Claudiu Matei
Biographic Data
| ID | 7948070 |
|---|---|
| NAME | Claudiu Matei |
| GIVEN NAMES | Claudiu |
| FAMILY NAME | Matei |
| SIGNATURE | MATEI C |
| AFFILIATIONS | Lucian Blaga University of Sibiu |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Impact and predictive modeling of risk factors for involuntary psychiatric admissions before and during Covid-19
Introduction The COVID-19 pandemic significantly reshaped involuntary psychiatric hospitalizations, disrupting the balance between patient rights, public safety, and healthcare delivery. This study aims to examine the pandemic’s impact on involuntary admissions (IA) from a major psychiatric hospital in Sibiu Romania. Furthermore, it proposes a prediction model for informed consent refusal rates (ICRR). Materials and methods We conducted a retrosp…
A Decision-Tree Approach to Assist in Forecasting the Outcomes of the Neonatal Brain Injury
Neonatal brain injury or neonatal encephalopathy (NE) is a significant morbidity and mortality factor in preterm and full-term newborns. NE has an incidence in the range of 2.5 to 3.5 per 1000 live births carrying a considerable burden for neurological outcomes such as epilepsy, cerebral palsy, cognitive impairments, and hydrocephaly. Many scoring systems based on different risk factor combinations in regression models have been proposed to predi…
No prominent works on this page.
A Decision-Tree Approach to Assist in Forecasting the Outcomes of the Neonatal Brain Injury
Neonatal brain injury or neonatal encephalopathy (NE) is a significant morbidity and mortality factor in preterm and full-term newborns. NE has an incidence in the range of 2.5 to 3.5 per 1000 live births carrying a considerable burden for neurological outcomes such as epilepsy, cerebral palsy, cognitive impairments, and hydrocephaly. Many scoring systems based on different risk factor combinations in regression models have been proposed to predi…
Impact and predictive modeling of risk factors for involuntary psychiatric admissions before and during Covid-19
Introduction The COVID-19 pandemic significantly reshaped involuntary psychiatric hospitalizations, disrupting the balance between patient rights, public safety, and healthcare delivery. This study aims to examine the pandemic’s impact on involuntary admissions (IA) from a major psychiatric hospital in Sibiu Romania. Furthermore, it proposes a prediction model for informed consent refusal rates (ICRR). Materials and methods We conducted a retrosp…
Apgar score (1 work) · Cerebral palsy (1 work) · Encephalopathy (1 work) · Epilepsy (1 work) · Etiology (1 work) · Gestational age (1 work) · Healthcare Decision-Making and Restraints (1 work) · Infant Development and Preterm Care (1 work) · Internal Medicine (1 work) · Logistic regression (1 work)