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    Abstract

    Although amazing progress has been made in machine learning to achieve high generalization accuracy and efficiency, there is still very limited work on deriving meaningful decision-making actions from the resulting models. However, in many applications such as advertisement, recommendation systems, social networks, customer relationship management, and clinical prediction, the users need not only accurate prediction, but also suggestions on actions to achieve a desirable goal (e.g., high ads hit rates) or avert an undesirable predicted result (e.g., clinical deterioration). Existing works for extracting such actionability are few and limited to simple models such as a decision tree. The dilemma is that those models with high accuracy are often more complex and harder to extract actionability from.

    In this paper, we propose an effective method to extract actionable knowledge from additive tree models (ATMs), one of the most widely used and best off-the-shelf classifiers. We rigorously formulate the optimal actionable planning (OAP) problem for a given ATM, which is to extract an actionable plan for a given input so that it can achieve a desirable output while maximizing the net profit. Based on a state space graph formulation, we first propose an optimal heuristic search method which intends to find an optimal solution. Then, we also present a sub-optimal heuristic search with an admissible and consistent heuristic function which can remarkably improve the efficiency of the algorithm. Our experimental results demonstrate the effectiveness and efficiency of the proposed algorithms on several real datasets in the application domain of personal credit and banking.


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    Abstract

    In order to maintain the quantity of ferrous ions, two eco-friendly chelating agents (CAs), i.e., sodium citrate (Citrate) and sodium gluconate (Glu), have been introduced into a traditional iron activated sodium persulfate (PS) system (Fe2+/PS). The results indicated that the PS/CA/Fe2+ oxidation could be an effective method for BDE209 removal. Effects of the chelating agents, reagents dosage, and pH were evaluated in batch experiments. Glu was observed to be more effective than citrate. In addition, the rate constants (k1) of BDE209 removal indicated a quadratic curve relationship with initial persulfate concentrations (k1 = −0.019 × [PS]02 + 0.031 × [PS]0 + 0.007, R2 = 0.933, [PS]0 = 0.1–1.0 M) and a good linear relationship with initial ferrous contents (k1 = 0.109 × [Fe2+]0 + 0.002, R2 = 0.943). Furthermore, as a reducing agent, ascorbic acid (H2A) could enhance the degradation rate of BDE209, which might be because H2A accelerated the transformation process from Fe3+- to Fe2+-gluconate complexes.


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    Abstract

    Background

    Surgeons are likely to get progressively fatigued and work less effectively during the course of a normal workday. We sought to examine the effects of surgery start times (morning vs. afternoon) and workload of the surgeons on morbidity of patients after partial liver resection (LR).

    Methods

    A total of 155 pairs of the patients from 383 patients undergoing LR were generated by propensity score analysis (PSM) according to the start times of surgery: group M (morning surgery, 8 a.m.–1 p.m.) and group A (afternoon surgery, 1 p.m.–6 p.m.). Patients in group A were further divided depending on whether or not the surgeons had performed other surgeries earlier in the day and the exact duration of the other surgeries before the afternoon surgery (≤180 and >180 min). The incidence and severity of postoperative complications were compared between different groups.

    Results

    By using PSM analysis, the patients in group M and group A were well matched in basic characteristics. The incidence and severity of the postoperative complications were similar between the two groups (all p > 0.05). Whether the surgeons had performed other surgeries prior to the afternoon surgery seemed not affecting the postoperative outcome (all p > 0.05). Moreover, the duration of other surgeries the surgeons had performed did not have significant influence on the outcome of patients undergoing afternoon surgery (all p > 0.05).

    Conclusions

    Surgery start times and workload of surgeons during working time did not measurably affect short-term outcomes of the patients. The negative findings might be a manifestation of professional judgment and self-regulation of the experienced physicians.


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    Abstract

    Image retargeting is a process to change the resolution of image while preserve interesting regions and avoid obvious visual distortion. In other words, it focuses on image content more than anything else that applies to filter the useful information for data analysis. Existing approaches may encounter difficulties on the various types of images since most of these approaches only consider 2D features, which are sensitive to the complexity of the contents in images. Researchers are now focusing on the RGB-D information, hoping depth information can help to promote the accuracy. However it is not easy to obtain the RGB-D image we need anywhere and how to utilize depth information is still at the exploration stage. In this paper, instead of using RGB-D data captured by 3D camera, we employ an iterative MRF learning model to predict depth information from a single still image. Then we propose our self-learning 3D saliency model based on the RGB-D data and apply it on the seam carving framework. In seam caving, the self-learning 3D saliency is combined with L1-norm of gradient for better seam searching. Experimental results demonstrate the advantages of our method using RGB-D data in the seam carving framework.


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    Abstract

    Background

    Few studies have investigated the use of dexmedetomidine in patient-controlled intravenous analgesia (PCIA) after thoracic surgery. This study to evaluate the effect of dexmedetomidine combined with sufentanil for PCIA after thoracotomy under general anaesthesia.

    Methods

    Ninety-seven adults patients scheduled for thoracotomy surgery. All two groups received PCIA with either sufentanil alone (control group) or combining dexmedetomidine with sufentanil (dexmedetomidine group). Hemodynamic measurements, visual analog scale (VAS) scores at rest and at coughing, Ramsay sedation score (RSS), analgesic consumption, and postoperative nausea and vomiting (PONV) as well as drug-related adverse effects were compared at 2, 6, 12, 24, 36 and 48 h postoperatively.

    Results

    In the patients of the dexmedetomidine group, compared to the control group, the pain scores at rest or at coughing during 48 h postoperatively were lower (P < 0.001), the sedation scores were lower, the consumption of sufentanil and rescue meperidine were lower, and the number of episode of moderate PONV was three times lower. No signs of toxicity or local complications were observed. There was a non-significant trend for a lower HR and BP in the dexmedetomidine group vs. Control.

    Conclusion

    The combining dexmedetomidine with sufentanil for post-thoracotomy PCIA can improve pain control together with the decrease in sufentanil requirements, and improve postoperative patient’s satisfaction compared with sufentanil alone in PCIA.

    Trial Registration

    This trial was retrospectively registered on 27 April 2016 at the Chinese Clinical Trial Register (number: ChiCTR-ONC-16008376).


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    Abstract

    During biomass fast pyrolysis process, the interactions among biomass components will affect the pyrolytic products distribution. In this study, d-glucose and a β-O-4 type lignin model dimer (LMD, 1-(4-hydroxy-3-methoxyphenyl)-2-(2-methoxyphenoxy)propane-1,3-diol) were selected as the model compounds of cellulose and lignin. The interaction characteristics and mechanism during their fast co-pyrolysis process were investigated by combined pyrolysis–gas chromatography/mass spectrometry (Py–GC/MS) experiments and density functional theory (DFT) calculations. The Py–GC/MS results indicated that during fast co-pyrolysis process, the presence of LMD significantly decreased the formation of levoglucosan (LG) from d-glucose, while promoted the formation of linear carbonyls and furans. Meanwhile, the presence of d-glucose enhanced the decomposition of LMD to generate phenolic compounds. The DFT calculations revealed that d-glucose would interact with a homolysis radical of LMD to form a ten-membered ring transition state. The formed complex transition state changed the energy barriers of certain pyrolytic reactions of d-glucose and LMD, thus affecting the pyrolytic products distribution.


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    Abstract

    Silver nanowires (Ag NWs) are the promising materials to fabricate flexible transparent electrodes, aiming to replace indium tin oxide (ITO) in the next generation of flexible electronics. Herein, a feasible polyvinylpyrrolidone (PVP)-mediated polyol synthesis of Ag NWs with different aspect ratios is demonstrated and high-quality Ag NWs transparent electrodes (NTEs) are fabricated without high-temperature thermal sintering. When employing the mixture of PVP with different average molecular weight as the capping agent, the diameters of Ag NWs can be tailored and Ag NWs with different aspect ratios varying from ca. 30 to ca. 1000 are obtained. Using these as-synthesized Ag NWs, the uniform Ag NWs films are fabricated by repeated spin coating. When the aspect ratios exceed 500, the optoelectronic performance of Ag NWs films improve remarkably and match up to those of ITO films. Moreover, an optimal Ag NTEs with low sheet resistance of 11.4 Ω/sq and a high parallel transmittance of 91.6% at 550 nm are achieved when the aspect ratios reach almost 1000. In addition, the sheet resistance of Ag NWs films does not show great variation after 400 cycles of bending test, suggesting an excellent flexibility. The proposed approach to fabricate highly flexible and high-performance Ag NTEs would be useful to the development of flexible devices.


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    Abstract

    Background

    Research interests toward single cell analysis have greatly increased in basic, translational and clinical research areas recently, as advances in whole-transcriptome amplification technique allow scientists to get accurate sequencing result at single cell level. An important step in the single-cell transcriptome analysis is to identify distinct cell groups that have different gene expression patterns. Currently there are limited bioinformatics approaches available for single-cell RNA-seq analysis. Many studies rely on principal component analysis (PCA) with arbitrary parameters to identify the genes that will be used to cluster the single cells.

    Results

    We have developed a novel algorithm, called SAIC (Single cell Analysis via Iterative Clustering), that identifies the optimal set of signature genes to separate single cells into distinct groups. Our method utilizes an iterative clustering approach to perform an exhaustive search for the best parameters within the search space, which is defined by a number of initial centers and P values. The end point is identification of a signature gene set that gives the best separation of the cell clusters. Using a simulated data set, we showed that SAIC can successfully identify the pre-defined signature gene sets that can correctly separated the cells into predefined clusters. We applied SAIC to two published single cell RNA-seq datasets. For both datasets, SAIC was able to identify a subset of signature genes that can cluster the single cells into groups that are consistent with the published results. The signature genes identified by SAIC resulted in better clusters of cells based on DB index score, and many genes also showed tissue specific expression.

    Conclusions

    In summary, we have developed an efficient algorithm to identify the optimal subset of genes that separate single cells into distinct clusters based on their expression patterns. We have shown that it performs better than PCA method using published single cell RNA-seq datasets.


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    Abstract

    The problem of efficiently generating test data covering multiple paths was focused on this study, and a method of generating test data covering multiple paths using a genetic algorithm incorporating with reducing the input domain of a program was presented. In this method, all target paths are first divided into several groups based on the same independent sub-path, and the input variables corresponding to the independent sub-path are determined. Then, a multi-population genetic algorithm is used to generate test data to cover these target paths, each sub-population generating test data covering target paths belonging to the same group. During the evolution, the input variables corresponding to the traversed independent sub-path are remained fixed, and the ranges of crossover and mutation operations are reduced, leading to these sub-populations’ search in a reduced input domain so that the efficiency of generating test data is improved.


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    Abstract

    Background

    Many orthopaedic surgeons worry about asymptomatic bacteriuria (ASB) as a possible risk factor for prosthetic joint infection (PJI). However, available evidence establishing a direct link between ASB and PJI is limited. This meta-analysis aimed to investigate whether ASB is a factor for PJI and whether pre-operative antibiotic treatment shows benefit.

    Method

    We systematically searched major databases such as PubMed, Web of Science, the Cochrane Library and EMBASE for studies. Risk ratio (RR) was calculated for included studies that reported raw counts with 95% confidence interval (CI).

    Results

    Five studies involved 3588 joint arthroplasties and 441 cases of ASB (overall incidence 12.3%). Compared with the control group, PJI was more common in both patients in the ASB group (RR = 2.87; 95% CI, 1.65–5.00). But in all five studies, the micro-organisms isolated from PJI and urine cultures were not the same. Three of the five studies reported that the antibiotic treated the ASB prior to joint arthroplasty and compared the untreated ASB group.There was no significant difference between groups (RR = 0.89; 95% CI, 0.36–2.20).

    Discussion

    PJI occurring via the haematogenous route from the genitourinary tract harbouring bacteria in ASB is impossible. Pre-operative antibiotic treatment has no benefit. A plausible explanation could be an indicator of frailty and increased susceptibility to infection.

    Conclusions

    ASB increased the risk of PJI in the meta-analysis. However, current evidence does not support systematic antibiotherapy prior to joint arthroplasty and screening for ASB.


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    Abstract

    Fast pyrolysis of specific corn stalk (CS) materials offered a promising and convenient way to selectively produce two valuable compounds, i.e., 4-vinyl phenol (4-VP) and 5-hydroxymethyl furfural (5-HMF). In this study, CSs at five different growth stages were prepared, including trefoil stage (30 days), elongation stage (70 days), heading stage (80 days), ripening stage (100 days) and full ripening stage (120 days). Moreover, three fractions were separated from CSs except the CS of trefoil stage, including leaf, stem bark and stalk pulp. Fast pyrolysis of CSs were performed via pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) technique. The results indicated that the pyrolytic characteristics of these CSs differed greatly from each other. 4-VP and 5-HMF were the two major products at low pyrolysis temperatures. Stem bark at elongation stage was the best feedstock for selective production of 4-VP, with a yield of 4.98 wt% at 300 °C. Stalk pulp at ripening stage was optimal for selective production of 5-HMF, with a yield of 4.87 wt% at 300 °C. In addition, a brief mechanism exploitation for the formation of 4-VP and 5-HMF was also conducted with the aid of CS sample characterization.

    Graphical Abstract


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    Abstract

    Business groups dominate the economic landscape in many economies around the world. While business groups overcome the institutional voids arising due to inefficiencies of external markets, they also possess market power, which could be economically and socially counterproductive, especially for unaffiliated firms. Drawing on the transaction cost and industrial organization economics, we examine whether the presence of business group affiliated firms in industries restricts the entry of unaffiliated firms or firms affiliated with small- and medium-size business groups. Findings based on Indian firms suggest that investments by business group affiliated firms in an industry have an inverted U-shaped relationship with the investment by unaffiliated firms. However, investments by firms affiliated with large-sized business groups have a U-shaped relationship with the investment by affiliates of small and medium business groups. These findings suggest that the market power of business groups and entry barrier relationship is contingent on the size of the business groups.


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    Abstract

    Background

    Transient elastography-based liver stiffness value (TE-LSV) has been investigated for assessing clinically significant portal hypertension (CSPH). The aetiology of CSPH is an important factor determining TE-LSV. There is insufficient evidence for selecting cut-off values.

    Aims

    This study performed a meta-analysis to compare the three most widely used cut-off values (around 13.6 kPa, 18 kPa and 22kPa) of TE-LSV for the diagnosis of CSPH in patients with chronic viral liver disease.

    Methods

    The PubMed, Ovid, Web of Science and Cochrane Library databases were searched. Diagnostic data for cut-off values around 13.6 kPa, 18 kPa and 22 kPa in each included study were extracted. The bivariate model was performed to estimate pooled sensitivity, specificity, positive likelihood ratio (LR+) and negative likelihood ratio (LR-).

    Results

    Eleven studies assessing 910 patients were included in this meta-analysis. Pooled sensitivities of cut-off values around 13.6 kPa, 18 kPa and 22 kPa were 0.96 (95% CI 0.93–0.97), 0.85 (0.81–0.89) and 0.74 (0.66–0.80), respectively; pooled specificities were 0.60 (0.47–0.75), 0.80 (0.71-0.87) and 0.94 (0.86–0.97), respectively. Pooled LR+ values were 2.4 (1.6–3.7), 4.4 (2.9–6.8) and 11.5 (5.5–23.5) for cut-off values around 13.6 kPa, 18 kPa and 22 kPa, respectively, for pooled LR- values of 0.07 (0.04–0.13), 0.17 (0.12–0.25) and 0.28 (0.22–0.36), respectively.

    Conclusion

    Cut-off values around 13.6 kPa (high sensitivity) and 22 kPa (high specificity) could be used as screening and confirmation tools, respectively, in the diagnosis of CSPH. Overall, the cut-off value around 22 kPa showed the best performance.

    Key Points

    • Transient elastography-based liver stiffness could be used to diagnose portal hypertension.

    • Comparison of certain cut-off values would provide more information for clinical decision-making.

    • Cut-off around 13.6 kPa was able to exclude clinically significant portal hypertension (CSPH) effectively.

    • Cut-off around 22 kPa was able to confirm CSPH effectively.


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    Abstract

    Background

    Protein secondary structure can be regarded as an information bridge that links the primary sequence and tertiary structure. Accurate 8-state secondary structure prediction can significantly give more precise and high resolution on structure-based properties analysis.

    Results

    We present a novel deep learning architecture which exploits an integrative synergy of prediction by a convolutional neural network, residual network, and bidirectional recurrent neural network to improve the performance of protein secondary structure prediction. A local block comprised of convolutional filters and original input is designed for capturing local sequence features. The subsequent bidirectional recurrent neural network consisting of gated recurrent units can capture global context features. Furthermore, the residual network can improve the information flow between the hidden layers and the cascaded recurrent neural network. Our proposed deep network achieved 71.4% accuracy on the benchmark CB513 dataset for the 8-state prediction; and the ensemble learning by our model achieved 74% accuracy. Our model generalization capability is also evaluated on other three independent datasets CASP10, CASP11 and CASP12 for both 8- and 3-state prediction. These prediction performances are superior to the state-of-the-art methods.

    Conclusion

    Our experiment demonstrates that it is a valuable method for predicting protein secondary structure, and capturing local and global features concurrently is very useful in deep learning.


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    Abstract

    Background

    Bone marrow is an important source of stem cells, which can promote bone fracture healing.

    Methods

    We investigated the optimal time to inject bone marrow mesenchymal stem cells (BMSCs) in a C57 murine unilateral, transverse, femur fracture model. BMSCs transfected with red fluorescent protein (RFP-BMSCs) were injected via the tail vein on day 1, 7, or 14 post-fracture. AMD3100 (inhibitor of stromal cell-derived factor 1 [SDF-1]) was also injected before RFP-BMSCs in one group for comparison; a control group received saline injections. RFP-BMSC migration and fracture healing were evaluated by in vivo fluorescence assay. Micro-CT was performed and mechanical testing and histological analysis. Chemokine levels were evaluated by quantitative real-time PCR and western blotting.

    Results

    Following injection on day 7 post-fracture, RFP-BMSCs more frequently homed to the fracture site and remained for a longer duration. Bone volume and bone mineral density were increased when BMSCs were injected on day 7 post-fracture (P < 0.05). The mechanical properties of fractured femurs were improved following day-7 BMSC injection. Histology confirmed that BMSC injection improved the formation of new bones.

    Conclusions

    Chemokines that induce BMSC migration were highly expressed, and protein levels of osteogenesis-related factors were increased. Seven days after fracture may be the optimal time for injection of BMSCs to promote fracture healing. Additionally, the SDF-1/CXCR4 pathway may play an important role in fracture healing following BMSC injection.


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    Abstract

    In order to understand the catalytic effects of inherent inorganic elements in biomass on the pyrolysis mechanism of lignin, density functional theory with a Gaussian method of M06-2X and basic set of 6-31 + G(d,p) was employed to simulate the pyrolysis pathways of a β-O-4 type lignin dimer model compound (1-methoxy-2-(4-methoxyphenethoxy)benzene) catalyzed by NaCl and KCl which are major inorganic constituents of biomass at microscale level. The calculation results indicate that cations (Na+ and K+) in alkali metal chlorides are facile to combine with the oxygen-containing functional groups in the lignin dimer model compound. Both cations increase the Cβ−O bond length and shorten the Cα–Cβ bond length, which will further affect their bond dissociation energies. In the initial pyrolysis process of the lignin dimer model compound, NaCl and KCl can promote the Cβ–O homolytic reaction and concerted decomposition reaction, while restrain the Cα–Cβ homolytic reaction. Therefore, the lignin dimer model compound decomposes mainly through the concerted decomposition and Cβ–O homolytic mechanisms under NaCl and KCl catalytic pyrolysis conditions, producing 1-methoxy-4-vinylbenzene, 1-ethyl-4-methoxybenzene, 2-methoxyphenol, catechol and 2-hydroxybenzaldehyde, among which NaCl and KCl have inhibitory effect on 2-hydroxybenzaldehyde, but have promoting effect on the other pyrolytic products.


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    Abstract

    Continuous exposure of chemicals could cause various environmental impacts. Decabromodiphenyl ether (BDE209) and lead (Pb) can co-exist and are discharged simultaneously at e-waste recycling sites (EWRSs). Extensive concerns have been attracted by their toxic effects on soil microorganisms. Thus, by using high-throughput sequencing, this study explored bacterial community responses in a soil system after repeated Pb exposure in the presence of BDE209 in the laboratory during 90-day indoor incubation period. Gene sequencing of 16S rDNA performed on an Illumina MiSeq platform proved that one-off Pb exposure caused higher microbial abundance and community diversity. Additionally, both repetitive Pb treatment and exogenous BDE209 input could change bacterial community composition. Twenty-three different bacterial phyla were detected in the soil samples, while more than 90% of the sequences in each treatment belonged to a narrow variety. The sequence analyses elucidated that Proteobacteria, Acidobacteria, and Bacteroidetes were the top three dominant phyla. Our observations could provide a few insights into the ecological risks of Pb and BDE209 co-existed contamination in soils at EWRSs.


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    Abstract

    In this paper, we address the problem of safe and efficient intersection crossing traffic management of autonomous and connected ground traffic. Toward this objective, we propose an algorithm called the discrete-time occupancies trajectory based intersection traffic coordination algorithm (DICA). We show that the basic DICA has a computational complexity of \(\mathcal {O}(n^{2} {L_{m}^{3}})\) where n is the number of vehicles granted to cross an intersection and Lm is the maximum length of intersection crossing routes. To improve the overall computational efficiency of the algorithm, the basic DICA is enhanced by several computational approaches that are proposed in this paper. The enhanced algorithm has the computational complexity of \(\mathcal {O}(n^{2} L_{m} \log _{2} L_{m})\). The improved computational efficiency of the enhanced algorithm is validated through simulations using an open source traffic simulator called the simulation of urban mobility (SUMO). The overall throughput, as well as the computational efficiency of the enhanced algorithm, are also compared with those of an optimized traffic light control algorithm.


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    Abstract

    In recent years, a variety of systems using deep convolutional neural network (CNN) approaches have achieved good performance on license plate detection and character recognition. However, most of these systems are not stable when the scenes changed, specification of each hierarchical layer to get the final detection result, which can detect multi-scale license plates from an input image. Meanwhile, at the stage of character recognition, data annotation is heavy and time-consuming, giving rise to a large burden on training a better model. We devise an algorithm to generate annotated training data automatically and approximate the data from the real scenes. Our system used for detecting license plate achieves 99.99% mean average precision (mAP) on OpenITS datasets. Character recognition also sees high accuracy, thus verifying the superiority of our method.


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    Abstract

    Background

    Delayed bowel function recovery and postoperative ileus are relatively serious complications of laparoscopic radical cystectomy (LRC). Our study aimed to determine whether performing pelvic re-peritonealization reduces the incidence of these complications.

    Methods

    Clinical data of 78 patients who had undergone LRC with pelvic re-peritonealization from August 2015 to December 2017 were retrospectively collected and compared with those of 92 patients who had undergone LRC alone between January 2013 and July 2015 in our institution. Differences in duration of surgery, estimated blood loss, time to recovery of bowel function, the complications of intestinal and blood vessel injury, and incidence of postoperative ileus between the two groups were analyzed.

    Results

    Baseline characteristics such as age, sex and BMI were balanced between the two groups. There were no significant differences in duration of surgery (P = 0.072), estimated blood loss (P = 0.717), or incidence of intestinal obstruction (P = 0.225) between the two groups. Interestingly, patients who had undergone pelvic re-peritonealization recovered bowel function more rapidly than those had not (2.79 d vs. 3.72 d, P = 0.001). Additionally, hospitalization stay was significantly shorter for patients with re-peritonealization than for those without (5.46 d vs. 6.68 d, P = 0.029).

    Conclusions

    Compared with LRC alone, LRC with pelvic re-peritonealization as described in the present study had comparable perioperative complications, but was associated with more rapid gastrointestinal recovery and shorter hospitalization stay.