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Abstract Electrochromic devices are applied extensively to camouflages, smart windows, heat insulation layers, and automobile rearview mirrors, etc. The amorphous WO3 is a very attractive electrochromic material, whereas it suffers from degradation of optical modulation and reversibility on ion exchange owing to those deep trapped ions with irreversible reaction behavior. Herein, we designed and, by using magnetron sputtering, prepared a composite film with TiO2/WO3/TiO2 double heterojunctions, which is capable of eliminating the deep trapped ions by itself under ultraviolet light (UV) assistance. The electrochromic device based on this composite film, after being recovery by short-time UV irradiation, can maintain a high transmission modulation of 94.72% after 7000 cycles of the voltammetry measurement. This feature allows the device to maintain its initial electrochromic performance after prolonged use. Moreover, the double heterojunction structure can reduce colouring time and enormously improve the colouration efficiency (CE) of electrochromic devices. Experimental research shows that when the thickness of the bottom and upper TiO2 layer of the WO3 film was 145.5 nm and 97.0 nm, respectively, the CE of electrochromic devices reached a perfectly high value (479.3 cm2/C), being much higher than that of WO3 devices (69.5 cm2/C). Functions of the TiO2/WO3/TiO2 double heterojunction in electrochromic device were investigated by combining theoretical analysis and experiment validation, and these results provide a general framework for developing and designing superior electrochromic materials and devices.

Abstract Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-dependent procedures and occur in a highly complex organ topology. There exists a high missed detection rate and incomplete removal of colonic polyps. To assist in clinical procedures and reduce missed rates, automated methods for detecting and segmenting polyps using machine learning have been achieved in past years. However, the major drawback in most of these methods is their ability to generalise to out-of-sample unseen datasets from different centres, populations, modalities, and acquisition systems. To test this hypothesis rigorously, we, together with expert gastroenterologists, curated a multi-centre and multi-population dataset acquired from six different colonoscopy systems and challenged the computational expert teams to develop robust automated detection and segmentation methods in a crowd-sourcing Endoscopic computer vision challenge. This work put forward rigorous generalisability tests and assesses the usability of devised deep learning methods in dynamic and actual clinical colonoscopy procedures. We analyse the results of four top performing teams for the detection task and five top performing teams for the segmentation task. Our analyses demonstrate that the top-ranking teams concentrated mainly on accuracy over the real-time performance required for clinical applicability. We further dissect the devised methods and provide an experiment-based hypothesis that reveals the need for improved generalisability to tackle diversity present in multi-centre datasets and routine clinical procedures.

Abstract Colorectal cancer is a leading cause of cancer-related deaths globally. In recent years, the use of convolutional neural networks in computer-aided diagnosis (CAD) has facilitated simpler detection of early lesions like polyps during real-time colonoscopy. However, the majority of existing techniques require a large training dataset annotated by experienced experts. To alleviate the laborious task of image annotation and utilize the vast amounts of readily available unlabeled colonoscopy data to further improve the polyp detection ability, this study proposed a novel self-supervised representation learning method called feature pyramid siamese networks (FPSiam). First, a feature pyramid encoder module was proposed to effectively extract and fuse both local and global feature representations among colonoscopic images, which is important for dense prediction tasks like polyp detection. Next, a self-supervised visual feature representation containing the general feature of colonoscopic images is learned by the siamese networks. Finally, the feature representation will be transferred to the downstream colorectal polyp detection task. A total of 103 videos (861,400 frames), 100 videos (24,789 frames), and 60 videos (15,397 frames) in the LDPolypVideo dataset are used to pre-train, train, and test the performance of the proposed FPSiam and its counterparts, respectively. The experimental results have illustrated that our FPSiam approach obtains the optimal capability, which is better than that of other state-of-the-art self-supervised learning methods and is also higher than the method based on transfer learning by 2.3 mAP and 3.6 mAP for two typical detectors. In conclusion, FPSiam provides a cost-efficient solution for developing colorectal polyp detection systems, especially in conditions where only a small fraction of the dataset is labeled while the majority remains unlabeled. Besides, it also brings fresh perspectives into other endoscopic image analysis tasks.

Objectives Risk prediction for patients with polymyositis/dermatomyositis-associated interstitial lung disease (PM/DM-ILD) is challenging due to heterogeneity in the disease course. We aimed to develop a mortality risk prediction model for PM/DM-ILD.Methods This prognostic study analysed patients with PM/DM-ILD admitted to Nanjing Drum Hospital from 2016 to 2021. The primary outcome was mortality within 1 year. We used a least absolute shrinkage and selection operator (LASSO) logistic regression model to identify predictive laboratory indicators. These indicators were used to create a laboratory risk score, and we developed a mortality risk prediction model by incorporating clinical factors. The evaluation of model performance encompassed discrimination, calibration, clinical utility and practical application for risk prediction and prognosis.Results Overall, 418 patients with PM/DM-ILD were enrolled and randomly divided into development (n=282) and validation (n=136) cohorts. LASSO logistic regression identified four optimal features in the development cohort, forming a laboratory risk score: C reactive protein, lactate dehydrogenase, CD3+CD4+ T cell counts and PO2/FiO2. The final prediction model integrated age, arthralgia, anti-melanoma differentiation-associated gene 5 antibody status, high-resolution CT pattern and the laboratory risk score. The prediction model exhibited robust discrimination (area under the receiver operating characteristic: 0.869, 95% CI 0.811 to 0.910), excellent calibration and valuable clinical utility. Patients were categorised into three risk groups with distinct mortality rates. The internal validation, sensitivity analyses and comparative assessments against previous models further confirmed the robustness of the prediction model.Conclusions We developed and validated an evidence-based mortality risk prediction model with simple, readily accessible clinical variables in patients with PM/DM-ILD, which may inform clinical decision-making.

Abstract Introduction The association between mycophenolate mofetil (MMF) and infection in patients with systemic lupus erythematosus (SLE) has not been clarified. This study evaluated the degree and factors in effect of MMF use on infection in patients with SLE. Methods A hospitalized-based observational study was conducted to collect medical records on patients with SLE during 2010–2021. A nested case–control study was performed among 3339 patients with SLE, including 1577 cases and 1762 controls by whether they developed any type of infection. The exposure of MMF use was determined within 1 year before diagnosed infection or the end of follow-up. Logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI) for association between MMF and subsequent infection. Results MMF was significantly associated with the risk of overall infection (adjusted OR 1.90, 95% CI 1.48–2.44) and different types of infections, including bacterial infection (adjusted OR 2.07, 95% CI 1.55–2.75), viral infection (adjusted OR 1.92, 95% CI 1.23–3.01), and opportunistic infection (adjusted OR 2.13, 95% CI 1.31–3.46). The top three risks of specific types of infections were bacteremia/septicemia, urinary tract infection/pyelonephritis, and herpes zoster. Stratification analysis showed risk of overall infection increased especially in MMF users with age over 55 years, diabetes, central nervous system involvement, and thrombocytopenia. Moreover, the risk of infection increased with increasing dosage and duration of MMF use. Additionally, the combination of MMF with CYC and other immunosuppressants significantly increases the risk of infections compared to using a single one. Conclusions MMF use is associated with various type of infections in patients with SLE, particularly in those with longer use, older age, complications with comorbidities, and concomitant use of CYC or other immunosuppressants.

Abstract Background Rheumatoid arthritis (RA) is a major public health problem. Unfortunately, there is a scarcity of comprehensive and up-to-date information regarding the burden of RA and its dynamic trends in subsequent years. To examine the changing trends in the global burden of RA and forecast for 2044, which will facilitate the development of strategies tailored to RA burden and provide reference for the development of effective treatment guidelines. Methods Following the general analytical strategy used the Global Burden of Disease Study (GBD) 2019, which included 204 countries, the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR) and age-standardized disability adjusted of life year (DALY) rate for RA were analyzed. Results The ASIR, ASMR and age-standardized DALY rate for RA in 2019 were 13.001/100,000 (95% UI, 11.833 ~ 14.274), 0.574/100,000 (95% UI, 0.356 ~ 0.793) and 39.565/100,000 (95% UI, 49.529 ~ 30.508), respectively. America had the highest ASIR [18.578(95% UI, 17.147 ~ 20.148)] and age-standardized DALY rate [53.676(95% UI, 40.106 ~ 67.968)] in 2019. Asia had the highest ASMR [0.681(95% UI, 0.802 ~ 0.480)] in 2019. From 1990 to 2019, a significant average annual percentage change (AAPC) in the ASIR was observed in both males [0.237% (95% CI, 0.216 ~ 0.259%)] and females [0.197% (95% CI, 0.141 ~ 0.254%)], AAPC in the ASMR was observed in both males [-0.398% (95% CI, -0.605~-0.191%)] and females [-0.295% (95% CI, -0.424~-0.65%)]. Age effects indicated that the relative risk (RR) of RA-associated incidence and mortality rates increased with age among males and females. The RR of RA increased over time and started to gradually increase from 1990. Cohort effects showed decreases in incidence, mortality and DALY rates in successive birth cohorts. The global incidence of RA would continue to increase in the future, while mortality would continue to decrease. Conclusion The increased risk of RA is dominantly influenced by age effects and period effects and the ethnic area. The results suggest that early identification and treatment of RA is important for reducing the ongoing burden with age, and targeted health education and specific intervention programs should be promoted to control middle-elderly population.

Objectives The study aims to investigate the impact of gene polymorphisms on blood hydroxychloroquine (HCQ) concentrations in patients with SLE and provide guidelines for individualised care.Methods 489 Chinese patients with SLE taking HCQ for more than 3 months were collected in this study. The blood HCQ, desethylhydroxychloroquine (DHCQ) and desethylchloroquine concentrations were measured. The optimal blood concentration of HCQ was determined by receiver operating characteristic curve analysis. Single nucleotide polymorphisms of metabolic enzymes involved in HCQ metabolism were genotyped and the associations with treatment effects were investigated.Results The cut-off value of HCQ was 559.67 ng/mL, with sensitivity and specificity values of 0.51 and 0.89, respectively. The TC and CC genotypes of CYP2C8 (rs7910936) were significantly related to the increase in blood HCQ concentrations, and the CYP2C8 (rs10882521) TT genotype was associated with lower blood HCQ concentrations. The DHCQ:HCQ ratio was highest in patients with the GG genotype of the CYP2D6*10 (rs1065852) polymorphism and lowest in those with the AA genotype. Patients with the CYP2C8 (rs7910936) CC genotype were more likely to achieve the optimal blood concentration (p=0.030) in HCQ 200 mg/day group and patients with the CYP2D6*10 (rs1065852) GG genotype were more likely to reach the optimal blood concentration (p=0.049) in 400 mg/day group.Conclusions Our results suggest that the optimal blood concentration of HCQ measured approximately 12–18 hours after the last dosage may be between 500 and 600 ng/mL in Chinese patients with SLE. The observed variations in HCQ concentrations between individuals can potentially be attributed to genetic polymorphisms in CYP2D6*10 (rs1065852) and CYP2C8 (rs7910936 and rs10882521). Genotypical testing of patients and regular monitoring of blood levels are recommended for optimising HCQ dosage management in Chinese patients with SLE.Trial registration number ChiCTR2300070628.

Objective Patients with systemic lupus erythematosus (SLE) have an increased risk of venous thromboembolism (VTE). We conducted this study to develop a risk score algorithm for VTE in patients with SLE that provides individualised risk estimates.Methods We developed a clinical prediction model of VTE in 4502 patients with SLE based on the Chinese SLE Treatment and Research group cohort (CSTAR) from January 2009 to January 2020 and externally validated in 3780 patients with SLE in CSTAR from January 2020 to January 2022. Baseline data were obtained and VTE events were recorded during the follow-up. The prediction model was developed to predict VTE risk within 6 months in patients with SLE, using multivariate logistic regression and least absolute shrinkage and selection operator. SLE-VTE score and nomogram were established according to the model.Results A total of 4502 patients included in the development cohort, 135 had VTE events. The final prediction model (SLE-VTE score) included 11 variables: gender, age, body mass index, hyperlipidaemia, hypoalbuminaemia, C reactive protein, anti-β2GPI antibodies, lupus anticoagulant, renal involvement, nervous system involvement and hydroxychloroquine, with area under the curve of 0.947 and 0.808 in the development (n=4502) and external validation cohort (n=3780), respectively. According to the net benefit and predicted probability thresholds, we recommend annual screening of VTE in high risk (≥1.03%) patients with SLE.Conclusion Various factors are related to the occurrence of VTE in patients with SLE. The proposed SLE-VTE risk score can accurately predict the risk of VTE and help identify patients with SLE with a high risk of VTE who may benefit from thromboprophylaxis.

Introduction Systemic lupus erythematosus (SLE) is a prototypic autoimmune disorder with a variable clinical course, ranging from mild to severe forms. It mainly occurs in women, especially those of fertile age. The aim of the study was to systematically analyze the associations of perinatal disease activity with adverse outcomes of Chinese patients with SLE and their off-spring. Material and methods Data of prenatal SLE patients and healthy pregnant woman admitted to our hospital during the period October 2001 to January 2018 were retrospectively collected, and the status of offspring of SLE patients was followed up in March 2020. Disease activity was evaluated by SLE disease activity index 2000 (SLEDAI-2k), and those with scores > 6 were defined as having active disease. Results In total, 198 deliveries of 194 SLE patients and 199 deliveries of healthy women were documented. Maternal and fetal adverse outcomes occurred in 74 (37.4%) and 90 (45.5%) deliveries of SLE patients, respectively, which were significantly higher than those of healthy subjects. Among SLE patients, the active group had higher rates of gestational hypertension (p < 0.001), reeclampsia/eclampsia (p < 0.001), low birth weight (p < 0.001), premature birth (p < 0.001) and fetal growth restriction (FGR) (p < 0.01) than the inactive group. Multivariate logistic analysis revealed that perinatal renal activity was associated with gestational hypertension (OR 4.43, p < 0.001), preeclampsia/ eclampsia (OR 9.14, p < 0.001), low birth weight (OR 2.24, p < 0.05) and premature birth (OR 4.20, p < 0.001). Compared with the general population, offspring of SLE patients had relatively high rates of eczema (50/142, 35.2%) and congenital heart disease (6/142, 4.2%), which were irrelevant to perinatal disease activity, but related to specific antibodies. Conclusions For perinatal women with SLE, renal activity is associated with a variety of adverse pregnancy outcomes. However, maternal perinatal dis�ease activity does not seem to affect the growth of their offspring

Abstract Studies on clinical features of systemic lupus erythematosus among different age-onset patients are lacking in China. This multicentre study aimed to systemically compare clinical manifestations, comorbidities, organ involvement, and laboratory findings among 797 Chinese juvenile-onset, adult-onset, and late-onset SLE (JSLE, ASLE, and LSLE) patients. They were classified into JSLE, ASLE, and LSLE groups if first diagnosed at < 18, 18–50, and > 50 years old, respectively. Chi-square test and analysis of variance were employed for categorical and continuous variables respectively. In younger-onset patients, the SLE Disease Activity Index 2000 score was significantly higher (JSLE vs. ASLE vs. LSLE = 17.43 ± 9.139 vs. 16.34 ± 8.163 vs. 14.08 ± 6.474, p = 0.031). Mucocutaneous symptoms (79.5% vs. 73.4% vs. 62.0%, p = 0.042), especially malar rash (76.1% vs. 66.1% vs. 53.5%, p = 0.011) occurred more frequently, and proteinuria rate was higher (54.5% vs. 56.3% vs. 36.6%, p = 0.007). In later-onset patients, cardiopulmonary involvement increased (11.4% vs. 24.3% vs. 29.6%, p = 0.012). In ASLE, hypoalbuminemia rate elevated (46.6% vs. 59.9% vs. 47.9%, p = 0.015). Our study demonstrated in a Chinese population that JSLE may be more active and suffer mucocutaneous disorders, while LSLE tended to suffer cardiopulmonary involvement at-onset. These findings may help identify treatment priorities when facing different age-onset SLE patients.

Abstract Gastric disease is a major health problem worldwide. Gastroscopy is the main method and the gold standard used to screen and diagnose many gastric diseases. However, several factors, such as the experience and fatigue of endoscopists, limit its performance. With recent advancements in deep learning, an increasing number of studies have used this technology to provide on-site assistance during real-time gastroscopy. This review summarizes the latest publications on deep learning applications in overcoming disease-related and nondisease-related gastroscopy challenges. The former aims to help endoscopists find lesions and characterize them when they appear in the view shed of the gastroscope. The purpose of the latter is to avoid missing lesions due to poor-quality frames, incomplete inspection coverage of gastroscopy, etc., thus improving the quality of gastroscopy. This study aims to provide technical guidance and a comprehensive perspective for physicians to understand deep learning technology in gastroscopy. Some key issues to be handled before the clinical application of deep learning technology and the future direction of disease-related and nondisease-related applications of deep learning to gastroscopy are discussed herein.

BackgroundAnti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with interstitial lung disease (anti-MDA5 DM-ILD) is a disease with high mortality. We sought to develop an effective and convenient prediction tool to estimate mortality risk in patients with anti-MDA5 DM-ILD and inform clinical decision-making early.MethodsThis prognostic study included Asian patients with anti-MDA5 DM-ILD hospitalized at the Nanjing Drum Hospital from December 2016 to December 2020. Candidate laboratory indicators were retrospectively collected. Patients hospitalized from 2016 to 2018 were used as the discovery cohort and applied to identify the optimal predictive features using a least absolute shrinkage and selection operator (LASSO) logistic regression model. A risk score was determined based on these features and used to construct the mortality risk prediction model in combination with clinical characteristics. Results were verified in a temporal validation comprising patients treated between 2019 and 2020. The primary outcome was mortality risk within one year. The secondary outcome was overall survival. The prediction model’s performance was assessed in terms of discrimination, calibration, and clinical usefulness.ResultsThis study included 127 patients, (72 men [56.7%]; median age, 54 years [interquartile range, 48-63 years], split into discovery (n = 87, 70%) and temporal validation (n=37, 30%) cohorts. Five optimal features were selected by LASSO logistic regression in the discovery cohort (n = 87) and used to construct a risk score, including lymphocyte counts, CD3+CD4+ T-cell counts, cytokeratin 19 fragment (CYFRA21-1), oxygenation index, and anti-Ro52 antibody. The retained predictive variables in the final prediction model were age, Heliotrope, fever, and risk score, and the most predictive factor was the risk score. The prediction model showed good discrimination (AUC: 0.915, 95% CI: 0.846–0.957), good calibration (Hosmer–Lemeshow test, P = 0.506; Brier score, 0.12), and fair clinical usefulness in the discovery cohort. The results were verified among patients in the temporal validation cohort (n = 38). We successfully divided patients into three risk groups with very different mortality rates according to the predictive score in both the discovery and validation cohorts (Cochran-Armitage test for trend, P < 0.001).ConclusionsWe developed and validated a mortality risk prediction tool with good discrimination and calibration for Asian patients with anti-MDA5 DM-ILD. This tool can offer individualized mortality risk estimation and inform clinical decision-making.

Minimally invasive medicine has become mainstream because of its crucial clinical significance in providing a low risk of postoperative complications, limited blood loss, short postoperative recovery time, and small sizes of associated physiological tissue wounds. Endoscopic navigation systems comprise a research hot spot in medical science and technology and are an essential means to achieve precision medicine and improve surgical operation safety. As a core component in endoscopic navigation during minimally invasive surgery, endoscopes play a critical role in disease diagnosis and treatment. The development of endoscopic vision technologies has resulted in a renewed drive to further develop endoscopic navigation systems. Multiple endoscopic optical imaging modalities provide data sources for endoscopic vision technology, including white-light endoscopy, contrast-enhanced imaging and technologies involving magnified observation. Endoscopic vision is a specific application of computer vision involving the use of endoscopes that include instrument tracking, endoscopic view expansion, and suspicious lesion tracking in the application of endoscopic navigation. These techniques help surgeons or surgical robots locate instruments and lesions and expand the field of view of the endoscope. Although these technologies have been applied to various clinical and pre-clinical diagnoses and treatments, the use and combination of these advanced technologies in endoscopic navigation system for specific clinical requirements remains challenging. This review performs a broad survey of advanced endoscopic vision technologies and their application in endoscopic navigation systems. Finally, we discuss the challenges and future directions in implementing and developing endoscopic navigation systems.

Abstract Surgeons face challenges in intraoperatively defining margin of brain tumors due to its infiltrative nature. Extracellular acidosis caused by metabolic reprogramming of cancer cells is a reliable marker for tumor infiltrative regions. Although the acidic margin‐guided surgery shows promise in improving surgical prognosis, its clinical transition is delayed by having the exogenous probes approved by the drug supervision authority. Here, an intelligent surface‐enhanced Raman scattering (SERS) navigation system delineating glioma acidic margins without administration of exogenous probes is reported. With assistance of this system, the metabolites at the tumor cutting edges can be nondestructively transferred within a water droplet to a SERS chip with pH sensitivity. Homemade deep learning model automatically processes the Raman spectra collected from the SERS chip and delineates the pH map of tumor resection bed with increased speed. Acidity correlated cancer cell density and proliferation level are demonstrated in tumor cutting edges of animal models and excised tissues from glioma patients. The overall survival of animal models post the SERS system guided surgery is significantly increased in comparison to the conventional strategy used in clinical practice. This SERS system holds the promise in accelerating clinical transition of acidic margin‐guided surgery for solid tumors with infiltrative nature.

The vast majority (>90%) of glioblastoma (GBM) patients belong to the isocitrate dehydrogenase 1 wild type (IDH1WT) group which exhibits a poor prognosis with a median survival of less than 15 months. This study demonstrated numerous immunosuppressive genes as well as β-catenin gene, pivotal for Wnt/β-catenin signaling, were upregulated in 206 IDH1WT glioma patients using the Chinese Glioma Genome Atlas (CGGA) database. The increase in microglia with an immunosuppressive phenotype and the overexpression of β-catenin protein were further verified in IDH1WT GBM patients and IDH1WT GL261 glioma allografts. Subsequently, we found that IDH1WT GL261 cell-derived conditioned medium activated Wnt/β-catenin signaling in primary microglia and triggered their transition to an immunosuppressive phenotype. Blocking Wnt/β-catenin signaling not only attenuated microglial polarization to the immunosuppressive subtype but also reactivated immune responses in IDH1WT GBM allografts by simultaneously enhancing cytotoxic CD8+ T cell infiltration and downregulating regulatory T cells. Positron emission tomography imaging demonstrated enhanced proinflammatory activities in IDH1WT GBM allografts after the blockade of Wnt signaling. Finally, gavage administration of a Wnt signaling inhibitor significantly restrained tumor proliferation and improved the survival of model mice bearing IDH1WT GBM allografts. Depletion of CD8+ T cells remarkably abrogated the therapeutic efficacy induced by the Wnt signaling inhibitor. Overall, the present work indicates that the crosstalk between IDH1WT glioma cells and immunosuppressive microglia is important in maintaining the immunosuppressive glioma microenvironment. Blocking Wnt/β-catenin signaling is a promising complement for IDH1WT GBM treatment by improving the hostile immunosuppressive microenvironment.

The camera is the main sensor of vison-based human activity recognition, and its high-precision calibration of distortion is an important prerequisite of the task. Current studies have shown that multi-parameter model methods achieve higher accuracy than traditional methods in the process of camera calibration. However, these methods need hundreds or even thousands of images to optimize the camera model, which limits their practical use. Here, we propose a novel point-to-point camera distortion calibration method that requires only dozens of images to get a dense distortion rectification map. We have designed an objective function based on deformation between the original images and the projection of reference images, which can eliminate the effect of distortion when optimizing camera parameters. Dense features between the original images and the projection of the reference images are calculated by digital image correlation (DIC). Experiments indicate that our method obtains a comparable result with the multi-parameter model method using a large number of pictures, and contributes a 28.5% improvement to the reprojection error over the polynomial distortion model.

Introduction: Systemic lupus erythematosus (SLE) is a prototypic autoimmune disorder with a variable clinical course, ranging from mild to severe forms. It mainly occurs in women, especially those of fertile age. The aim of the study was to systematically analyze the associations of perinatal disease activity with adverse outcomes of Chinese patients with SLE and their offspring. Material and methods: Data of prenatal SLE patients and healthy pregnant woman admitted to our hospital during the period October 2001 to January 2018 were retrospectively collected, and the status of offspring of SLE patients was followed up in March 2020. Disease activity was evaluated by SLE disease activity index 2000 (SLEDAI-2k), and those with scores > 6 were defined as having active disease. Results: In total, 198 deliveries of 194 SLE patients and 199 deliveries of healthy women were documented. Maternal and fetal adverse outcomes occurred in 74 (37.4%) and 90 (45.5%) deliveries of SLE patients, respectively, which were significantly higher than those of healthy subjects. Among SLE patients, the active group had higher rates of gestational hypertension (p < 0.001), preeclampsia/eclampsia (p < 0.001), low birth weight (p < 0.001), premature birth (p < 0.001) and fetal growth restriction (FGR) (p < 0.01) than the inactive group. Multivariate logistic analysis revealed that perinatal renal activity was associated with gestational hypertension (OR = 4.43, p < 0.001), preeclampsia/eclampsia (OR = 9.14, p < 0.001), low birth weight (OR = 2.24, p < 0.05) and premature birth (OR = 4.20, p < 0.001). Compared with the general population, offspring of SLE patients had relatively high rates of eczema (50/142, 35.2%) and congenital heart disease (6/142, 4.2%), which were irrelevant to perinatal disease activity, but related to specific antibodies. Conclusions: For perinatal women with SLE, renal activity is associated with a variety of adverse pregnancy outcomes. However, maternal perinatal disease activity does not seem to affect the growth of their offspring. [ABSTRACT FROM AUTHOR]