Abstract and Introduction
Abstract
Objectives: This study aimed to investigate the variables that influence neurological functional restoration in cardiac arrest patients and construct a nomogram to predict neurofunctional prognosis.
Patients and Methods: We extracted the data from the Dryad database. Associations between patient variables and neurological outcomes were examined by logistic regression models. On the basis of these predictors, a prognostic nomogram was constructed. The identification and calibration of the prognostic nomogram were evaluated through the receiver operating characteristic (ROC) curve, the calibration curve, and the concordance index (C-index).
Results: A total of 374 cardiac arrest individuals were recruited in the research. Sixty percent of the participants had an adverse neurological result. The multivariable logistic regression analysis for poor neurological recovery, which showed patient age ≥ 65 years, previous neurological disease, witnessed arrest, bystander cardio-pulmonary resuscitation(CPR), cardiac arrest presenting with a non-shockable rhythm, total epinephrine dose ≥ 2.5 mg at the time of resuscitation and acute kidney injury(AKI) remained independent predictors for neurological outcomes.
Conclusions: The novel nomogram based on clinical characteristics is an efficient tool to predict neurological outcomes in cardiac arrest patients, which may help clinicians identifying high-risk patients and tailoring personalized treatment regimens.
Introduction
Cardiac arrest is one of the leading causes of death globally, with a universal prevalence of 5 to 11 cases per 100,000 inhabitants annually.[1,2] It has long been believed that the prognosis of cardiac arrest were so poor that resuscitation may not even be necessary. While results remain disappointing, more recent findings indicate that progress has been made over the last two decades.[3]
Neurological dysfunction, which primarily stems from global ischemia–reperfusion injury, is the determining factor that contributes to adverse outcomes following cardiac arrest.[4] Although targeted temperature management (TTM) and other neuroprotective strategies have made significant strides, the outcomes of discharge from the hospital remain unsatisfactory, and the favorable neurological recovery rate is only about 8%.[5] More recently, the prediction of neurological function in comatose individuals following cardiopulmonary resuscitation(CPR) is the hot spot of research. Several prognostic methods, including electroencephalography, visual and quantitative brain magnetic resonance imaging, somatosensory evoked potential, neuron-specific enolase, serum tau, grey matter to white matter ratio in brain, and optic nerve sheath diameter, have been applied to predicting the neurological outcomes for individuals who suffered cardiac arrest.[6–11] Nonetheless, these techniques are not consistently accessible, and predicting neurological functional restoration conditions for post-cardiac arrest individuals remains challenging.
Researchers consider that nomogram, which is a simple graphical representation of statistical prediction model, to be an effective and practical method for recently predicting the survival and prognosis of individuals experiencing cardiac arrest.[12,13] Nevertheless, to the best of our knowledge, no prognostic nomograms for recovery of neurological function in comatose individuals following cardiac arrest have been established. Using the Dryad database, the present study was the first to establish a comprehensive prognostic nomogram to predict neurological outcomes for comatose individuals following cardiac arrest.
BMC Anesthesiol. 2023;23(289) © 2023 BioMed Central, Ltd.
