A Pilot Study of Viscoelastic Monitoring in Pediatric Trauma: Outcomes and Lessons Learned

Development and validation of a novel nomogram to predict the risk of the prolonged postoperative length of stay for lumbar spinal stenosis patients

BACKGROUND

Lumber spinal stenosis (LSS) is the increasingly reason for spine surgery for elder patients since China is facing the fastest-growing aging population. The aim of this research was to create a model to predict the probabilities of requiring a prolonged postoperative length of stay (PLOS) for lumbar spinal stenosis patients, minimizing the healthcare burden.

METHODS

A total of 540 LSS patients were enrolled in this project. The outcome was a prolonged PLOS after spine surgery, defined as hospitalizations ≥ 75th percentile for PLOS, including the day of discharge. The least absolute shrinkage and selection operator (LASSO) was used to identify independent risk variables related to prolonged PLOS. Multivariable logistic regression analysis was utilized to generate a prediction model utilizing the variables employed in the LASSO approach. The receiver operating characteristic (ROC) curve's area under the curve (AUC) and the calibration curve's respective curves were used to further validate the model's calibration with predictability and discriminative capabilities. By using decision curve analysis, the resulting model's clinical effectiveness was assessed.

RESULTS

Among 540 individuals, 344 had PLOS that was within the usual range of P75 (8 days), according to the interquartile range of PLOS, and 196 had PLOS that was above the normal range of P75 (prolonged PLOS). Four variables were incorporated into the predictive model, named: transfusion, operation duration, blood loss and involved spine segments. A great difference in clinical scores can be found between the two groups (P < 0.001). In the development set, the model's AUC for predicting prolonged PLOS was 0.812 (95% CI: 0.768-0.859), while in the validation set, it was 0.830 (95% CI: 0.753-0.881). The calibration plots for the probability showed coherence between the expected probability and the actual probability both in the development set and validation set respectively. When intervention was chosen at the potential threshold of 2%, analysis of the decision curve revealed that the model was more clinically effective.

CONCLUSIONS

The individualized prediction nomogram incorporating five common clinical features for LSS patients undergoing surgery can be suitably used to smooth early identification and improve screening of patients at higher risk of prolonged PLOS and minimize health care.

Thromboelastography in the Perioperative Period: A Literature Review

Assessing coagulation status is essential for prompt intervention to reduce morbidity and mortality related to bleeding and thrombotic complications during the perioperative period. Traditional coagulation tests such as platelet count, activated partial thromboplastin time (aPTT), prothrombin time (PT), international normalized ratio (INR), and activated clotting time (ACT) provide only static evaluation. These tests are not designed for assessment of dynamically changing coagulation conditions during the perioperative time. However, viscoelastic coagulation testing such as thromboelastography (TEG) produces a rapid numerical and graphical representation that helps to detect and direct targeted hemostatic therapy. Searching the literature through PubMed, Medline, Ovid, CINAHL, and ClinicalTrials.gov we retrieved 210 studies, which represent the use of TEG in the perioperative period. The included studies were categorized under various settings such as trauma, obstetrics, orthopedics, intensive care unit (ICU), cardiovascular, transplant, and miscellaneous scenarios. TEG showed promising results in trauma surgeries in predicting mortality, hypercoagulability, and bleeding even when it was compared to conventional methods. TEG was also useful in monitoring anticoagulant therapy in orthopedic and obstetric surgeries; however, its role in predicting thrombotic events, hypercoagulability, or complications was questionable. In ICU patients, it showed promising results, especially in the prediction or improvement of sepsis, coagulopathy, thrombotic events, ICU duration, hospital stay, and ventilator duration. TEG parameters effectively predicted hypercoagulation in transplant surgeries. Regarding cardiovascular surgeries, they were effective in the prediction of the need for blood products, coagulopathy, thrombotic events, and monitoring anticoagulation therapy. More randomized clinical trials comparing TEG parameters with standardized tools are needed to produce robust results to standardize its use in different perioperative settings.