Admission source and mortality in a pediatric intensive care unit

Halal, Michel Georges dos Santos El; Barbieri, Evandro; Filho, Ricardo Mombelli; Trotta, Eliana de Andrade; Carvalho, Paulo Roberto Antonacci

doi:10.4103/0972-5229.99114

Cited by 47 publications

(54 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This may be due to the wide age (2 weeks–18 years) distribution of patients admitted to our ICU. However, the age distribution of ICU admission of which, the majority were under five (62.5%), was similar to studies done in India, 53–72.4% were under five [9–13]. The preponderance of male sex (53.8%) was similar to study done in Ethiopia − 54.7% [6] and Brazil − 55.2% [13], but somehow lower than studies done in India, Nepal, and Greek (54–61.1%) [9–12, 14].…”

Section: Discussionsupporting

confidence: 81%

Assessment of pattern and treatment outcome of patients admitted to pediatric intensive care unit, Ayder Referral Hospital, Tigray, Ethiopia, 2015

et al. 2018

View full text Add to dashboard Cite

ObjectiveTo describe admission pattern and outcome with its predictor variable on the mortality of children admitted to pediatric intensive care unit (PICU), Ayder Referral Hospital, Northern Ethiopia, from September 2012 to August 2014.ResultFrom 680 admitted patients, 400 patients were analyzed. Average age at admission was 62.99 ± 60.94 months, with F:M ratio of 1:1.2. Overall (from infectious and non-infectious) the most commonly affected systems were respiratory (90/400 pts., 22.5%) and central nervous system (83/400 pts., 20.75%). Most were admitted due to meningitis (44/400 pts., 11%), post-operative (43/400 pts., 10.8%) and acute glomerulonephritis (41/400 pts., 10.3%). The overall mortality rate was 8.5%. Multivariable logistic regression shows, use of inotropes (p = 0.000), need for mechanical ventilator (p = 0.007) and presence of comorbid illness (p = 0.002), infectious cause (p = 0.015) and low level of Glasgow coma scale less than eight (p = 0.04) were independent predictors of mortality. From this study, common cause of PICU admission and death was meningitis. This highlights the importance of focusing on the preventable methods in the public such as vaccine, creating awareness about hygiene, and expanding ICU for early detection and for treatment acutely ill children.Electronic supplementary materialThe online version of this article (10.1186/s13104-018-3432-4) contains supplementary material, which is available to authorized users.

show abstract

Section: Discussionsupporting

confidence: 81%

Assessment of pattern and treatment outcome of patients admitted to pediatric intensive care unit, Ayder Referral Hospital, Tigray, Ethiopia, 2015

et al. 2018

View full text Add to dashboard Cite

show abstract

“…1 Although the total number of hospital beds in the United States decreased by 26.4% from the year 1985 to 2000; the ICU beds increased by 26.2% during the same period. 2 As a fact, we know little on the exact causes of death and the impact of risk factors that may complicate the course of critical illness irrespective of the underlying disease.…”

Section: Introductionmentioning

confidence: 97%

Application of different scoring systems and their value in pediatric intensive care unit

Rady

Mohamed

Mohssen

et al. 2014

Egyptian Pediatric Association Gazette

View full text Add to dashboard Cite

Background: Little is known on the impact of risk factors that may complicate the course of critical illness. Scoring systems in ICUs allow assessment of the severity of diseases and predicting mortality. Objectives: Apply commonly used scores for assessment of illness severity and identify the combination of factors predicting patient's outcome. Methods: We included 231 patients admitted to PICU of Cairo University, Pediatric Hospital. PRISM III, PIM2, PEMOD, PELOD, TISS and SOFA scores were applied on the day of admission. Follow up was done using SOFA score and TISS. Results: There were positive correlations between PRISM III, PIM2, PELOD, PEMOD, SOFA and TISS on the day of admission, and the mortality rate (p < 0.0001). TISS and SOFA score had the highest discrimination ability (AUC: 0.81, 0.765, respectively). Significant positive correlations were found between SOFA score and TISS scores on days 1, 3 and 7 and PICU mortality rate (p < 0.0001). TISS had more ability of discrimination than SOFA score on day 1 (AUC: 0.843, 0.787, respectively). Conclusion: Scoring systems applied in PICU had good discrimination ability. TISS was a good tool for follow up. LOS, mechanical ventilation and inotropes were risk factors of mortality.

show abstract

“…On the other hand, PIM2 predicted mortality was 6.5%. 21 In Iran, a prospective cohort study to validate PIM2 performance in a tertiary hospital in Tehran, the observed mortalities among children admitted to the PICU reached 15%, while PIM2 predicted mortality was 8.3%, SMR is 1.8 (95% CI 1.28-2.46). 22 Of the limitations of the study is that it is hospital-based, thus the observed mortality rate of 8.4% cannot be generalized to represent children's mortalities admitted to PICUs all over Egypt.…”

Section: Discussionmentioning

confidence: 98%

Assessment of the performance of the Pediatric Index of Mortality 2 (PIM2) among Egyptian pediatric patients admitted to the intensive care

Youssef

Mosleh

Labib

2014

Egyptian Pediatric Association Gazette

View full text Add to dashboard Cite

Background: Mortality prediction models are useful in pediatric intensive care units (PICUs) as risk assessment tools and as a benchmark for the quality of care. Objectives: To assess the performance of the Pediatric Index of Mortality 2 (PIM2) in terms of calibration and discrimination between survivors and non-survivors among pediatric patients. Methods: This is a cohort prospective study including 317 pediatric patients admitted to two PICU settings in a tertiary care hospital in Egypt over a period of one year (from June 2012 till June 2013). Collected data included personal characteristics, hospital data, diagnosis, outcome and variables included in PIM2 scoring. Results: Non-survivors constituted 8.5%. Most common diagnosis was respiratory diseases (47.9%). Only CNS morbidities (11.7% of survivors versus 37% of non-survivors, P = 0.001) and a higher PIM2 score (2.39 ± 5.49 in survivors versus 41.38 ± 36.06 in non-survivors, P = 0.001) were associated with increased risk of non-survival. The area under the curve (AUC) for PIM2 is 0.796 (95% CI 0.675-0.916), P < 0.001. The Hosmer-Lemeshow goodness-of-fit was 2.850, 8 df, P = 0.943. PIM2. Conclusion: The calibration and the discriminative ability of PIM2 scoring system aiming to distinguish survivors from non-survivors are satisfactory for this sample of pediatric patients. PIM2 is easily calculated and is freely available. Thus, this tool provides a good incentive for ICU settings in Egypt for admission of high risk patients in the light of the limited PICU bed complement capacity in relation to the demands.

show abstract

Admission source and mortality in a pediatric intensive care unit

Cited by 47 publications

References 15 publications

Assessment of pattern and treatment outcome of patients admitted to pediatric intensive care unit, Ayder Referral Hospital, Tigray, Ethiopia, 2015

Assessment of pattern and treatment outcome of patients admitted to pediatric intensive care unit, Ayder Referral Hospital, Tigray, Ethiopia, 2015

Application of different scoring systems and their value in pediatric intensive care unit

Assessment of the performance of the Pediatric Index of Mortality 2 (PIM2) among Egyptian pediatric patients admitted to the intensive care

Contact Info

Product

Resources

About