ABSTRACT
Predicting factors of delirium
in critically ill patients with neurological disorder
Lee, Hyun Jin
Department of Nursing
The Graduate School
Chonbuk National University
The aims of this study were to identify predicting factors of delir...
ABSTRACT
Predicting factors of delirium
in critically ill patients with neurological disorder
Lee, Hyun Jin
Department of Nursing
The Graduate School
Chonbuk National University
The aims of this study were to identify predicting factors of delirium in critically ill patients with neurological disorder. The participants were 193 critical ill patients with neurological disorder sampled from one university hospital in Chonbuk province. Between April 1 and November 25, 2017, data were collected through face-to-face interviews using five structured questionnaires: Confusion Assessment Method for the Intensive Care Unit, Glasgow Coma Scale, Acute Physiology and Chronic Health Evaluation Ⅱ, Karnofsky Performance Scale and Critical Care Pain Observation Tool. Data were analyzed using descriptive statistics, t-test, Chi-squared test, Fisher's exact test, Mann-Whitney U test and logistic regression using the SPSS 21.0 program.
The obtained results from this study are as follows;
1. Delirium was evaluated in 193 patients. The incidence rate of delirium was 11.9%.
2. Delirium was related to age, stayed in intensive care units, Glasgow Coma Scale score, Acute Physiology and Chronic Health Evaluation Ⅱ score, Karnofsky Performance Scale score, Critical Care Pain Observation Tool score, physical restraint, antihypertensive drugs, and anticonvulsants.
3. Logistic regression analysis showed that age, stayed in intensive care unit, Critical Care Pain Observation Tool score, and physical restraint were predicting factors of delirium in critically ill patients with neurological disorder.
Routine delirium screening is important for early detection of delirium. Identification of high-risk group and delirium prevention programs may be improve early recognition of delirium in critically ill patients with neurological disorder.
keywords : Critical Illness, Delirium,
Nervous System Diseases, Patient
ABSTRACT
Predicting factors of delirium
in critically ill patients with neurological disorder
Lee, Hyun Jin
Department of Nursing
The Graduate School
Chonbuk National University
The aims of this study were to identify predicting factors of delirium in critically ill patients with neurological disorder. The participants were 193 critical ill patients with neurological disorder sampled from one university hospital in Chonbuk province. Between April 1 and November 25, 2017, data were collected through face-to-face interviews using five structured questionnaires: Confusion Assessment Method for the Intensive Care Unit, Glasgow Coma Scale, Acute Physiology and Chronic Health Evaluation Ⅱ, Karnofsky Performance Scale and Critical Care Pain Observation Tool. Data were analyzed using descriptive statistics, t-test, Chi-squared test, Fisher's exact test, Mann-Whitney U test and logistic regression using the SPSS 21.0 program.
The obtained results from this study are as follows;
1. Delirium was evaluated in 193 patients. The incidence rate of delirium was 11.9%.
2. Delirium was related to age, stayed in intensive care units, Glasgow Coma Scale score, Acute Physiology and Chronic Health Evaluation Ⅱ score, Karnofsky Performance Scale score, Critical Care Pain Observation Tool score, physical restraint, antihypertensive drugs, and anticonvulsants.
3. Logistic regression analysis showed that age, stayed in intensive care unit, Critical Care Pain Observation Tool score, and physical restraint were predicting factors of delirium in critically ill patients with neurological disorder.
Routine delirium screening is important for early detection of delirium. Identification of high-risk group and delirium prevention programs may be improve early recognition of delirium in critically ill patients with neurological disorder.
keywords : Critical Illness, Delirium,
Nervous System Diseases, Patient
주제어
#Critical Illness Delirium Nervous System Diseases Patient
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