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Master's Dissertation
DOI
https://doi.org/10.11606/D.7.2019.tde-22022021-103402
Document
Author
Full name
Tatiane Gonçalves Gomes de Novais do Rio
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2019
Supervisor
Committee
Nogueira, Lilia de Souza (President)
Domingues, Cristiane de Alencar
Parreira, José Gustavo
Whitaker, Iveth Yamaguchi
Title in Portuguese
Índices de gravidade do trauma: capacidade preditiva para admissão e mortalidade de pacientes na unidade de terapia intensiva de um hospital privado
Keywords in Portuguese
Cuidados críticos
Curva ROC
Ferimentos e lesões
Hospitais
Índices de gravidade do trauma
Mortalidade
Saúde suplementar
Abstract in Portuguese
Introdução: há muito tempo se discute a definição do nível de gravidade do trauma, o qual pode ser determinado por índices de trauma. Atualmente, existem diversos índices na literatura que, em sua maioria, analisam a probabilidade de sobrevida (Ps) das vítimas de trauma. Entretanto, são escassos os estudos que utilizam os índices de trauma como preditores de admissão e mortalidade de traumatizados em Unidade de Terapia Intensiva (UTI), o que justifica a relevância desta pesquisa. Objetivo: avaliar a capacidade dos índices de gravidade do trauma na predição de admissão e mortalidade na UTI de doentes traumatizados. Método: coorte retrospectiva realizada por meio da análise de prontuários de pacientes atendidos entre 2014-2017 em hospital privado de São Paulo. Os critérios de inclusão dos doentes foram: ser vítima de trauma contuso ou penetrante, ter idade 18 anos e ser admitido no hospital em até 24 horas do evento traumático. Foram analisados os índices Revised Trauma Score (RTS), New Trauma Score (NTS), Injury Severity Score (ISS), New Injury Severity Score (NISS), Trauma and Injury Severity Score (TRISS), New Trauma and Injury Severity Score (NTRISS), Base-deficit Injury Severity Score (BISS) e Base- deficit and New Injury Severity Score (BNISS). Os testes Qui-Quadrado de Pearson, Exato de Fisher, Wilcoxon-Mann-Whitney e Brunner-Munzel, além de Receiver Operating Characteristic Curves e área sob a curva (AUC) foram utilizados nas análises (nível de significância de 5%). Resultados: a casuística foi composta por 747 pacientes, a maioria do sexo feminino (52,5%) e média de idade de 51,5 (±21,3) anos. O mecanismo de trauma contuso (89,4%) e as quedas (36,1%) prevaleceram. As médias do RTS, NTS, mREMS, ISS e NISS foram 7,8 (±0,3), 10,5 (±0,5), 2,1 (±2,3), 3,4 (±5,5) e 4,3 (±7,1), respectivamente. A média da Ps indicada pelos índices TRISS e NTRISS superou 98,0%. O BNISS apresentou menor média (78,8%) de Ps que o BISS (82,9%). Um total de 106 pacientes foi admitido na UTI. Houve diferença significativa (p<0,050) entre os grupos (pacientes admitidos versus não admitidos na UTI) em relação às variáveis sexo, idade, mecanismo do trauma, causa externa, atendimento pré-hospitalar e gravidade segundo RTS, NTS, mREMS, ISS, NISS, TRISS e NTRISS. Os índices ISS (AUC 0,919) e NISS (AUC 0,916) apresentaram melhor capacidade preditiva para admissão dos pacientes na UTI. A análise comparativa dos grupos (100 sobreviventes e 6 não sobreviventes na UTI) mostrou diferença significativa (p<0,050) entre eles em relação aos índices NTS, mREMS, ISS, NISS, TRISS, NTRISS, BISS e BNISS. O NISS (AUC 0,949), TRISS (AUC 0,909), NTRISS (AUC 0,967), BISS (AUC 0,902) e BNISS (AUC 0,976) apresentaram excelente desempenho na predição de mortalidade dos pacientes da UTI. Conclusão: os índices anatômicos apresentaram melhor capacidade preditiva para admissão na UTI. Em relação à mortalidade, o NISS e os índices mistos tiveram os melhores desempenhos. Por fim, aplicar o índice de trauma mais assertivo para admissão e mortalidade na UTI tem potencial para auxiliar os profissionais em processos decisórios sobre alocação de recursos e estratégias para melhoria da qualidade da assistência aos pacientes.
Title in English
Trauma Severity Indices: Predictive capacity for admission and mortality of patients in the intensive care unit of a private hospital.
Keywords in English
Critical Care
Hospitals
Mortality
ROC Curve
Supplemental Health
Trauma Severity Indices
Wounds and Injuries
Abstract in English
Introduction: Historically, we defined the severity level of trauma using trauma indices. Currently, several indices in the literature analyze the probability of survival (Ps) of trauma victims. However, there are few studies that use trauma indices as predictors of the admission and mortality of traumatized patients in the intensive care unit (ICU), which justifies the relevance of this research. Objective: to evaluate the ability of trauma severity indices to predict admission and mortality of trauma patients in the ICU. Method: a retrospective cohort study conducted through the analysis of medical records of patients attended between 20142017 in a private hospital in São Paulo. The inclusion criteria for patients were being a victim of blunt or penetrating trauma, aged 18 years and admitted to the hospital within 24 hours of the traumatic event. We analyzed the following indices: Revised Trauma Score (RTS), New Trauma Score (NTS), modified Rapid Emergency Score (mREMS), Injury Severity Score (ISS), New Injury Severity Score (NISS), Trauma and Injury Severity Score (TRISS), New Trauma and Injury Severity Score (NTRISS), Base-Deficit Injury Severity Score (BISS) and Base-Deficit and New Injury Severity Score (BNISS). Pearsons chi-squared, Fishers exact, Wilcoxon-Mann-Whitney and Brunner-Munzel tests, in addition to Receiver Operating Characteristic Curves and area under the curve (AUC), were used in the analysis (significance level of 5%). Results: The sample consisted of 747 patients, 52.5% females, with a mean age of 51.5 (± 21.3) years. The blunt trauma (89.4%) and falls (36.1%) prevailed. The averages of the index scores were as follows: RTS, 7.8 (±0.3), NTS, 10.5 (±0.5), mREMS, 2.1 (±2.3), ISS, 3.4 (±5.5) and NISS, 4.3 (±7.1). The mean Ps indicated by the TRISS and NTRISS indices exceeded 98.0%. The BNISS showed a lower mean (78.8%) of Ps than BISS (82.9%). A total of 106 patients were admitted to the ICU. There was a significant difference (P < .050) between the groups (patients admitted vs not admitted to the ICU) in relation to the variables gender, age, mechanism of trauma, external cause, pre-hospital care and severity according to RTS, NTS, mREMS, ISS, NISS, TRISS and NTRISS. The ISS (AUC 0.919) and NISS (AUC 0.916) indices presented better predictive capacity for ICU patient admission. The comparative analysis of the groups (100 survivors and 6 non-survivors in the ICU) showed a significant difference (p<.050) between them in relation to the NTS, mREMS, ISS, NISS, TRISS, NTRISS, BISS and BNISS indices. The NISS (AUC 0.949), TRISS (AUC 0.909), NTRISS (AUC 0.967), BISS (AUC 0.902) and BNISS (AUC 0.976) presented excellent performance in predicting the mortality of ICU patients. Conclusion: the anatomical indices presented better predictive capacity for ICU admission. In relation to mortality, NISS and the mixed indices had the best performances. Finally, applying the most assertive trauma index for admission and mortality in the ICU has the potential to help professionals in decision-making processes about resource allocation and strategies to improve the quality of patient care.
 
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2021-02-25
 
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