Perfil epidemiológico de dezesseis anos de uma unidade de terapia intensiva pediátrica

Einloft, Paulo Roberto; García, Pedro Celiny Ramos; Piva, Jefferson Pedro; Bruno, Francisco; Kipper, Délio José; Fiori, Renato Machado

doi:10.1590/s0034-89102002000700011

Cited by 39 publications

(49 citation statements)

References 14 publications

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“…The mean length of stay in hospital was 6.9 ± 5.5 days. These data are similar to those in previous studies [6][7][8][9] .…”

Section: Resultssupporting

confidence: 93%

“…This is close to what was found by other authors, including Sfoggia et al 17 and Einloft et al 7 , who found a frequency of surgical admissions of 25.8% and 20.3%, respectively. Regarding the involvement of organs and systems, Khilnani et al 9 and Linhares et al 12 reported results similar to those found in our study.…”

Section: Resultssupporting

confidence: 92%

“…The annual average admissions identified in the study are similar to those observed by Einloft et al 7 . The uniform monthly distribution of hospitalisations during the study may be explained by individual clinical condition that need or don't need intensive care, not related to seasonality, except for some diseases as bronchiolitis, chickenpox, and dengue.…”

Section: Resultssupporting

confidence: 90%

“…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. The percentage of mortality differences may be related mainly to the indications of hospitalisation in the PICU; to the clinical conditions at admission and the high availability of beds and resources to hospitalise patients before clinical deterioration or increased tissue damage.…”

Section: Resultscontrasting

confidence: 65%

“…In a study conducted in a PICU in Rio Grande do Sul, Brazil, covering a period of 16 years, Einloft et al 7 noted that the deaths occurring within the first 24 hours of admission ranged from 12% to 70% of the total. Thinking about fatal events or those resulting in permanent sequels, interrupting the normal development trajectory and causing great impact on the family, is needed 24 .…”

Section: Resultsmentioning

confidence: 99%

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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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“…The mean length of stay in hospital was 6.9 ± 5.5 days. These data are similar to those in previous studies [6][7][8][9] .…”

Section: Resultssupporting

confidence: 93%

Section: Resultssupporting

confidence: 92%

Section: Resultssupporting

confidence: 90%

Section: Resultscontrasting

confidence: 65%

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

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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Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?

et al. 2019

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Background Identifying children at malnutrition risk on admission to hospital is considered best practice; however, nutrition screening in pediatric populations is not common. The aim of this study was to determine which screening tool is able to identify children with malnutrition on admission to hospital. Methods A nurse administered 2 pediatric nutrition screening tools, Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) and Pediatric Nutrition Screening Tool (PNST) to patients admitted to medicine and surgery units (n = 165). The Subjective Global Nutritional Assessment (SGNA) was then completed by a dietitian, blinded to the results of the screens. Sensitivity, specificity, and κ were calculated for both screening tools against the SGNA. A receiver operating characteristic (ROC) curve assessed alternate cutoffs for each tool. Length of hospital stay (LOS) was used to assess prospective validity. Results Using the recommended cutoffs, the sensitivity of STRONGkids was 89%, specificity 35%, and κ 0.483. The sensitivity of PNST was 58%, specificity 88%, and κ 0.601. Using adjusted cutoffs, PNST's sensitivity improved to 87%, specificity 71%, and κ 0.681, and STRONGkids specificity improved to 61%, sensitivity 80%, and κ 0.5. Children identified at nutrition risk had significantly longer LOS (P < 0.05). Conclusion This study showed neither tool was appropriate for clinical use based on published cutoffs. By adjusting the cutoffs using ROC curve analysis, both tools improved overall agreement with the SGNA without significantly impacting the prospective validity. PNST with adjusted cutoffs is the most appropriate for clinical use in this population.

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Update to the pediatric Subjective Global Nutritional Assessment (SGNA)

et al. 2022

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Lack of a standardized method of identifying and defining pediatric malnutrition has led to an inability to fully understand the prevalence of and impact that malnutrition has on pediatric patients and the healthcare system. The Subjective Global Nutritional Assessment (SGNA) is an assessment tool meant to determine presence and severity of malnutrition in pediatric populations. However, the anthropometric section of the tool contains some out-dated parameters. This has limited its clinical practicality. The aim of this paper is to propose updates to the anthropometrics section of the SGNA. A retrospective analysis of 153 SGNA's performed on children aged 1 month to 16 years was completed, comparing the original SGNA results to SGNA results incorporating updated anthropometric parameters for percentiles and ideal body weight. The category of length/height for age was updated to include z score cutoffs rather than percentiles, and ideal body weight was updated to z scores for weight for length or body mass index (BMI). Two serial growth questions were updated in wording only, to reflect z score trends. The results of the analysis showed these updates would have changed the rankings of eight patients (5%) for length/height for age, and 20 patients (13%) for ideal body weight to weight for length or BMI.Adjustments to these questions did not impact the overall SGNA rating. This study shows updates to the SGNA are not expected to have a significant impact on the validity of the tool and has the potential to improve its applicability to current day practice.

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Perfil epidemiológico de dezesseis anos de uma unidade de terapia intensiva pediátrica

Cited by 39 publications

References 14 publications

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

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

Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?

Update to the pediatric Subjective Global Nutritional Assessment (SGNA)

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