UroAngel: a single-kidney function prediction system based on computed tomography urography using deep learning.

BACKGROUND: Accurate estimation of the glomerular filtration rate (GFR) is clinically crucial for determining the status of obstruction, developing treatment strategies, and predicting prognosis in obstructive nephropathy (ON). We aimed to develop a deep learning-based system, named UroAngel, for non-invasive and convenient prediction of single-kidney function level. METHODS: We retrospectively collected computed tomography urography (CTU) images and emission computed tomography diagnostic reports of 520 ON patients. A 3D U-Net model was used to segment the renal parenchyma, and a logistic regression multi-classification model was used to predict renal function level. We compared the predictive performance of UroAngel with the Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations, and two expert radiologists in an additional 40 ON patients to validate clinical effectiveness. RESULTS: UroAngel based on 3D U-Net convolutional neural network could segment the renal cortex accurately, with a Dice similarity coefficient of 0.861. Using the segmented renal cortex to predict renal function stage had high performance with an accuracy of 0.918, outperforming MDRD and CKD-EPI and two radiologists. CONCLUSIONS: We proposed an automated 3D U-Net-based analysis system for direct prediction of single-kidney function stage from CTU images. UroAngel could accurately predict single-kidney function in ON patients, providing a novel, reliable, convenient, and non-invasive method.

[Improvement effect of cinnamaldehyde on reserpine-induced Parkinson's disease rat model].

In order to study the neuroprotective mechanism of cinnamaldehyde on reserpine-induced Parkinson's disease(PD) rat models, 72 male Wistar rats were randomly divided into blank group, model group, Madopar group, and cinnamaldehyde high-, medium-, and low-dose groups. Except for the blank group, the other groups were intraperitoneally injected with reserpine of 0.1 mg·kg~(-1) once every other morning, and cinnamaldehyde and Madopar solutions were gavaged every afternoon. Open field test, rotarod test, and oral chewing movement evaluation were carried out in the experiment. The brain was taken and fixed. The positive expression of dopamine receptor D1(DRD1) was detected by TSA, and the changes in neurotransmitters such as dopamine(DA) and 3,4-dihydroxyphenylacetic acid(DOPAC) in the brain were detected by enzyme-linked immunosorbent assay(ELISA). The protein and mRNA expression levels of tyrosine hydroxylase(TH) and α-synuclein(α-Syn) in substantia nigra(SN) were detected by RT-PCR and Western blot. The results showed that after the injection of reserpine, the hair color of the model group became yellow and dirty; the arrest behavior was weakened, and the body weight was reduced. The spontaneous movement and exploration behavior were reduced, and the coordination exercise ability was decreased. The number of oral chewing was increased, but the cognitive ability was decreased, and the proportion of DRD1 positive expression area in SN was decreased. The expression of TH protein and mRNA was down-regulated, and that of α-Syn protein and mRNA was up-regulated. After cinnamaldehyde intervention, it had an obvious curative effect on PD model animals. The spontaneous movement behavior, the time of staying in the rod, the time of movement, the distance of movement, and the number of standing times increased, and the number of oral chewing decreased. The proportion of DRD1 positive expression area in SN increased, and the protein and mRNA expression levels of α-Syn were down-regulated. The protein and mRNA expression levels of TH were up-regulated. In addition, the levels of DA, DOPAC, and homovanillic acid(HVA) neurotransmitters in the brain were up-regulated. This study can provide a new experimental basis for clinical treatment and prevention of PD.

The SUPER reporting guideline suggested for reporting of surgical technique.

Background: Existing reporting guidelines pay insufficient attention to the detail and comprehensiveness reporting of surgical technique. The Surgical techniqUe rePorting chEcklist and standaRds (SUPER) aims to address this gap by defining reporting standards for surgical technique. The SUPER guideline intends to apply to articles that encompass surgical technique in any study design, surgical discipline, and stage of surgical innovation. Methods: Following the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network approach, 16 surgeons, journal editors, and methodologists reviewed existing reporting guidelines relating to surgical technique, reviewed papers from 15 top journals, and brainstormed to draft initial items for the SUPER. The initial items were revised through a three-round Delphi survey from 21 multidisciplinary Delphi panel experts from 13 countries and regions. The final SUPER items were formed after an online consensus meeting to resolve disagreements and a three-round wording refinement by all 16 SUPER working group members and five SUPER consultants. Results: The SUPER reporting guideline includes 22 items that are considered essential for good and informative surgical technique reporting. The items are divided into six sections: background, rationale, and objectives (items 1 to 5); preoperative preparations and requirements (items 6 to 9); surgical technique details (items 10 to 15); postoperative considerations and tasks (items 16 to 19); summary and prospect (items 20 and 21); and other information (item 22). Conclusions: The SUPER reporting guideline has the potential to guide detailed, comprehensive, and transparent surgical technique reporting for surgeons. It may also assist journal editors, peer reviewers, systematic reviewers, and guideline developers in the evaluation of surgical technique papers and help practitioners to better understand and reproduce surgical technique. Trial Registration: https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-other-study-designs/#SUPER.

Clinical characteristics of bloodstream infections in adult patients with solid tumours and a nomogram for mortality prediction: a 5-year case-controlled retrospective study in a tertiary-level hospital.

Background: Bloodstream infections (BSIs) are one of the leading causes of death in cancer patients. Nevertheless, the risk factors of BSIs in solid tumors have rarely been ascertained adequately. Methods: We conducted a single-center case-controlled retrospective study from 2017 to 2021 among adults with solid tumors in a tertiary-level hospital. The BSIs and control group were matched by the propensity score matching method. We found independent risk factors of occurrence and death of BSIs using univariate and multivariate regression analysis. Additionally, a nomogram was constructed to predict the risk of mortality in BSIs. Results: Of 602 patients with solid tumors in the study period, 186 had BSIs and 416 had non-BSIs. The incidence of BSIs was 2.0/1,000 admissions (206/102,704), and the 30-day mortality rate was 18.8% (35/186). Compared to the control group, the BSIs had longer hospital stays (24.5 days vs. 20.0 days), and higher frequency complicating with organ failure (10.5% vs. 2.4%), nephropathy (19.6% vs. 3.8%), comorbidities≥3 (35.5% vs. 20.0%), and liver-biliary-pancreatic infections (15.6% vs. 5.3%) (all P<0.001). Among the 186 patients with BSIs, 35 died within 30 days after BSIs. Gram-negative bacteria were the most frequent microorganisms (124/192, 64.6%). Liver cancer, organ failure, a high level of lactate dehydrogenase and septic shock were the independent hazardous factors for death of BSIs. What's more, a nomogram was constructed to predict the 30-day survival rate of BSIs, which was proved to have good accuracy (AUC: 0.854; 95% confidence interval: 0.785~0923) and consistency. Conclusion: Being aware of the risk factors of BSIs redounds to take preventive measures to reduce the incidence and death of BSIs.

The SUPER reporting guideline suggested for reporting of surgical technique: explanation and elaboration.

Background: Surgical technique plays an essential role in achieving good health outcomes. However, the quality of surgical technique reporting remains heterogeneous. Reporting checklists could help authors to describe the surgical technique more transparently and effectively, as well as to assist reviewers and editors evaluate it more informatively, and promote readers to better understand the technique. We previously developed SUPER (surgical technique reporting checklist and standards) to assist authors in reporting their research that contains surgical technique more transparently. However, further explanation and elaboration of each item are needed for better understanding and reporting practice. Methods: We searched surgical literature in PubMed, Google Scholar and journal websites published up to January 2023 to find multidiscipline examples in various article types for each SUPER item. Results: We explain the 22 items of the SUPER and provide rationales item by item alongside. We provide 69 examples from 53 literature that present optimal reporting of the 22 items. Article types of examples include pure surgical technique, and case reports, observational studies and clinical trials that contain surgical technique. Examples are multidisciplinary, including general surgery, orthopaedical surgery, cardiac surgery, thoracic surgery, gastrointestinal surgery, neurological surgery, oncogenic surgery, and emergency surgery etc. Conclusions: Along with SUPER article, this explanation and elaboration file can promote deeper understanding on the SUPER items. We hope that the article could further guide surgeons and researchers in reporting, and assist editors and peer reviewers in reviewing manuscripts related to surgical technique.

Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study.

BACKGROUND: Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. We aimed to develop and validate a weakly-supervised deep learning model to predict LNM status from digitized histopathological slides in MIBC. METHODS: We trained a multiple instance learning model with an attention mechanism (namely SBLNP) from a cohort of 323 patients in the TCGA cohort. In parallel, we collected corresponding clinical information to construct a logistic regression model. Subsequently, the score predicted by the SBLNP was incorporated into the logistic regression model. In total, 417 WSIs from 139 patients in the RHWU cohort and 230 WSIs from 78 patients in the PHHC cohort were used as independent external validation sets. RESULTS: In the TCGA cohort, the SBLNP achieved an AUROC of 0.811 (95% confidence interval [CI], 0.771-0.855), the clinical classifier achieved an AUROC of 0.697 (95% CI, 0.661-0.728) and the combined classifier yielded an improvement to 0.864 (95% CI, 0.827-0.906). Encouragingly, the SBLNP still maintained high performance in the RHWU cohort and PHHC cohort, with an AUROC of 0.762 (95% CI, 0.725-0.801) and 0.746 (95% CI, 0.687-0.799), respectively. Moreover, the interpretability of SBLNP identified stroma with lymphocytic inflammation as a key feature of predicting LNM presence. CONCLUSIONS: Our proposed weakly-supervised deep learning model can predict the LNM status of MIBC patients from routine WSIs, demonstrating decent generalization performance and holding promise for clinical implementation.

A Weakly Supervised Deep Learning Model and Human-Machine Fusion for Accurate Grading of Renal Cell Carcinoma from Histopathology Slides.

(1) Background: The Fuhrman grading (FG) system is widely used in the management of clear cell renal cell carcinoma (ccRCC). However, it is affected by observer variability and irreproducibility in clinical practice. We aimed to use a deep learning multi-class model called SSL-CLAM to assist in diagnosing the FG status of ccRCC patients using digitized whole slide images (WSIs). (2) Methods: We recruited 504 eligible ccRCC patients from The Cancer Genome Atlas (TCGA) cohort and obtained 708 hematoxylin and eosin-stained WSIs for the development and internal validation of the SSL-CLAM model. Additionally, we obtained 445 WSIs from 188 ccRCC eligible patients in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) cohort as an independent external validation set. A human-machine fusion approach was used to validate the added value of the SSL-CLAM model for pathologists. (3) Results: The SSL-CLAM model successfully diagnosed the five FG statuses (Grade-0, 1, 2, 3, and 4) of ccRCC, and achieved AUCs of 0.917 and 0.887 on the internal and external validation sets, respectively, outperforming a junior pathologist. For the normal/tumor classification (Grade-0, Grade-1/2/3/4) task, the SSL-CLAM model yielded AUCs close to 1 on both the internal and external validation sets. The SSL-CLAM model achieved a better performance for the two-tiered FG (Grade-0, Grade-1/2, and Grade-3/4) task, with AUCs of 0.936 and 0.915 on the internal and external validation sets, respectively. The human-machine diagnostic performance was superior to that of the SSL-CLAM model, showing promising prospects. In addition, the high-attention regions of the SSL-CLAM model showed that with an increasing FG status, the cell nuclei in the tumor region become larger, with irregular contours and increased cellular pleomorphism. (4) Conclusions: Our findings support the feasibility of using deep learning and human-machine fusion methods for FG classification on WSIs from ccRCC patients, which may assist pathologists in making diagnostic decisions.

Machine Learning Quantified Tumor-Stroma Ratio Is an Independent Prognosticator in Muscle-Invasive Bladder Cancer.

Although the tumor-stroma ratio (TSR) has prognostic value in many cancers, the traditional semi-quantitative visual assessment method has inter-observer variability, making it impossible for clinical practice. We aimed to develop a machine learning (ML) algorithm for accurately quantifying TSR in hematoxylin-and-eosin (H&E)-stained whole slide images (WSI) and further investigate its prognostic effect in patients with muscle-invasive bladder cancer (MIBC). We used an optimal cell classifier previously built based on QuPath open-source software and ML algorithm for quantitative calculation of TSR. We retrospectively analyzed data from two independent cohorts to verify the prognostic significance of ML-based TSR in MIBC patients. WSIs from 133 MIBC patients were used as the discovery set to identify the optimal association of TSR with patient survival outcomes. Furthermore, we performed validation in an independent external cohort consisting of 261 MIBC patients. We demonstrated a significant prognostic association of ML-based TSR with survival outcomes in MIBC patients (p < 0.001 for all comparisons), with higher TSR associated with better prognosis. Uni- and multivariate Cox regression analyses showed that TSR was independently associated with overall survival (p < 0.001 for all analyses) after adjusting for clinicopathological factors including age, gender, and pathologic stage. TSR was found to be a strong prognostic factor that was not redundant with the existing staging system in different subgroup analyses (p < 0.05 for all analyses). Finally, the expression of six genes (DACH1, DEEND2A, NOTCH4, DTWD1, TAF6L, and MARCHF5) were significantly associated with TSR, revealing possible potential biological relevance. In conclusion, we developed an ML algorithm based on WSIs of MIBC patients to accurately quantify TSR and demonstrated its prognostic validity for MIBC patients in two independent cohorts. This objective quantitative method allows application in clinical practice while reducing the workload of pathologists. Thus, it might be of significant aid in promoting precise pathology services in MIBC.

Reporting guidelines for surgical technique could be improved: a scoping review and a call for action.

OBJECTIVES: To identify reporting guidelines related to surgical technique and propose recommendations for areas that require improvement. STUDY DESIGN AND SETTING: A protocol-guided scoping review was conducted. A literature search of MEDLINE, the EQUATOR Network Library, Google Scholar, and Networked Digital Library of Theses and Dissertations was conducted to identify surgical technique reporting guidelines published up to December 31, 2021. RESULTS: We finally included 55 surgical technique reporting guidelines, vascular surgery (n = 18, 32.7%) was the most common among the clinical specialties covered. The included guidelines generally showed a low degree of international and multidisciplinary cooperation. Few guidelines provided a detailed development process (n = 14, 25.5%), conducted a systematic literature review (n = 13, 23.6%), used the Delphi method (n = 4, 7.3%), or described post-publication strategy (n = 6, 10.9%). The vast majority guidelines focused on the reporting of intraoperative period (n = 50, 90.9%). However, of the guidelines requiring detailed descriptions of surgical technique methodology (n = 43, 78.2%), most failed to provide guidance on what constitutes an adequate description. CONCLUSION: Our study demonstrates significant deficiencies in the development methodology and practicality of reporting guidelines for surgical technique. A standardized reporting guideline that is developed rigorously and focuses on details of surgical technique may serve as a necessary impetus for change.

Accurate Diagnosis and Survival Prediction of Bladder Cancer Using Deep Learning on Histological Slides.

(1) Background: Early diagnosis and treatment are essential to reduce the mortality rate of bladder cancer (BLCA). We aimed to develop deep learning (DL)-based weakly supervised models for the diagnosis of BLCA and prediction of overall survival (OS) in muscle-invasive bladder cancer (MIBC) patients using whole slide digitized histological images (WSIs). (2) Methods: Diagnostic and prognostic models were developed using 926 WSIs of 412 BLCA patients from The Cancer Genome Atlas cohort. We collected 250 WSIs of 150 BLCA patients from the Renmin Hospital of Wuhan University cohort for external validation of the models. Two DL models were developed: a BLCA diagnostic model (named BlcaMIL) and an MIBC prognostic model (named MibcMLP). (3) Results: The BlcaMIL model identified BLCA with accuracy 0.987 in the external validation set, comparable to that of expert uropathologists and outperforming a junior pathologist. The C-index values for the MibcMLP model on the internal and external validation sets were 0.631 and 0.622, respectively. The risk score predicted by MibcMLP was a strong predictor independent of existing clinical or histopathologic indicators, as demonstrated by univariate Cox (HR = 2.390, p < 0.0001) and multivariate Cox (HR = 2.414, p < 0.0001) analyses. The interpretability of DL models can help in the analysis of critical regions associated with tumors to enrich the information obtained from WSIs. Furthermore, the expression of six genes (ANAPC7, MAPKAPK5, COX19, LINC01106, AL161431.1 and MYO16-AS1) was significantly associated with MibcMLP-predicted risk scores, revealing possible potential biological correlations. (4) Conclusions: Our study developed DL models for accurately diagnosing BLCA and predicting OS in MIBC patients, which will help promote the precise pathological diagnosis of BLCA and risk stratification of MIBC to improve clinical treatment decisions.

Quantitative Assessment of Tumor-Infiltrating Lymphocytes Using Machine Learning Predicts Survival in Muscle-Invasive Bladder Cancer.

(1) Purpose: Although assessment of tumor-infiltrating lymphocytes (TILs) has been acknowledged to have important predictive prognostic value in muscle-invasive bladder cancer (MIBC), it is limited by inter- and intra-observer variability, hampering widespread clinical application. We aimed to evaluate the prognostic value of quantitative TILs score based on a machine learning (ML) algorithm to identify MIBC patients who might benefit from immunotherapy or the de-escalation of therapy. (2) Methods: We constructed an artificial neural network classifier for tumor cells, lymphocytes, stromal cells, and "ignore" cells from hematoxylin-and-eosin-stained slide images using the QuPath open source software. We defined four unique TILs variables based on ML to analyze TILs measurements. Pathological slide images from 133 MIBC patients were retrospectively collected as the discovery set to determine the optimal association of ML-read TILs variables with patient survival outcomes. For validation, we evaluated an independent external validation set consisting of 247 MIBC patients. (3) Results: We found that all four TILs variables had significant prognostic associations with survival outcomes in MIBC patients (p < 0.001 for all comparisons), with higher TILs score being associated with better prognosis. Univariate and multivariate Cox regression analyses demonstrated that electronic TILs (eTILs) variables were independently associated with overall survival after adjustment for clinicopathological factors including age, sex, and pathological stage (p < 0.001 for all analyses). Results analyzed in different subgroups showed that the eTILs variable was a strong prognostic factor that was not redundant with pre-existing clinicopathological features (p < 0.05 for all analyses). (4) Conclusion: ML-driven cell classifier-defined TILs variables were robust and independent prognostic factors in two independent cohorts of MIBC patients. eTILs have the potential to identify a subset of high-risk stage II or stage III-IV MIBC patients who might benefit from adjuvant immunotherapy.

Off-label use of drugs in pediatrics: a scoping review.

To explore the current state of research on off-label drug use in children and identify the existing research gaps in this topic. Six literature databases were searched to identify studies focusing exclusively on off-label drug use in children (aged < 18 years) published in Chinese or English between 2016 and 2021. We also searched clinicaltrials.gov for pediatric clinical trials conducted in the same period and compared the numbers of studies on off-label use and clinical trials for the most commonly reported drugs and drug types. Our search revealed 568 studies on off-label drug use. Almost half of the studies (n = 240) were cross-sectional. A total of 212 specific drugs or drug types were addressed in 361 studies, the most frequent being antipsychotic agents (n = 12), dexmedetomidine (n = 10), and rituximab (n = 8). Antipsychotic agents were also the most common type of drug examined in clinical trials in children. We identified a total of 435 different types of off-label use, the top three being unapproved indication (n = 157), population (n = 96), or age (n = 36). Only about one-third of the studies reported collecting informed consent (n = 195) or having ethics committee approval (n = 166).    Conclusions: Off-label use of antipsychotics in children is widely reported in the literature. We suggest pediatric researchers to consider the number of studies on off-label use and existing clinical trials on different drugs when selecting target drugs for new studies and systematic reviews. What is Known: • There exist a large number of studies on off-label drug use in children. What is New: • This is the first scoping review of studies on off-label drug use in children. • Off-label use of antipsychotic agents is widely reported.

Prognostic value of high FOXO3a expression in patients with solid tumors: A meta-analysis and systematic review.

BACKGROUND: FOXO3a (previously termed FKHRL1), plays an evolutionarily conserved role in the control of biological process, including DNA damage, apoptosis, and cell cycle regulation. However, the role of FOXO3a in tumors remains controversial. This meta-analysis was conducted to evaluate the prognostic value of FOXO3a expression in patients with solid tumors. METHODS: A systematic literature search of the PubMed, Web of Science, Embase, and Cochrane Library databases was performed. Eligible publications on FOXO3a and cancer prognosis were collected and screened according to the eligibility criteria. The combined odds ratios (ORs) or hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) were used to assess the prognostic value of FOXO3a. Stata 12.0 software was used for statistical analysis. RESULTS: A total of 4058 patients from 21 articles on a variety of solid tumors were included. Meta-analysis showed that the increased FOXO3a expression level was associated with longer overall survival (HR = 0.62; 95% CI: 0.46-0.85). The pooled ORs indicated high expression level of FOXO3a in tumors was significantly associated with lymph node metastasis (OR = 0.46; 95% CI: 0.30-0.71), TNM stage (OR = 0.37; 95% CI: 0.25-0.54), tumor differentiation (OR = 0.46; 95% CI: 0.26-0.80), distant metastasis (OR = 0.44; 95% CI: 0.32-0.61), and age (OR = 1.28; 95% CI: 1.08-1.51). However, we did not observe a significant correlation between the high expression of FOXO3a and sex or tumor size. CONCLUSIONS: The high expression level of FOXO3a was associated with better clinical outcomes in solid tumors. FOXO3a may therefore serve as a potential prognostic biomarker and a promising molecular target.

Hydraulic mechanisms of the uneven enrichment of soil organic carbon in sediments during rain-induced overland flow.

Organic carbon (OC) can be unevenly enriched in different-sized sediment particles under low-intensity, rain-induced overland flows, but its hydraulic mechanisms are not completely understood. Hence, in this study, the hydraulic transport mechanisms of unevenly enriched OC between different-sized sediment particles were investigated through simulated rainfall experiments at gradients of 5°, 10°, and 15° and typical regional rainfall intensities of 45, 90, and 120 mm h-1. Results showed that the critical flow velocity of aggregate transport through loess soil was approximately 0.08 m s-1. When the flow velocity was larger than this critical value, the aggregate loss amount increased quickly and exponentially. Flow velocities lower than 0.08 m s-1 were determined to be essential conditions for uneven OC enrichment between sediment particles. At such velocities, even when the runoff depth was greater than 0.0018 m, the enrichment ratio of soil organic carbon (SOC; ERoc) values in all size classes of sediment particles was larger than 1.0. Small runoff depths caused preferential OC enrichment in silt and clay, whereas large runoff depths promoted OC enrichment in the >0.25 mm size class of sediment particles. The critical flow velocity and transport way differ between these high-OC-concentration clay and silt and large light organic particles. The interaction between flow velocity and runoff depth on ERocs in <0.05 mm particles was larger than that of >0.05 mm particles. Under the transport limit erosion, the flow velocity and stream power positively correlated with uneven ERocs in different size sediment particles through distinct laws. Slope and rainfall intensity could not be ignored in predicting uneven OC enrichment in sediments by interacting with hydraulic factor and effecting aggregate stripping, respectively. Hydraulic factors mainly affected the uneven OC enrichment by controlling particle selective detachment and transport process. Owing to the different hydraulic mechanisms of OC enrichment in different size particles, the obtained regression functions for uneven OC enrichment could be divided into two types. One was for calculating the OC concentrations in sediment particles with sizes of <2 mm (R2 > 0.844, P < 0.005), and the other was for calculating the OC concentrations in large macroaggregates (>2 mm; R2 = 0.805, P < 0.005). The findings provide an important reference for understanding SOC transport mechanisms and its mineralization potential under the effect of water erosion and improving SOC dynamic models.

Developing the surgical technique reporting checklist and standards: a study protocol.

BACKGROUND: Standardized and transparent reporting of surgical technique is the cornerstone of effective dissemination, implementation and improvement. However, current reporting of surgical techniques is inadequate. The existing guidelines potentially applied to guide surgical technique reporting are with a minimal highlight of the surgical technique, lack requirements explaining what extent and dimensions need to be described in detail, or are unlikely to extrapolate to a wide range of surgical techniques. This study aims to formulate a rigorous protocol to develop a surgical technique reporting checklist and standards (SUPER) that defines what a clear, comprehensive and detailed surgical technique report should be contained. METHODS: This protocol is designed following the classic guidance for developing reporting guidelines recommended by the EQUATOR network. RESULTS: The development team will consist of surgeons (~80%), methodologists, and journal editors. The draft checklist sources will include a scoping review of existing reporting guidelines related to surgical technique, surgical technique articles from 15 top journals published in the last year, and brainstorming by the multidisciplinary development team. The final SUPER checklist will be formed after three rounds of Delphi surveys, one round of face-to-face meeting, and a month-long pilot test. The SUPER checklist will be published as open-access and be used in combination with existing reporting guidelines related to surgical techniques (e.g., IDEAL). This protocol will steer the SUPER checklist's development, allowing us to further elaborate surgical technique reporting for all surgical specialties, and enabling a more favorable experience for surgeons, nurses, medical students, residents, editors, and reviewers. TRIAL REGISTRATION: This trial is registered at the EQUATOR network on December 18th, 2020. Available at: https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-other-study-designs/.

Evidence on reporting guidelines for surgical technique in clinical disciplines: a scoping review protocol.

BACKGROUND: The reporting of surgical techniques is of mixed quality, with most at a very minimal level. Reporting guidelines that could be applied to guide surgical technique reporting vary in methodology for development, discipline coverage, dimension coverage and detail requested. However, a scoping review that could indicate the gaps and efforts needed in surgical technique reporting guidelines is lacking and warranted. This study aims to design a methodological rigour protocol to guide the development of a scoping review of surgical technique reporting guidelines. METHODS: This protocol is designed following the 2020 manual proposed by the Joanna Briggs Institute. To further ensure the soundness of the protocol, we also included multidisciplinary professionals (including methodologists, clinicians, and journal editors) to refine the protocol. DISCUSSION: Seven key steps for developing the scoping review are identified and presented in detail, including (I) identifying the research questions; (II) inclusion criteria; (III) search strategy; (IV) source of evidence selection; (V) data extraction; (VI) analysis of the evidence; and (VII) presentation of the results. Guided by this protocol, the subsequent scoping review will inform us the overview of surgical technique reporting guidelines and precisely guide our direction and next steps in improving surgical technique reporting guidelines. TRIAL REGISTRATION: This protocol is not registered as the PROSPERO database only accepts registration of systematic review protocols while does not accept registration of scoping review protocols.

The pathogenic characteristics and influencing factors of health care-associated infection in elderly care center under the mode of integration of medical care and elderly care service: A cross-sectional study.

ABSTRACT: The aim of this study was to analyze the distribution of pathogenic bacteria in hospitalized patients in elderly care centers under the mode of integration of medical care and elderly care service, and explore the influencing factors to reduce the health care-associated infection rate of hospitalized patients.A total of 2597 inpatients admitted to elderly care centers from April 2018 to December 2019 were included in the study. The etiology characteristics of health care-associated infections (HCAI) was statistically analyzed, univariate analysis, and multivariate logistic regression analysis method were used to analyze the influencing factors of HCAI.A total of 98 of 2597 inpatients in the elderly care centers had HCAI, and the infection rate was 3.77%. The infection sites were mainly in the lower respiratory tract and urinary tract, accounting for 53.92% and 18.63%, respectively. A total of 53 pathogenic bacteria were isolated, 43 of which (81.13%) were Gram-negative, mainly Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae, which respectively accounted for 24.53, 16.98, and 13.21%. 9 (16.98%) strains were Gram-positive, mainly Staphylococcus aureus and Enterococcus faecium, respectively accounting for 7.55 and 5.66%. Only 1 patient (1.89%) had a fungal infection. Multivariate logistic regression analysis indicated that total hospitalization days, antibiotic agents used, days of central line catheter, use of urinary catheter and diabetes were independent risk factors of nosocomial infection in elderly care centers (P < .05).Many factors can lead to nosocomial infections in elderly care centers. Medical staff should take effective intervention measures according to the influencing factors to reduce the risk of infection in elderly care facilities.

The high expression of CHD1L and its clinical significance in human solid tumors: A meta-analysis.

BACKGROUND: Chromodomain helicase DNA-binding protein 1-like (CHD1L) is an oncogene. It was cloned from 1q21 chromosome region of hepatocellular carcinoma in 1991. CHD1L is up-regulated in many kinds of cancers and is involved in the carcinogenesis and development of tumors. More and more studies have shown that over-expression of CHD1L is associated with poor prognosis of tumors. The purpose of this study was to evaluate the prognostic value of CHD1L in human solid tumors. METHODS: The key words in the database of PubMed, Web of Science, Embase, Cochrane library, and TCGA were searched for systematic literature retrieval. We collected relevant articles and data about CHD1L and prognosis of cancer and screened them according to the eligible criteria to evaluate the prognostic value of CHD1L in cancer patients. Then Stata SE12.0 software is used to analyze the data. RESULTS: In our meta-analysis, 2720 patients with a total of 15 articles involving multiple types of tumors showed that high expression levels of CHD1L were associated with shorter overall survival (OS) (hazard ratio  = 2.21, 95% confidence interval [CI]: (1.49-3.30)] and (hazard ratio  = 1.16, 95% CI: (1.01-1.32)] in the TCGA database, in addition, the pooled odds ratios (ORs) indicated high expression levels of CHD1L in tumors significantly are associated with TNM stage (OR = 1.61, 95% CI: 1.01-2.55, P < .05), tumor size (OR = 1.38, 95% CI: 1.07-1.78, P < .05), tumor differentiation (OR = 2.13, 95% CI: 1.43-3.16, P < .05), and distant metastasis (OR = 1.86, 95% CI: 1.45-2.39 P < .05). However, we did not observe a significant correlation between the high expression of CHD1L and age, gender. CONCLUSION: The high expression of CHD1L is associated with poor OS as well as related to tumor differentiation, tumor size, and distant metastasis, which can be served as a prognostic marker and a potential predictor of clinical pathology in human solid tumors.

Could saline irrigation clear all residual common bile duct stones after lithotripsy? A self-controlled prospective cohort study.

BACKGROUND: A previous study showed that irrigation with 100 mL saline reduced residual common bile duct (CBD) stones, which potentially cause recurrent stones after endoscopic retrograde cholangiopancreatography. AIM: To determine whether saline irrigation can improve CBD clearance after lithotripsy. METHODS: This prospective self-controlled study enrolled patients receiving mechanical lithotripsy for large (> 1.2 cm) CBD stones. After occlusion cholangiography confirmed CBD stone clearance, peroral cholangioscopy (POC) was performed to determine clearance scores based on the number of residual stones. The amounts of residual stones spotted via POC were graded on a 5-point scale (score 1, worst; score 5, best). Scores were documented after only stone removal (control) and after irrigation with 50 mL and 100 mL saline, respectively. The stone composition was analyzed using infrared spectroscopy. RESULTS: Between October 2018 and January 2020, 47 patients had CBD clearance scores of 2.4 ± 1.1 without saline irrigation, 3.5 ± 0.7 with 50 mL irrigation, and 4.6 ± 0.6 with 100 mL irrigation (P < 0.001). Multivariate analysis showed that CBD diameter > 15 mm [odds ratio (OR) = 0.08, 95% confidence interval (CI): 0.01-0.49; P = 0.007] and periampullary diverticula (PAD) (OR = 6.51, 95%CI: 1.08-39.21; P = 0.041) were independent risk factors for residual stones. Bilirubin pigment stones constituted the main residual stones found in patients with PAD (P = 0.004). CONCLUSION: Irrigation with 100 mL of saline may not clear all residual CBD stones after lithotripsy, especially in patients with PAD and/or a dilated (> 15 mm) CBD. Pigment residual stones are soft and commonly found in patients with PAD. Additional saline irrigation may be required to remove retained stones.

Bacteria are more sensitive than fungi to moisture in eroded soil by natural grass vegetation restoration on the Loess Plateau.

Community composition and respiration rates of bacterial and fungal communities from grass-covered eroded soils of the Loess Plateau responded differently to constant and increasing soil moisture (SM) regimes. The soils were incubated with SM contents of 5%, 30%, and 45% and with wetting processes in the SM ranges from 5% to 30% (5-30%), from 5% to 30% to 45% (5-30-45%) and from 30% to 45% (30-45%); high-throughput sequencing and co-occurrence network analyses were applied to investigate the different responses of the bacterial and fungal communities to changed SM. Our results showed that bacteria were more sensitive than fungi to changes in SM. The dominant bacterial communities converted from Actinobacterial to Proteobacteria and Acidobacteria in 5-30-45% wetting procedure. Firmicutes preferred wet condition and exhibited slow resilience. However, no difference was observed for the Chloroflexi communities across any sample. The obvious difference in fungal composition was found between the wetting process of 5-30-45% and constant 45% SM. During the 5-30-45% procedure, the respiration rate was higher than that at 30-45% procedure after incubation for 24 days. The respiration rate in 5-30% procedure was lower than that of 5-30-45% process after incubation for 16-27 days. The larger effects on bacterial response than on fungi were verified in network analysis. Multiple stepwise regression analysis showed that 84.40% of the variation in bacterial richness and diversity as well as fungal diversity can be explained by changes in soil respiration rate in response to wetting procedure. Understanding the response of difference between bacterial and fungal community composition, phylum-levels networks and respiration rate to changes in SM is essential for the management of plant-soil-water relationship in the ecosystem after natural vegetation restoration on the Loess Plateau.