Oxygen Treatment in Intensive Care and Emergency Medicine

Hyperbaric Oxygen Therapy in Upper Limb Crush Injury: Why and When?

Introduction In 2016, the European Committee for Hyperbaric Medicine strongly recommended hyperbaric oxygen therapy (HBOT) adjunctive to surgery in post-traumatic crush injuries, initiating as rapidly as possible. For the last 30 years, HBOT has been used in crush injury, but in most cases as a last resort, after skin flaps necrosis or wound bed infection, diminishing its potential benefits as a complementary treatment. It is, therefore, essential to understand how HBOT modulates the outcome of crush injury, and when to use it, since this can be a significant and underused therapeutic weapon that may alter the natural course of these patients. Methods Nineteen (n=19) adult patients with upper limb crush injuries underwent adjunctive HBOT, after the initial surgical approach. The measured outcomes included trauma-related acute complications (tissue necrosis and local infection), and late complications (pseudarthrosis and late deep infection). Results Only six (n=6) patients started HBOT in the first 24 hours. Four (n=4) patients presented acute complications; in half of those cases (n=2), HBOT was initiated more than 24 hours post-injury. Late complications were observed in three patients, none of which had initiated HBOT in the first 24 hours post-injury. Conclusions Either lack of awareness or logistic difficulties, preclude initiating timely HBOT, limiting its potential benefits. It is important to alert all practitioners to the right timing to initiate HBOT in order to improve these patients' outcomes.

Interpretable Machine Learning to Optimize Early In-Hospital Mortality Prediction for Elderly Patients with Sepsis: A Discovery Study

Sepsis-related mortality rates are high among elderly patients, especially those in intensive care units (ICUs). Early prediction of the prognosis of sepsis is critical, as prompt and effective treatment can improve prognosis. Researchers have predicted mortality and the development of sepsis using machine learning algorithms; however, few studies specifically focus on elderly patients with sepsis. This paper proposes a viable model for early prediction of in-hospital mortality among elderly patients diagnosed with sepsis. We extracted patient information from the Medical Information Mart for Intensive Care IV database. We employed several machine learning algorithms to predict the in-hospital mortality of elderly ICU patients with sepsis. The performance of the model was evaluated by using the AUROC and F1 score. Furthermore, the SHAP algorithm was used to explain the model, analyze how the individual features affect the model output, and visualize the Shapley value for a single individual. Our study included 18522 elderly patients, with a mortality of 15.4%. After screening, 59 clinical variables were extracted to develop models. Feature importance analysis showed that age, PO2, RDW, SPO2, WBC, and urine output were significantly related to the in-hospital mortality. According to the results of AUROC (0.871 (95% CI: 0.854-0.888)) and F1 score (0.547 (95% CI: 0.539-0.661)) analyses, the extreme gradient boosting (XGBoost) model outperformed the other models (i.e., LGBM, LR, RF, DT, and KNN). Furthermore, SHAP force analysis illustrated how the constructed model visualized the individualized prediction of death. XGBoost machine learning framework gives good in-hospital mortality prediction of elderly patients with sepsis and can maximize prediction model accuracy. The XGBoost model could be an effective tool to assist doctors in identifying high-risk cases of in-hospital mortality among elderly patients with sepsis. This could be used to create a clinical decision support system in the future.

Is Structured Exercise Performed with Supplemental Oxygen a Promising Method of Personalized Medicine in the Therapy of Chronic Diseases?

Aim: This systematic review aimed to explore the literature to identify in which types of chronic diseases exercise with supplemental oxygen has previously been utilized and whether this type of personalized therapy leads to superior effects in physical fitness and well-being. Methods: Databases (PubMed/MEDLINE, CINHAL, EMBASE, Web of knowledge and Cochrane Library) were searched in accordance with PRISMA. Eligibility criteria included adult patients diagnosed with any type of chronic diseases engaging in supervised exercise training with supplemental oxygen compared to normoxia. A random-effects model was used to pool effect sizes by standardized mean differences (SMD). Results: Out of the identified 4038 studies, 12 articles were eligible. Eleven studies were conducted in chronic obstructive pulmonary disease (COPD), while one study included coronary artery disease (CAD) patients. No statistical differences were observed for markers of physical fitness and patient-reported outcomes on well-being between the two training conditions (SMD −0.10; 95% CI −0.27, 0.08; p = 0.26). Conclusions: We found that chronic exercise with supplemental oxygen has mainly been utilized for COPD patients. Moreover, no superior long-term adaptations on physical fitness, functional capacity or patient-reported well-being were found, questioning the role of this method as a personalized medicine approach. Prospero registration: CRD42018104649.