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PubMed2026

Measurement of low-density lipoprotein cholesterol and other circulating lipids in Brazil: a systematic literature review.

Accurate laboratory assessment of circulating lipids underpins cardiovascular risk stratification, yet clinical interpretation depends not only on the assays but on the formula chosen to estimate low-density lipoprotein cholesterol (LDL-C). This review integrates the 2019-2025 evidence on laboratory methods for triglycerides (TG), total cholesterol (TC), and high-density lipoprotein cholesterol (HDLC), and on the formulas estimating LDL-C, VLDL-C, and non-HDL cholesterol, to determine how these should be measured, reported, and harmonized in Brazil, where lipid thresholds are adapted from international consensus. A PRISMA 2020 systematic search (PROSPERO CRD420251241064) of PubMed/MEDLINE, Scopus, SciELO, LILACS, Web of Science, and Embase retrieved 57,915 records; after removing 38,210 duplicates, 19,705 titles/abstracts were screened, 312 full texts assessed, and 25 sources included. Enzymatic colorimetric assays remain standard for TG, TC, and HDLC. For LDL-C, Martin/Hopkins classifies more accurately than Friedewald (89.6% vs 83.2% correct categorization in 5,051,467 patients), particularly at high TG and low LDL-C, while Sampson/NIH and modified Sampson/NIH extend reliable estimation into hypertriglyceridemia and very low LDL-C; direct measurement is reserved for TG beyond the validated range. Although the review centers on the Friedewald, Martin/Hopkins, and Sampson/NIH families that dominate guideline practice, other published equations exist and are addressed in context. In Brazil, atherogenic-lipid thresholds are risk-based decision limits rather than reference intervals; national surveys describe lipid distributions but were not designed to establish them. Analytical standardization through traceability programs, multicenter validation of formulas, and-where the distribution-based construct applies (HDLC, pediatrics)-nationally derived reference intervals are priorities for equitable cardiovascular risk assessment in Brazil.

Humans↗

PubMed2026

Assessing the accuracy and efficiency of an electronic platform for managing childhood illnesses in rural China: A cluster randomized controlled trial.

OBJECTIVES: The Integrated Management of Childhood Illness (IMCI) faces challenges in capacity building and quality control. This trial aims to assess an electronic IMCI (eIMCI) platform in improving the effectiveness and efficiency in disease classification and management by community health workers (CHWs). DESIGN: Cluster randomized controlled trial. SETTING: Rural western China. PARTICIPANTS: 24 CHWs and 72 ill children aged 2 months to 5 years (3 children per CHW). CHWs were randomly assigned to intervention or control groups. INTERVENTIONS: The intervention CHWs received online training and performed disease management using the eIMCI platform featuring integrated training modules and decision-support tools. The control group received traditional face-to-face training and used paper-based IMCI protocols. MAIN OUTCOME MEASURES: Proportion of children correctly diagnosed or classified by CHWs, as determined by a pediatric specialist. Relative risk (RR) between groups was estimated using Poisson Generalized Linear Mixed Models incorporating a random intercept for CHW to account for clustering of children within individual CHWs and adjusting for key covariates at both the CHW and child levels. RESULTS: The intervention group (13 CHWs, 39 children) had a higher rate of correct classification (64.1%) compared to the control group (11 CHWs, 33 children) (39.4%, P = .056). Multivariable regression analysis confirmed this (RR = 2.1, 95% CI: 1.5-3.1; P < .001). No significant difference was found in correct treatment rates (38.5% vs. 27.3%, P = .316). Online training reduced time and costs by approximately 80%, though with a slight decrease in post-training evaluation scores. CONCLUSIONS: The eIMCI platform shows potential in enhancing IMCI implementation and significantly reducing the training burden in resource-limited settings. Trial registration: Chinese Clinical Trial Registry: ChiCTR2100042533, https://www.chictr.org.cn/showproj.html?proj=119995.

Humans↗

PubMed2026

Risk Factors and Predictive Model for Postoperative High Myopia in Children Undergoing Congenital Cataract Surgery With Intraocular Lens Implantation.

PURPOSE: To identify risk factors associated with the development of high myopia following congenital cataract surgery and to establish a robust predictive model. DESIGN: Retrospective clinical cohort study. SUBJECTS: This retrospective study included 106 pediatric patients who underwent congenital cataract surgery with primary IOL implantation (mean follow-up 8.19 years). The model was externally validated in an independent cohort of 72 patients with a mean follow-up of 7.83 years. METHODS: Preoperative and postoperative ocular biometric parameters were collected. Risk factors for postoperative high myopia were analyzed using Cox proportional hazards regression, which served as the basis for model construction. The predictive performance of the model was rigorously evaluated for discrimination and calibration. Discriminative ability was quantified using Harrell's C-index and the area under the receiver operating characteristic curve (AUC). Model calibration was assessed via calibration plots by comparing predicted probabilities with actual observed outcomes. Internal validation was performed using a bootstrapping method (500 iterations) to ensure model stability and adjust for potential overfitting. RESULTS: An initial postoperative refraction of <+0.75D, and a higher IOL Power to Axial length Ratio (IOL/AL ratio) were identified as significant risk factors for the development of postoperative high myopia. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. The predictive model demonstrated robust performance, achieving a C-index of 0.711 (internal validation C-index: 0.713). The area under the receiver operating characteristic curve (AUC) values for predicting high myopia at 5 and 10 years were 0.858 and 0.745, respectively. Furthermore, calibration curves demonstrated excellent agreement between the predicted and observed outcomes throughout the follow-up period. In external validation, the model achieved a C-index of 0.825, 5-year AUC of 0.833, and 10-year AUC of 0.713. CONCLUSIONS: Our analysis established that initial postoperative refraction <+0.75D, and an elevated IOL/AL ratio are key determinants of high myopia risk following surgery. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. This predictive framework provides clinicians with a practical tool to optimize preoperative IOL selection and identify high-risk infants who require vigilant myopia prevention and balanced amblyopia management.

Humans↗