The summary of finding (SoF) table for network meta-analysis (NMA) was developed by the GRADE working group to facilitate and consolidate understanding NMA findings and GRADE certainty of evidence. This paper introduces the development process, the structure of NMA-SoF and limitations. A NMA publication was presented as an example to comprehensively illustrate the application of the NMA-SoF table.
ObjectiveTo understand the current status of oral frailty in older patients with colostomy, and analyze the factors affecting oral frailty. MethodsRetrospective analysis of older patients with colostomy who visited the gastroenterology outpatient department of Affiliated Provincial Hospital of Shandong First Medical University from May 2023 to December 2023 as research subjects. The questionnaire survey was conducted using the general data questionnaire, oral frailty index-8 (OFI-8), the edmonton frail scale (EFS), and the nutritional risk screening score 2002. According to the OFI-8 score, the patients were divided into oral frailty group and non-oral frailty group, and the two-classified logistic regression model was used for multi-factor analysis to explore the factors affecting the oral frailty of older patients. ResultsA total of 283 survey subjects were collected, and the incidence of oral frailty in older patients was 66.4% (188/283). Multi-factor analysis results show that old age [OR=1.181, 95% CI(1.015, 1.373), P=0.032], history of smoking [OR=2.721, 95%CI(1.122, 6.599), P=0.027], history of alcohol [OR=2.878, 95%CI(1.185, 6.991), P=0.020], dentures [OR=3.173, 95%CI(1.297, 7.759), P=0.011], postoperative oral diseases≥2 [OR=5.802, 95%CI(1.911, 17.615), P=0.002], nutritional risk [OR=2.744, 95%CI(1.033, 7.284), P=0.043], high EFS score [OR=1.823, 95% CI(1.309, 2.538), P<0.001], the type of stoma is permanent [OR=2.659, 95%CI(1.126, 6.275), P=0.026] is a risk factor for oral frailty in older patients with colostomy. ConclusionThe incidence of oral frailty in older patients with colostomy is relatively high. We should pay more attention to the patient's oral frailty, and implement precise intervention measures for high-risk factors to prevent the occurrence of oral frailty or improve the condition of oral frailty.
Objective To study the relation between the pathogenesis of gallstone and blood lipid and protein.Methods Then indexes of blood lipid and protein in 204 cases of gallstone patients were measured and analysed by statistical software SPSS. Results There was a significant difference between the gallstone group and control in the value of proalbumin, total cholesterol, high density lipoprotein and carrier protein B (Ｐ＜0.01), the value of total protein, triglyceride, low density lipoprotein cholesterol, very low density lipoprotein cholesterol and carrier protein A1 were higher than those in the control (Ｐ＜0.05). Conclusion The indexes mentioned above may play an important role in the gallstone formation.
【Abstract】Objective To explore the changes of expression of AFP mRNA in human hepatocellular carcinoma （HCC） tissues after oral Xeloda therapy.Methods Total RNA was extracted from HCC tissue samples collect after operation and nested reverse transcription polymerase chain reaction （RT-nested PCR） assay was performed to determine the expression of AFP mRNA in this study.Results The final product of AFP mRNA amplified by RT-PCR was 174 bp and by RT-nested PCR was 101 bp. The AFP mRNA is positive in 12 of 21 patients (positive rate 57.14%) amplified by RT-nested PCR assay in Xeloda treatment group which is much lower than control group: 18 of 20 patients (positive rate 90.00%),P＜0.05.The serum AFP value of Xeloda treatment group 〔(23.2±12.8) μg/L〕 is much lower than that of control group 〔(39.6±24.3) μg/L〕 four weeks after operation (P＜0.05). However, There was no difference between two groups in serum AFP value before operation.Conclusion Xeloda can effectively suppress the expression of AFP mRNA in human HCC tissues and lower it’s product serum AFP value.The clinical application of Xeloda in HCC patients deserve further study.
Randomized controlled trials are the gold standard for evaluating the effects of medical interventions, primarily providing estimates of the average effect of an intervention in the overall study population. However, there may be significant differences in the effect of the same intervention across sub-populations with different characteristics, that is, treatment heterogeneity. Traditional subgroup analysis and interaction analysis tend to have low power to examine treatment heterogeneity or identify the sources of heterogeneity. With the recent development of machine learning techniques, causal forest has been proposed as a novel method to evaluate treatment heterogeneity, which can help overcome the limitations of the traditional methods. However, the application of causal forest in the evaluation of treatment heterogeneity in medicine is still in the beginning stage. In order to promote proper use of causal forest, this paper introduces its purposes, principles and implementation, interprets the examples and R codes, and highlights some attentions needed for practice.
In observational studies, multivariable analysis is commonly used to control confounding and reduce bias in the estimation of causal effect between exposure and outcome. However, in clinical problems with complex causal relationships, researchers select covariates for adjustment through clinical intuition and data-driven methods, which may lead to biased results. In recent years, directed acyclic graphs (DAGs) have become a popular method for visualizing causal relationships between variables. An appropriately constructed DAG can help researchers identify confounders, intermediate variables and other non-confounding variables, thereby improving covariates selection for multivariable analysis. In practice, researchers should incorporate clinical knowledge, systematic methods and transparent reporting to fully utilize DAG in causal inference, and support more reliable clinical decisions.
近十年，在藥品不良反應監測領域，基于醫療保健數據庫的安全信號檢測方法受到越來越多的關注，已成為彌補自發報告固有局限性的重要手段。目前數據挖掘方法主要基于比值失衡分析法（disproportionality analysis）、傳統藥物流行病學設計（如自身對照設計）、序列對稱分析（sequence symmetry analysis，SSA）、序貫統計檢驗（sequential statistical testing）、時序關聯規則（temporal association rules）、監督機器學習（supervised machine learning，SML）、樹狀掃描統計量方法（tree-based scan statistic）等。本文從應用場景和實用性角度對醫療保健數據庫中安全信號檢測方法及其性能進行介紹。
混合模型框架下的模型，如潛變量增長混合模型（latent growth mixture modeling，LGMM）或潛類別增長分析（latent class growth analysis，LCGA），因估算過程中涉及多個決策過程，導致潛變量軌跡分析結果的報告呈現多樣性。為解決這一問題，指南制訂小組按照系統化的制訂流程，通過 4 輪德爾菲法調查，遵循專家小組意見，提出了各領域報告潛變量軌跡分析結果時需采用統一的標準，最終確定了報告軌跡研究結果必要的關鍵條目，發布了潛變量軌跡研究報告規范（guidelines for reporting on latent trajectory studies，GRoLTS），并利用 GRoLTS 評價了 38 篇使用 LGMM 或 LCGA 研究創傷后應激軌跡的論文的報告情況。
ObjectiveTo systematically review the risk factors leading to postoperative persistence of children diagnosed with obstructive sleep apnea (OSA) after adenoidectomy and tonsillectomy. MethodsPubMed, EMbase, The Cochrane Library, ClinicalTrials.gov, CNKI, VIP, WanFang Data and SinoMed databases were electronically searched to collect case-control studies and cohort studies related to risk factors for postoperative persistence of OSA in children from inception to July 2019. Two reviewers independently screened literature, extracted data, and evaluated the risk of bias of the included studies. Meta-analysis was then performed using RevMan 5.3 software. ResultsA total of 12 cohort studies involving 1 659 OSA patients were included. Meta-analysis results showed that the risk of postoperative persistence of OSA in children with preoperative obesity was 3.47 times higher than that in non-obese children (RR=3.47, 95%CI 2.04 to 5.92, P<0.000 01). Compared with normal-weight children, obese children had 4.11 times higher risk of postoperative residual OSA (RR=4.11, 95%CI 1.68 to 10.07, P<0.000 01).ConclusionsPreoperative obesity is a risk factor for postoperative persistence of OSA in children. Due to the limited quantity and quality of included studies, more high-quality studies are needed to verity the above conclusions.
ObjectivesTo systematically review the efficacy and safety of Orlistat for obese patients with cardiovascular risk including hyperlipidemia, hypertension, diabetes and prediabetes.MethodsSinomed, CNKI, WanFang Data, PubMed, EMbase, The Cochrane Library and ClinicalTrails.gov databases were electronically searched to collect randomized controlled trials (RCTs) of Orlistat for obese patients with cardiovascular risk such as hyperlipemia, diabetes, prediabetes and hypertension from inception to Jan 7th, 2017. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of included studies. Then, meta-analysis was performed using Stata 14.0 software.ResultsA total of 28 RCTs were included. The results of meta-analysis showed that, compared with placebo, Orlistat could significantly reduce the weight (MD=–2.85, 95%CI –3.47 to –2.24, P=0.000), waist (MD=–2.45, 95%CI –3.07 to –1.83, P=0.000) and BMI (MD=–1.29, 95%CI –2.08 to –0.49, P=0.002) of patients. Orlistat could also control the blood pressure, blood glucose and other cardiovascular risk factors well. Compared with the blank control, Orlistat could improve the waist and parts of cardiovascular risk factors (P<0.05). The incidence of adverse events of Orlistat was slightly higher than that of placebo, but most could be self-healing.ConclusionsCurrent evidence shows that compared with placebo and blank control, Orlistat is effective for improving both weight loss and some cardiovascular risk factors. Due to limited quality and quantity of the included studies, more high quality studies are needed to verify above conclusion.