Associations between anthropometric indicators in early life and low-grade inflammation,insulin resistance and lipid profile in adolescence

Background and aimsThe long-term relations between excessive adiposity in early childhood and unfavourable cardiometabolic profiles in later ages are not yet completely understood. We aimed to assess the associations between birth weight (BW) and BMI from 6 months to 6 years of age, with biomarkers indicative of low-grade inflammation, insulin resistance and lipid profiles in adolescence.Methods and resultsRetrospective school-based study with 415 Portuguese adolescents (220 girls), mean age of 14.08 ± 1.6 years old. Anthropometric data from birth to 6 years old was extracted from individual child health book records. Actual weight and height were measured and BMI calculated. Participants were classified at each time point as normal weight or overweight according to WHO reference values. Biomarkers were obtained from venous blood samples. Linear regressions were used to explore the associations between the biomarkers and early life anthropometric indicators. From 2 years onwards, BMI associated positively with the inflammatory score and HOMA-IR in adolescence. Children who were overweight/obese from 2 to 6 years of age presented significantly higher inflammatory score and HOMA-IR later in adolescence. TC/HDL ratio was also positively associated with BMI from the age of 5 years onwards. The associations between BMI and cardiometabolic outcomes remained positive in adolescence, with overweight adolescents presenting a higher inflammatory score, HOMA-IR and TC/HDL than normal weight adolescents.ConclusionA high BMI from an early age was consistently associated with worse inflammatory and lipid profiles and insulin resistance in adolescence. No associations were found between BW and the same studied outcomes.     

Rotavirus,vaccine failure or diagnostic error?

Immunochromatography (ICG) is highly used in clinical settings for rotavirus (RV) diagnosis. The specificity of the tests differs by brand type and is not 100%, therefore its use when the prevalence of the disease is low (i.e. in vaccinated children) may result in a proportion of false positive diagnoses.In some areas, vaccine effectiveness studies or surveillance is done using ICG. Our objective was to estimate the validity of ICG test in vaccinated children, and estimate the number of false positive results in the Valencian Region of Spain, where all RV infections are diagnosed using ICG and are not confirmed by PCR.Population based registries were used to identify all results from the RV antigen tests performed between January 2008 and June 2012 in children under 37 months. Hospitalization and vaccination status of the patients were obtained by linking different databases through a unique identification number. The Positive Predictive Value of the ICG test depending on the vaccination status of the child, hospitalization and the rotavirus season was estimated by a Bayesian model of latent classes.Of the 48,833 tests with valid results, 9429 were done in vaccinated children, and of those 3963 (42%) during the rotavirus season. The prevalence of positive results in vaccinated varied from 2.9 to 21.4% of the tests depending on the hospitalization and seasonality. The estimated PPV also varied from 27.1 to 84.6% when stratified by these two parameters. Globally it is calculated that approximately 267 out of the 520 (51.3%) positives in vaccinated children were false positive tests.The large percentage of false positives, due to an excessive number of tests in vaccinated and out of the RV season, if interpreted as vaccine failures, can cause a loss of confidence in the vaccine and lower the estimates of vaccine effectiveness.     

Validation of PATHFx 2.0: An open-source tool for estimating survival in patients undergoing pathologic fracture fixation

Treatment decisions in patients with metastatic bone disease rely on accurate survival estimation. We developed the original PATHFx models using expensive, proprietary software and now seek to provide a more cost-effective solution. Using open-source machine learning software to create PATHFx version 2.0, we asked whether PATHFx 2.0 could be created using open-source methods and externally validated in two unique patient populations. The training set of a well-characterized, database records of 189 patients and the bnlearn package within R Version 3.5.1 (R Foundation for Statistical Computing), was used to establish a series of Bayesian belief network models designed to predict survival at 1, 3, 6, 12, 18, and 24 months. Each was externally validated in both a Scandinavian (n = 815 patients) and a Japanese (n = 261 patients) data set. Brier scores and receiver operating characteristic curves to assessed discriminatory ability. Decision curve analysis (DCA) evaluated whether models should be used clinically. DCA showed that the model should be used clinically at all time points in the Scandinavian data set. For the 1-month time point, DCA of the Japanese data set suggested to expect better outcomes assuming all patients will survive greater than 1 month. Brier scores for each curve demonstrate that the models are accurate at each time point. Statement of Clinical Significance: we successfully transitioned to PATHFx 2.0 using open-source software and externally validated it in two unique patient populations, which can be used as a cost-effective option to guide surgical decisions in patients with metastatic bone disease.     

原发性肝癌患者手术切除术后早期复发影响因素分析

目的:探究原发性肝癌患者手术切除术后早期复发影响因素分析。方法:对广州市番禺区中医院2017年2月-2019年2月收治的原发性肝癌患者98例进行回顾性分析,依据各项临床指标分析手术切除术后早期复发的影响因素。结果:原发性肝癌患者经由手术切除后出现复发的可能性较高,同时手术切缘有残留、包膜不完整、肿瘤结节、心理因素、甲胎蛋白、血管侵犯、肝硬化及肿瘤直径等均是影响原发性肝癌手术期后再复发的高危因素。结论:原发性肝癌通常具有术后复发的生物学特性,依据对手术切除术之后早期复发因素的分析,对手术风险与治疗方案进行充分评估,同时要求患者进行定期复查及随访等工作,可对患者手术成功以及并发症的防治等均具有积极意义。