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1.
J Perinatol ; 28(1): 55-60, 2008 Jan.
Article in English | MEDLINE | ID: mdl-18165830

ABSTRACT

OBJECTIVE: To establish beginning evidence of clinical validity and reliability of the Neonatal Pain, Agitation and Sedation Scale (N-PASS) in neonates with prolonged pain postoperatively and during mechanical ventilation. STUDY DESIGN: Prospective psychometric evaluation. Two nurses administered the N-PASS simultaneously and independently before and after pharmacologic interventions for pain or sedation. One nurse also administered the premature infant pain profile (PIPP) concurrently with the N-PASS. The setting consisted of 50-bed level III neonatal intensive care unit. Convenience sample of 72 observations of 46 ventilated and/or postoperative infants, 0 to 100 days of age, gestational age 23 to 40 weeks was used. Outcome measures comprised convergent and construct validity, interrater reliability and internal consistency. RESULT: Interrater reliability measured by intraclass coefficients of 0.85 to 0.95 was high (P<0.001 to 0.0001). Convergent validity was demonstrated by correlation with the PIPP scores (Spearman's rank correlation coefficient of 0.83 at high pain scores, 0.61 at low pain scores). Internal consistency, measured by Cronbach's alpha, was evident with pain scores (0.82), and with sedation scores (0.87). Construct validity was established via the Wilcoxon signed-rank test, comparing the distribution of N-PASS scores before and after pharmacologic intervention showing pain scores of 4.86 (3.38) and 1.81 (1.53) (mean (s.d.), P<0.0001) and sedation scores of 0.85 (1.66) and -2.78 (2.81) (P<0.0001) for pre- and postintervention assessments, respectively. CONCLUSIONS: This research provides beginning evidence that the N-PASS is a valid and reliable tool for assessing pain/agitation and sedation in ventilated and/or postoperative infants 0 to 100 days of age, and 23 weeks gestation and above.


Subject(s)
Intensive Care Units, Neonatal , Neuropsychological Tests , Pain Measurement , Pain, Postoperative/classification , Respiration, Artificial/adverse effects , Cohort Studies , Conscious Sedation/classification , Female , Gestational Age , Humans , Infant , Infant, Newborn , Male , Observer Variation , Postoperative Care , Psychometrics , Psychomotor Agitation/classification
2.
Am J Psychiatry ; 158(1): 43-8, 2001 Jan.
Article in English | MEDLINE | ID: mdl-11136632

ABSTRACT

OBJECTIVE: The authors' objectives were to determine 1) whether major depressive disorder diagnosed according to DSM-IV criteria modified for the medically ill predicted in-hospital mortality better than major depressive disorder diagnosed according to inclusive DSM-IV criteria and 2) whether a history of depression and current depression predicted mortality independent of severity of physical illness. METHOD: Of 392 consecutive medical inpatients, 241 were interviewed within the first 3 days of admission and 151 were excluded from the study. Chart review and a clinical interview that included the Schedule for Affective Disorders and Schizophrenia were used to determine demographic variables, past psychiatric history, psychiatric diagnoses, and illness measures. Diagnoses included major depressive disorder and minor depression diagnosed according to DSM-IV criteria that included all symptoms regardless of etiology and according to criteria modified for the medically ill (hopelessness, depression, or anhedonia were used as the qualifying affective symptoms; depressive symptoms were eliminated if easily explained by medical illness, treatments, or hospitalization). The Charlson combined age-comorbidity index was used to measure severity of illness. RESULTS: A diagnosis of major depressive disorder based on criteria modified for patients with medical illness better predicted mortality than a diagnosis based on inclusive criteria. A past history of depression and the Charlson combined age-comorbidity index predicted in-hospital mortality, but demographic variables, pain, discomfort, length of stay, medical diagnoses, and minor depression did not. In the final multivariate logistic regression model, the Charlson combined age-comorbidity index, a modified diagnosis of major depressive disorder, and a history of depression were independent predictors of in-hospital death. CONCLUSIONS: Severity of medical illness, a diagnosis of major depressive disorder based on modified criteria, and a past history of depression independently predicted in-hospital mortality in medical inpatients.


Subject(s)
Depressive Disorder/epidemiology , Hospital Mortality , Hospitalization/statistics & numerical data , Comorbidity , Depressive Disorder/diagnosis , Depressive Disorder/mortality , Female , Humans , Inpatients/statistics & numerical data , Logistic Models , Male , Mental Disorders/diagnosis , Mental Disorders/epidemiology , Middle Aged , Multivariate Analysis , Psychiatric Status Rating Scales/statistics & numerical data , Recurrence , Risk Factors , Severity of Illness Index
3.
Psychosomatics ; 41(5): 426-32, 2000.
Article in English | MEDLINE | ID: mdl-11015629

ABSTRACT

The authors interviewed a consecutive series of medical inpatients (N = 241) using the Schedule for Affective Disorders and Schizophrenia to determine which depressive symptoms are associated with in-hospital mortality. Fifteen depressive symptoms, pain, and physical discomfort were assessed along with medical comorbidity. Twenty patients died in-hospital (8.3%). Logistic regression showed that anhedonia, hopelessness, worthlessness, indecisiveness, and insomnia predicted in-hospital death after adjusting for physical comorbidity and age. Clinicians should be aware that these depressive symptoms may predict mortality in medical inpatients. Future studies should address which treatment modalities lead to better outcomes.


Subject(s)
Chronic Disease/psychology , Depression/mortality , Depressive Disorder, Major/mortality , Hospital Mortality , Sick Role , Adult , Aged , Brazil , Cause of Death , Chronic Disease/mortality , Depression/psychology , Depressive Disorder, Major/psychology , Female , Humans , Male , Middle Aged , Prognosis , Survival Analysis
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