Many risk prediction models have been extensively studied to predict adverse clinical and prognostic outcomes in critically ill patients, mainly focusing on patients from the ICU. However critically ill patients constitute a considerably diverse population, and there is a growing consensus that a “one size fits all” approach can lead to inconsistent results in the ICU. In this scenario, the established risk prediction models to predict the adverse clinical and prognostic outcomes in hospitalized patients in ICU patients may not be suitable for use in clinical risks prediction and management in neurocritical ill patients. Therefore, this issue is launched to collect high-quality evidence, explicitly focusing on establishing and validating Prognostic Models in neurocritical and neurohospitalist care.
Establishing and validating prognosis prediction models in neurocritical ill patients is imperative, as many diseases are fatal or cause severe disability. Patients, families, and healthcare professionals want to know what to expect, and these expectations often influence both short-term and long-term healthcare decisions. Therefore, collecting reliable prognostic models to quantify individual patient risk is necessary and desirable to guide better treatment of individuals affected by nerve damage. Prognostic models can provide a reference and basis for early identification, prevention, and control of poor prognosis in clinical practice. To promote the early screening and monitoring of neurocritical patients in clinical practice, prevent the occurrence and development of adverse prognoses, improve the quality of life of patients, reduce the medical burden of patients, and improve the clinical work efficiency of medical staff.
This Research Topic aims to construct a prognosis model to provide reference and evidence for the early identification, prevention, and control of poor prognosis in clinical treatment and care. We hope to foster best practices in caring for patients hospitalized because of neurological illnesses. We welcome submissions of Original Research articles, Reviews, Mini-reviews, Commentaries, etc.
Potential topics include but are not limited to the following:
- Construction of prognostic models by machine learning techniques in patients with neurocritical and neurohospitalist care
- Validating and improving the established prognosis prediction models in neurocritical ill patients
- Narrowing down the implementation gap by studying the application of the prognosis prediction models in neurocritical ill patients
- Review the research progress of prognostic models in neurocritical and neurohospitalist care
Many risk prediction models have been extensively studied to predict adverse clinical and prognostic outcomes in critically ill patients, mainly focusing on patients from the ICU. However critically ill patients constitute a considerably diverse population, and there is a growing consensus that a “one size fits all” approach can lead to inconsistent results in the ICU. In this scenario, the established risk prediction models to predict the adverse clinical and prognostic outcomes in hospitalized patients in ICU patients may not be suitable for use in clinical risks prediction and management in neurocritical ill patients. Therefore, this issue is launched to collect high-quality evidence, explicitly focusing on establishing and validating Prognostic Models in neurocritical and neurohospitalist care.
Establishing and validating prognosis prediction models in neurocritical ill patients is imperative, as many diseases are fatal or cause severe disability. Patients, families, and healthcare professionals want to know what to expect, and these expectations often influence both short-term and long-term healthcare decisions. Therefore, collecting reliable prognostic models to quantify individual patient risk is necessary and desirable to guide better treatment of individuals affected by nerve damage. Prognostic models can provide a reference and basis for early identification, prevention, and control of poor prognosis in clinical practice. To promote the early screening and monitoring of neurocritical patients in clinical practice, prevent the occurrence and development of adverse prognoses, improve the quality of life of patients, reduce the medical burden of patients, and improve the clinical work efficiency of medical staff.
This Research Topic aims to construct a prognosis model to provide reference and evidence for the early identification, prevention, and control of poor prognosis in clinical treatment and care. We hope to foster best practices in caring for patients hospitalized because of neurological illnesses. We welcome submissions of Original Research articles, Reviews, Mini-reviews, Commentaries, etc.
Potential topics include but are not limited to the following:
- Construction of prognostic models by machine learning techniques in patients with neurocritical and neurohospitalist care
- Validating and improving the established prognosis prediction models in neurocritical ill patients
- Narrowing down the implementation gap by studying the application of the prognosis prediction models in neurocritical ill patients
- Review the research progress of prognostic models in neurocritical and neurohospitalist care
