ABC of intensive care: Outcome data and scoring systems

Gunning, K.; Rowan, Kathy

doi:10.1136/bmj.319.7204.241

Cited by 137 publications

(93 citation statements)

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“…This percentage is higher than those found by other authors [7][8][9][10][11][12][13] , who reported mortality rates ranging from 1.85% to 7.4% and with a greater prevalence among infants under 12 months. [7][8][9] In contrast, Freire et al 18 and Costa et al 6 reported mortality rates of 19.2% and 33.9%, respectively, in the cities of Natal, Rio Grande do Norte, and São Luiz, Maranhão, Brazil.…”

Section: Resultscontrasting

confidence: 66%

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Clinical-Epidemiological Profile of Hospitalised Patients in Paediatric Intensive Care Unit

Batista

Coelho

Trugilho

et al. 2015

J. Hum. Growth Dev.

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Introduction: Paediatric intensive care units have made important advances in technology and assistance since the 1980s, which have made more favourable the prognosis of critically ill children all over the world. Objective: Identify the epidemiological profile and clinical outcomes of hospitalised children and adolescents in the Paediatric Intensive Care Unit of Hospital Vitória, Espirito Santo, Brazil. Methods: A descriptive and retrospective study carried out in the Paediatric Intensive Care Unit of Hospital Infantil Nossa Senhora da Glória in the city of Vitória, Espirito Santo, Brazil. Age, sex, hospitalisation diagnosis, progression to discharge/death, and length of hospital admission were obtained from the Sector of Medical and Hospital Statistics Files between 2011 and 2012. For the descriptive analysis, categorical variables were expressed as absolute and percentage, and the continuous variables in average and standard deviation. For comparison, Pearson's chi-squared tests, Fisher's test, and Student's t test were used and p values <0.05 with confidence interval of 95% were considered statistically significant. Results: Of the 609 patients analysed, 342 (56.2%) were male (mean age: 72.7 ± 71.3 months). Respiratory disease, postoperative processes, and trauma were the main causes of hospitalisation. The average duration of hospitalization was 6.9 ± 5.5 days; 514 (84.4%) patients were discharged, 95 (15.6%) died, and of those, 53 (55.7%) died in less than 72 hours of hospitalisation. Conclusion: Most of the patients were less than 2 years of age. The leading causes of hospitalisation were respiratory disease (pneumonia, bronchiolitis, and asthma), sepsis, and head injury, which was the major cause of the trauma motivated by violence. The average hospital admission in the unit was one week and the mortality rate was 15.6%, with one third of the deaths recorded in the first 72 hours of hospitalisation.

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Section: Resultscontrasting

confidence: 66%

“…After the first year of high intensive care, the risk of death is 3.4 times higher than the general population and the risk of mortality is high up to the fourth year after the discharge of the PICU. Age and the existence of preexisting serious illness are factors that influence the mortality rate and quality of life after discharge 11,12 .…”

Section: Resultsmentioning

confidence: 99%

Clinical-Epidemiological Profile of Hospitalised Patients in Paediatric Intensive Care Unit

Batista

Coelho

Trugilho

et al. 2015

J. Hum. Growth Dev.

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“…Esses escores foram desenvolvidos a partir da identificação de variáveis relevantes para o risco de mortalidade e pontuados após uma posterior análise estatística multivariada de regressão logística 9 .…”

Section: Introductionunclassified

Comparison of two prognostic scores (PRISM and PIM) at a pediatric intensive care unit

Martha¹,

García²,

Piva³

et al. 2005

J Pediatr (Rio J)

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Resultados: Internaram na unidade de terapia intensiva pediátri-ca 498 pacientes, sendo 77 excluídos. Dos 421 pacientes estudados, 33 (7,83%) foram a óbito. A mortalidade estimada pelo PRISM foi de 30,84 (7,22%), com standardized mortality rate 1,07 (0,74-1,50), z = -0,45. Pelo PIM, foi de 26,13 (6,21%), com standardized mortality rate 1,26 (0,87-1,77), z = -1,14. O teste de ajuste de Hosmer-Lemeshow obteve um qui-quadrado 9,23 (p = 0,100) para o PRISM e 27,986 (p < 0,001) para o PIM. A área abaixo da curva ROC foi 0,870 (0,810-0,930) para o PRISM e 0,845 (0,769-0,920) para o PIM. Teste de Spearman r = 0,65 (p < 0,001).Conclusão: Na análise dos testes podemos constatar que, embora o PIM apresente uma pior calibração no conjunto dos resultados, tanto o PRISM como o PIM apresentaram boa capacidade de discriminar entre sobreviventes e não sobreviventes, constituindo-se em ferramentas de desempenho comparáveis na avaliação prognóstica de pacientes pediá-tricos admitidos em nossa unidade. AbstractObjective: To compare the performance of the PRISM (Pediatric Risk of Mortality) and the PIM (Pediatric Index of Mortality) scores at a general pediatric intensive care unit, investigating the relation between observed mortality and survival and predicted mortality and survival.Methods: A contemporary cohort study undertaken between 1 June 1999 and 31 May 2000 at the Pontifícia Universidade Católica do Rio Grande do Sul, Hospital São Lucas pediatric intensive care unit. The inclusion criteria and the PRISM and PIM calculations were performed as set out in the original articles and using the formulae as published. Statistical analysis for model evaluation employed the Flora z test, Hosmer-Lemeshow goodness-of-fit test, ROC curve (receiver operating characteristic) and Spearmans correlation tests. The study was approved by the institutions Ethics CommitteeResults: Four hundred and ninety-eight patients were admitted to the pediatric intensive care unit, 77 of whom presented exclusion criteria. Thirty-three (7.83%) of the 421 patients studied died and 388 patients were discharged. Estimated mortality by PRISM was 30.84 (7.22%) with a standardized mortality rate of 1.07 (0.74-1.50), z = -0.45 and by PIM this was 26.13 (6.21%) with a standardized mortality rate of 1.26 (0.87-1.77), z = -1.14. The Hosmer-Lemeshow test gave a chi-square of 9.23 (p = 0.100) for PRISM and 27.986 (p < 0.001) for PIM. The area under the ROC curve was 0.870 (0.810-0.930) for PRISM and 0.845 (0.769-0.920) for PIM. The Spearman test returned r = 0.65 (p < 0.001).Conclusion: Analyzing the tests we can observe that, although the PIM test was less well calibrated overall, both PRISM and PIM offer a good capacity for discriminating between survivors and moribund patients. They are tools with comparable performance at the prognostic evaluation of the pediatric patients admitted to our unit.

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“…[12][13][14] Because of evolving medical practices and populationspecific characteristics, prognostic scoring systems may become obsolete and may not be relevant in certain patient populations. 12 The APACHE III prognostic scoring system was developed in 1991 with the use of physiologic data, age, chronic health, and disease components from a database of 17,440 unselected medical/surgical ICU admissions at 40 hospitals and was noted to have good predictive accuracy (receiver operated curve, 0.90) in that population.…”

Section: Commentmentioning

confidence: 99%

Utility of Acute Physiology, Age, and Chronic Health Evaluation (APACHE III) score in maternal admissions to the intensive care unit

Stevens¹,

Carroll²,

Promecene³

et al. 2006

American Journal of Obstetrics and Gynecology

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ABC of intensive care: Outcome data and scoring systems

Cited by 137 publications

References 0 publications

Clinical-Epidemiological Profile of Hospitalised Patients in Paediatric Intensive Care Unit

Clinical-Epidemiological Profile of Hospitalised Patients in Paediatric Intensive Care Unit

Comparison of two prognostic scores (PRISM and PIM) at a pediatric intensive care unit

Utility of Acute Physiology, Age, and Chronic Health Evaluation (APACHE III) score in maternal admissions to the intensive care unit

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