: In women with non-prolapsed uteri >12 weeks' size, VH is a safe and cost effective option. The vaginal route is associated with significantly lower estimated blood loss and 55% shorter post-operative stay, with no increase in complication rates., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)