With the development of science and technology, a large number of advanced technologies are applied to medical equipment, which play an increasingly important role in clinical engineering. Therefore, new requirements are put forward for clinical engineering and clinical engineers in hospitals. This study comprehensively analyzed the training objectives and certification assessment of clinical engineering in many countries around the world. Combined with the current situation in China, it is of reference significance for the discipline construction and certification assessment of clinical engineering at the present stage in China, so as to promote the development of clinical engineering in China and speed up the development and certification of international clinical engineering.
ObjectiveTo investigate the association between cardiometabolic indicators and the risk of incident renal insufficiency using a longitudinal physical examination cohort. MethodsBased on a large-scale, multi-center, repeated-measurement physical examination cohort in China, this study evaluated the impact of baseline cardiovascular metabolic indicators on incident renal insufficiency using logistic regression, Cox proportional hazards models, Poisson regression, and generalized linear mixed-effects models. Furthermore, latent class mixed models (LCMM) were employed to identify the longitudinal trajectories of these indicators, and the associations between distinct trajectory patterns and the risk of renal insufficiency were analyzed using Cox and logistic regression models. ResultsDerived from a massive longitudinal cohort of 680 000 individuals across a multi-center healthcare network, a total of 264 379 participants were ultimately included, among whom 82 849 developed renal insufficiency during the follow-up period. Baseline analyses revealed that elevated levels of triglycerides (TG) and fasting glucose (FG) consistently increased the risk of renal insufficiency across multiple statistical models (all PFDR<0.001). Trajectory analyses demonstrated that high-level longitudinal trajectories of FG (HR=1.274, 95%CI 1.230 to 1.320) and diastolic blood pressure (DBP) (HR=1.042, 95%CI 1.023 to 1.061) were significant independent risk factors for the disease. Notably, the evolutionary trajectory of systolic blood pressure (SBP) exhibited opposite association directions between the Cox and logistic models, whereas the TG trajectory lost its statistical significance after fully adjusting for smoking and alcohol consumption. ConclusionBoth baseline characteristics and longitudinal variations of cardiovascular metabolic indicators are significantly associated with the incidence of renal insufficiency. Abnormal levels and high-level evolutionary trajectories of fasting glucose and triglycerides serve as robust risk factors for the disease. Regular monitoring and longitudinal tracking of these metabolic profiles are of profound clinical value for the prevention and early identification of renal insufficiency.
ObjectiveTo investigate the association between kidney function indicators in routine health examinations and the incidence of urinary stone disease using longitudinal repeated-measurement data. MethodsThis study was based on the large-scale longitudinal data in the WHALE study. Cox proportional hazards models were first applied to examine the associations between baseline kidney function indicators and incident urolithiasis. Subsequently, Poisson regression and mixed-effects models were used to analyze repeated-measurement data to further explore the relationships between kidney function indicators and urolithiasis. Latent class trajectory modeling was then employed to characterize longitudinal patterns of kidney function indicators. Based on the optimal trajectory models, logistic regression analyses and Cox regression analyses were performed to assess the associations between trajectory classes and the risk of urolithiasis. ResultsAmong 313 280 health examination participants included in the study, 8 864 incident cases of urolithiasis were identified during follow-up. In the baseline Cox analyses, cystatin C showed the strongest association with urolithiasis (HR=1.230, 95%CI 1.083 to 1.396, FDR=0.001). In analyses incorporating repeated measurements, serum uric acid demonstrated a strong association in both Poisson regression and mixed-effects models (RR=1.123, 95%CI 1.094 to 1.152, FDR<0.001; RR=1.106, 95%CI 1.075 to 1.137, FDR<0.001). In trajectory analyses, U-shaped trajectories of blood urea (HR=0.548, 95%CI 0.438 to 0.685, FDR<0.001) and uric acid (HR=0.910, 95%CI 0.857 to 0.685, FDR=0.005) were associated with a lower risk of urolithiasis. ConclusionBoth baseline levels and longitudinal changes in kidney function indicators measured during routine health examinations are significantly associated with the incidence of urolithiasis. Regular assessment and longitudinal monitoring of kidney function may contribute to the prevention and early identification of urolithiasis development and progression.