RESUMO
BACKGROUND: Metabolic diseases contribute significantly to premature mortality worldwide, with increasing burdens observed among the working-age population (WAP). This study assessed global, regional, and national trends in metabolic disorders and associated mortality over three decades in WAP. METHODS: Data from the Global Burden of Disease 2019 study were leveraged to assess global metabolism-associated mortality and six key metabolic risk factors in WAP from 1990-2019. An age-period-cohort model was employed to determine the overall percentage change in mortality. RESULTS: The 2019 global metabolic risk-related mortality rate in WAP rose significantly by 50.73%, while the age-standardized mortality rate declined by 21.5%. India, China, Indonesia, the USA, and the Russian Federation were the top contributing countries to mortality in WAP, accounting for 51.01% of the total. High systolic blood pressure (HSBP), high body mass index (HBMI), and high fasting plasma glucose (HFPG) were the top metabolic risk factors for the highest mortality rates. Adverse trends in HBMI-associated mortality were observed, particularly in lower sociodemographic index (SDI) regions. HFPG-related mortality declined globally but increased in older age groups in lower SDI countries. CONCLUSIONS: Despite a general decline in metabolic risk-related deaths in WAP, increasing HBMI- and HFPG-related mortality in lower SDI areas poses ongoing public health challenges. Developing nations should prioritize interventions addressing HBMI and HFPG to mitigate mortality risks in WAP.
Assuntos
Carga Global da Doença , Humanos , Pessoa de Meia-Idade , Adulto , Masculino , Feminino , Fatores de Risco , Carga Global da Doença/tendências , Estudos de Coortes , Doenças Metabólicas/mortalidade , Doenças Metabólicas/epidemiologia , Saúde Global , Idoso , Índice de Massa Corporal , Adulto Jovem , Fatores Etários , Mortalidade/tendênciasRESUMO
Artificial intelligence (AI) has been found to assist in optical differentiation of hyperplastic and adenomatous colorectal polyps. We investigated whether AI can improve the accuracy of endoscopists' optical diagnosis of polyps with advanced features. We introduced our AI system distinguishing polyps with advanced features with more than 0.870 of accuracy in the internal and external validation datasets. All 19 endoscopists with different levels showed significantly lower diagnostic accuracy (0.410-0.580) than the AI. Prospective randomized controlled study involving 120 endoscopists into optical diagnosis of polyps with advanced features with or without AI demonstration identified that AI improved endoscopists' proportion of polyps with advanced features correctly sent for histological examination (0.960 versus 0.840, p < 0.001), and the proportion of polyps without advanced features resected and discarded (0.490 versus 0.380, p = 0.007). We thus developed an AI technique that significantly increases the accuracy of colorectal polyps with advanced features.
RESUMO
BACKGROUND/AIM: The dramatic color change after iodine staining (from white-yellow to pink after 2-3 min), designated as the "pink-color sign" (PCS), is indicative of esophageal high-grade intraepithelial neoplasia (HGIN) or an invasive lesion. However, no study has yet examined the association between the time of PCS appearance and histopathology. We investigated the association between the time of PCS appearance and esophageal histopathology in 456 lesions of 438 patients who were examined for suspected esophageal cancer. MATERIALS AND METHODS:: The records of 495 consecutive patients who had suspected esophageal cancer based on gastroscopy and who underwent Lugol's chromoendoscopy from January 2015 to March 2018 were retrospectively reviewed. The time of PCS appearance was recorded in all patients, and tissue specimens were examined. RESULTS: We examined 456 lesions in 438 patients. Use of PCS positivity at 2 min for the diagnosis of HGIN/invasive cancer had a sensitivity of 84.1%, a specificity of 72.7%, and an accuracy of 80.4%. We classified the PCS-positive patients in whom the time of PCS appearance was recorded (168 lesions) into 4 groups: 0-30, 31-60, 61-90, and 91-120 s. Based on a 60-s time for appearance of the PCS, the area under the receiver operating characteristic curve was 0.897, indicating good validity. At the optimal cutoff value of 60 s, the sensitivity was 90.2% and the specificity was 82.3%. The appearance of the PCS within 60 s had a diagnostic accordance rate of 88.6%, significantly higher than appearance of the PCS within 2 min (79.7%, P < 0.05). CONCLUSION: Appearance of the PCS within 1 min after iodine staining has a higher diagnostic accordance rate for esophageal HGIN/invasive cancer than appearance of the PCS at 2 min.