A risk prediction model for adult patients with difficult intravenous access

Background: The challenges posed by difficult intravenous access (DIVA) in clinical treatment are not only related to technical difficulties but also have the potential to affect the quality of patient care and overall experience. It is crucial to adopt effective strategies to address difficult intravenous access. Currently, the assessment of difficult veins largely relies on individual perception and experience, which introduces a significant degree of subjectivity. Aim: To develop and validate a risk prediction model for DIVA in adult patients, providing a tool for early identification and intervention. Design: An observational study. Methods: Retrospective data collection was conducted on 1170 hospitalized patients who required the placement of a short peripheral venous catheter for treatment in a tertiary hospital from June 1, 2022, to September 30, 2022, as the training set. Logistic regression analysis was employed to identify factors influencing DIVA in adult patients and to construct a risk prediction model. Prospective data collection was conducted on 300 hospitalized patients from June 1, 2023, to June 30, 2023, for external validation. The discriminative ability, calibration, and clinical utility of the model were evaluated using the area under the receiver operating characteristic curve, calibration curve, and clinical decision curve, respectively. A TRIPOD checklist was used to guide the reporting of this study. Results: The average age of patients in the training set was 58.60 ± 15.39 years. Among them, 626 were males (53.50%) and 544 were females (46.50%). The external validation group included a total of 300 patients with a mean age of 58.77 ± 15.26 years. There were 142 males (47.33%) and 158 females (52.67%). Advanced age, female sex, extreme weight (BMI <18.5 or >30), history of hemodialysis, axillary lymph node dissection for breast cancer, compromised skin integrity, history of DIVA, and target cannula size ⩽20G are independent predictive factors for DIVA in adult patients (all p < 0.05). The risk prediction model constructed based on these factors had an area under the ROC curve of 0.912 (95% CI 0.880–0.943) in the modeling group. The areas under the ROC curve in the internal and external validation groups were 0.887 (95% CI 0.855–0.924) and 0.870 (95% CI 0.799–0.942), respectively. Calibration curves showed good agreement between predicted and observed probabilities. Decision curve analysis demonstrated that intervening when the risk of venous puncture difficulty ranged from 3% to 91% yielded favorable clinical benefits for patients. Conclusion: Constructing a risk prediction model for DIVA in adult patients has significant predictive value. It assists medical staff in early intervention and management for high-risk patients, thereby achieving effective prediction, warning, and control.