Identification of population multimorbidity patterns in 3.9 million patients from Bogota in 2018 [0.03%]
基于2018年波哥大390万患者数据的多病共患模式识别研究
Carolina Saavedra-Moreno,Rafael Hurtado,Nubia Velasco et al.
Carolina Saavedra-Moreno et al.
Background: Multimorbidity has emerged as a challenge for health systems due to its association with adverse clinical outcomes. Given the limited information available on multimorbidity, particularly in low- and middle-in...
Sofiia Shatylo,Volodymyr Bogomaz,Oleksii Babych
Sofiia Shatylo
Background: Available epidemiological data on vitamin D status in the Ukrainian population are limited. Objective: The aim of this stud...
Comparing AI/ML approaches and classical regression for predictive modeling using large population health databases: Applications to COVID-19 case prediction [0.03%]
基于大规模人群健康数据库的预测建模中AI/ML方法与传统回归方法的比较：在COVID-19病例预测中的应用
Lise M Bjerre,Cayden Peixoto,Rawan Alkurd et al.
Lise M Bjerre et al.
Background: Research comparing artificial intelligence and machine learning (AI/ML) methods with classical statistical methods applied to large population health databases is limited. ...
Improving the integration of epidemiological data into human health risk assessment: What risk assessors told us they want [0.03%]
改善流行病学数据在人类健康风险评估中的整合：风险评估师希望得到的事项
Carl V Phillips,Igor Burstyn,David J Miller et al.
Carl V Phillips et al.
One of the practical contributions of epidemiology studies is to inform risk assessment and management to protect public health. However, there is a perception among some that environmental and occupational epidemiology is falling short of ...
The mockery that confounds better treatment of confounding in epidemiology: The change in estimate fallacy [0.03%]
对流行病学混淆因素处理更好的嘲弄：“估计变化谬误”
Igor Burstyn
Igor Burstyn
Confounding is one of the most infamous bugbears of epidemiology, used by some to dismiss the field's utility outright. The subject has received considerable attention from epidemiologists and the field boasts a remarkable arsenal for addre...
Tailored guidance to apply the Estimand framework to Trials within Cohorts (TwiCs) studies [0.03%]
定制的指导以将估计量框架应用于队列中的试验（TwiC）研究
R Gal,R Kessels,K Luijken et al.
R Gal et al.
Objective: The estimand framework offers a structured approach to define the treatment effect to be estimated in a clinical study. Defining the estimand upfront helps formulating the research question and informs study design, data collecti...
Mohammad Ali Mansournia,Maryam Nazemipour,Mahyar Etminan
Mohammad Ali Mansournia
In medical research, some variables are conditionally defined on some levels of another variable, leading to conditional missing data. Imputation of this type of structural missing data is needed given inefficiency of listwise deletion inhe...
Improving the timeliness of birth registration in Fiji through a financial incentive [0.03%]
通过财政激励改善斐济出生登记的及时性
Christine Linhart,Neel Singh,Meli Nadakuca et al.
Christine Linhart et al.
Background: Fiji is a Pacific Island nation with the predominant ethnic groups indigenous Fijians (iTaukei) (62 %) and Fijians of Indian descent (31 %). This study reports on the effect of a Parental Assistance Payment Pr...
Challenging unverified assumptions in causal claims: Do gas stoves increase risk of pediatric asthma? [0.03%]
挑战因果推断中的未经证实的假设：燃气灶会增加儿童哮喘的风险吗？
Louis Anthony Cox Jr
Louis Anthony Cox Jr
The use of unverified models for risk estimates and policy recommendations can be highly misleading, as their predictions may not reflect real-world health impacts. For example, a recent article states that NO2 from gas stoves "likely cause...
Incidence and prevalence of autoimmune diseases in China: A systematic review and meta-analysis of epidemiological studies [0.03%]
中国自身免疫性疾病发病和患病率的系统评价和meta分析研究
Olaa Mohamed-Ahmed,Lianhan Shang,Lin Wang et al.
Olaa Mohamed-Ahmed et al.
Background: Autoimmune diseases account for a substantial burden of disease in high-income countries, including Europe and North America. However, their epidemiology remains under-researched in other regions. We examined ...