ObjectivesThe aim of this study was to identify the prevalence of peripherally inserted central catheter (PICC) malposition and the influence of guide wire removal on tip location in PICCs and determine whether related factors, including age, sex, side of insertion and brand of catheter, influence the PICC tip location.SettingSingle-centre research institute in China recruiting patients from the hospital.ParticipantsA total of 837 adult patients with inserted PICCs were recruited from October 2016 to May 2017.InterventionsThis was a cross-sectional study aiming to identify the prevalence of PICC malposition and the influence of guide wire removal on tip location in PICCs. A linear regression model and a variance of factorial design analysis were performed. The PICC tip location was documented on a postinsertion chest X-ray. Multivariable analyses were performed based on the following related factors: age, sex, side of insertion and brand of catheter.ResultsThe tip location moved a mean of 17.4 mm among the 837 included patients. The prevalence of PICC malposition was 83.6% (700/837), while 16.4% (137/837) of PICCs remained in correct location. The mean movement caused by guide wire removal without an adjusted tail end was (−1.95±26.90) mm. The difference between tail end adjustment movement and actual tip position movement in each PICC was (33.0±17.1) mm in type C, which was significantly higher than the findings for type A (12.8±13.3) mm and type B (12.9±12.7) mm.ConclusionsPICC malposition is a frequent event. Different catheter brands were associated with different ranges of movement in tip location after guide wire removal. The age and sex of the patients and the insertion side did not influence the extent of movement.
Structural contradictions among cities, agriculture, animal husbandry, and ecosystems in agriculture/ pastoral zones have become increasingly prominent. This study analyzed land use change for a typical farming-pastoral interlacing area in the Keerqinzuoyihou Banner, China, using land use status data from 2009 to 2017. The drivers of land use changes were determined using logistic regression analysis. The Conversion of Land Use and its Effects at Small Region Extent (CLUE-S) model simulated four scenarios (i.e., natural evolution, ecological, economic, and social benefits maximization), and there were three key findings. First, land use structure mainly consisted of cropland, forest, and grassland; these accounted for nearly 90% of the total land area. There was a rapid increase in cultivated and built-up areas from 2009 to 2017. Second, the Kappa coefficient of the CLUE-S simulated results and actual land use was 0.936, indicating high model accuracy and applicability for simulating spatial land use distribution in the study area. Third, under the natural evolution scenario, forest, grassland, water bodies, sandy land, and unused land decreased from 2017 to 2025, whereas cropland and built-up land increased. This provides a reference to guide government land use planning and measures to improve land use efficiency and optimize the industrial structure.
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