Predictive Model for PICC Occlusion Risk for Patients in Intensive Care Units: A Retrospective Clinical Study

科研成果详情

题名	Predictive Model for PICC Occlusion Risk for Patients in Intensive Care Units: A Retrospective Clinical Study
作者	Zhu, Yijun; Li, Diwen; Li, Yunfei; Cai, Weiwei
发表日期	2023
发表期刊	ALTERNATIVE THERAPIES IN HEALTH AND MEDICINE 影响因子和分区
语种	英语
原始文献类型	Article
其他关键词	VENOUS THROMBOEMBOLISM
摘要	Context . Peripherally inserted central catheters (PICCs) have a high incidence of catheter occlusion, but research exploring the risk factors for such an occlusion for patients in intensive care units (ICUs) is lacking. Objective . The study intended to examine the impact of multiple risk factors on the occurrence of PICC catheter occlusion to find evidence that can help clinical medical staff identify patients at an early stage who are at high risk of a catheter occlusion. Design . The research team performed a retrospective, observational clinical study. Setting . The study took place at a tertiary general hospital, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University in Wenzhou, China. Participants . Participants were 300 patients with a PICC who received treatment in the hospital's adult ICU between January 2019 and April 2022. Groups . According to the time of catheterization, the research team numbered the 1.300 participants and then selected one starting number to divided them into two groups according to the random number table. These two groups were: (1) a training group with 225 participants and (2) validation group with 75 participants. Outcome Measures . The main outcome measure was the evaluation of the factors impacting patients who had had a PICC occlusion during catheter retention, including complete and incomplete occlusions, to build a risk prediction model of PICC occlusion. A secondary outcome measure was the occurrence of extubation of the PICC discharge of the ICU patient. The research team performed a univariate analysis of the training group's data and a multivariate logistic regression analysis of the risk factors. The team: (1) built a risk prediction model of PICC occlusion using the independent risk factors for catheter occlusion for PICC patients in an ICU and (2) used the Hosmer-Lemeshow goodness-of-fit test to test the prediction model. A two tailed using p>0.05 indicated that the model had a good fit. Then, the team applied the model to the validation group and evaluated the model's predictive ability using a receiver operating characteristic (ROC) curve. The team considered an area under the curve (AUC) >0.5 to have predictive value. The larger the area was, the better the predicted value was. The incidence of PICC occlusion in the training group was 18.22%, including 10 participants with complete occlusion and 31 with partial occlusion. The team used the SPSS 22.0 and R software for statistical analysis. Results . The univariate analysis showed that 13 factors were associated with PICC occlusion, including: (1) an age >= 65 years (P <.001), a BMI of >= 24 kg/m(2) (P <.001), (2) a BMI of >= 24kg/m(2) (P = .002), (3) diabetes (P <.001), (4) stroke (P <.001), (5) hypertension (P <.001), (6) malignant tumors (P <.001), (7) a history of deep vein thrombosis (P <.001), (8) limb activity (P <.001), (10) flushing and sealing pipe frequency of Q8h (P = .035), (11) retention time (P <.001), (12) an increased platelet count (P =.036), (13) blood transfusions (P <.001), and (14) intravenous nutrition (P <.001). The independent risk factors for PICC occlusion included: (1) age >= 65 years-OR=1.224, P = .028; (2) BMI > 24 kg/m(2)-OR=1.679, P=.004; (3) diabetes-OR=1.343, P = .017; (4) malignant tumors-OR=2.736, P <.001; (5) blood transfusions-OR=1.947, P <.001), and (6) intravenous nutrition-OR=2.021, P<.001. The frequency of flushing and sealing the pipe (Q8h)-OR=-2.145, P =.002-was a protective factor. In the training group, the area under the curve (AUC) for predicting a PICC occlusion was 0.917. The Hosmer-Lemeshow test of the prediction model showed that no significant differences existed in the test results within the model (chi(2) = 5.830, P =.666), indicating that the model passed the internal validation. The ideal and calibration curves of the prediction model were highly coincident, and the model was well calibrated. The Hosmer-Lemeshow test of the validation group showed that no significant differences existed in the test results outside the model, suggesting that the model had high consistency. Conclusions . Age >= 65 years, BMI >= 24 kg/m(2), diabetes, malignant tumors, blood transfusions, and intravenous nutrition were independent risk factors for PICC occlusion, while the frequency of flushing and sealing pipe (Q8h) was a protective factor. This prediction model had an outstanding ability to discriminate in identifying patients with a high-risk of PICC occlusion in the ICU.
出版者	InnoVision Professional Media
ISSN	1078-6791
卷号	29 期号:8 页码:278-285
页数	8
WOS类目	Integrative & Complementary Medicine
WOS研究方向	Integrative & Complementary Medicine
WOS记录号	WOS:001137669200044
收录类别	SCIE
PubMed ID	37573601
通讯作者地址	[Cai, Weiwei]Wenzhou Med Univ, Affiliated Hosp 2, Dept Crit Med, Wenzhou, Peoples R China.
引用统计
文献类型	期刊论文
条目标识符	https://kms.wmu.edu.cn/handle/3ETUA0LF/207319
专题	附属第二医院_重症医学科
通讯作者	Cai, Weiwei
作者单位	Wenzhou Med Univ, Affiliated Hosp 2, Dept Crit Med, Wenzhou, Peoples R China; Wenzhou Med Univ, Yuying Childrens Hosp, Wenzhou, Peoples R China
第一作者单位	附属第二医院_重症医学科
通讯作者单位	附属第二医院_重症医学科
第一作者的第一单位	附属第二医院_重症医学科
推荐引用方式 GB/T 7714	Zhu, Yijun,Li, Diwen,Li, Yunfei,et al. Predictive Model for PICC Occlusion Risk for Patients in Intensive Care Units: A Retrospective Clinical Study[J]. ALTERNATIVE THERAPIES IN HEALTH AND MEDICINE,2023,29(8):278-285.
APA	Zhu, Yijun, Li, Diwen, Li, Yunfei, & Cai, Weiwei. (2023). Predictive Model for PICC Occlusion Risk for Patients in Intensive Care Units: A Retrospective Clinical Study. ALTERNATIVE THERAPIES IN HEALTH AND MEDICINE, 29(8), 278-285.
MLA	Zhu, Yijun,et al."Predictive Model for PICC Occlusion Risk for Patients in Intensive Care Units: A Retrospective Clinical Study".ALTERNATIVE THERAPIES IN HEALTH AND MEDICINE 29.8(2023):278-285.