Síndrome do desconforto respiratório agudo: fatores prognósticos / Acute respiratory distress syndrome: prognostic factors

O conhecimento dos fatores prognósticos de pacientes com síndrome do desconforto respiratório agudo (SDRA) é importante para estabelecermos a gravidade da doença e para o planejamento de novas medidas terapêuticas. A revisão dos estudos epidemiológicos publicados nos últimos dez anos através do PubMed/Medline, utilizando o critério diagnóstico da Conferência Americana e Europeia de Consenso em SDRA de 1994, revelou os seguintes fatores prognósticos em pacientes com SDRA: fatores gerais — idade avançada, escores prognósticos gerais elevados (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score e Mortality Prediction Model) e escores para disfunção orgânica múltipla elevados (Multiple Organ Dysfunction Score, Logistic Organ Dysfunction Score e Sequential Organ Failure Assessment); e fatores específicos — relação pressão parcial arterial de oxigênio/fração inspirada de oxigênio baixa e presença dos elementos causais da SDRA, como pneumonia, sepse e choque. A SDRA secundária a trauma apresenta melhor prognóstico.

An understanding of the prognostic factors of acute respiratory distress syndrome (ARDS) is essential for determining its severity and for designing studies to evaluate potential therapies. A review of epidemiologic studies published in the last ten years in PubMed/Medline, using the 1994 American-European Consensus Conference diagnostic criteria, indicated that the following are prognostic factors for ARDS: general factors—advanced age, elevated general prognostic scores (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score, and Mortality Prediction Model), and elevated multiple organ systems dysfunction scores (Multiple Organ Dysfunction Score, Logistic Organ Dysfunction Score, and Sequential Organ Failure Assessment); and specific factors—low arterial carbon dioxide tension/fraction of inspired oxygen ratio and ARDS predisposing disorders, such as pneumonia, sepsis, and shock. The prognosis is better for patients with ARDS occurring secondary to major trauma than for those with ARDS of other etiologies. ARDS patients with the above risks factors constitute a population at high risk of in-hospital mortality.

Central venous saturation: a prognostic tool in cardiac surgery patients.

BACKGROUND: Central venous oxygen saturation (ScvO(2)) is a valuable prognostic marker in sepsis. However, its value in cardiac surgery has not been assessed yet. This study aimed at evaluating ScvO(2) as a tool for predicting short-term organ dysfunction (OD) after cardiac surgery. METHODS: A prospective cohort including cardiac surgery patients submitted to a goal-oriented therapy to maintain ScvO(2) above 70% was studied. Postoperative blood samples collected at 30 minutes (T1), 6 hours (T2), and 24 hours (T3) for ScvO(2) measurement were selected to further analysis. Two groups were formed according to the absence (G0) or presence (G1) of OD defined as a Sequential Organ Failure Assessment (SOFA) score >or=5 on the third postoperative day. A logistic regression analysis was performed to identify the variables independently associated with OD on the third postoperative day. RESULTS: From the 246 patients included, 54 (22%) developed OD and were defined as G1. The mortality rates in G0 and G1 were 1.6% and 31.5%, respectively (P < .001). In the comparative analysis between G0 and G1, the ScvO(2) values were remarkably lower in G1 at T1 (66.2 +/- 9.2 vs 62.3 +/- 11.6; P = .009), T2 (69.6 +/- 5.9 vs 63.5 +/- 9.4; P

Bronchopulmonary dysplasia prediction modelfor 7-day-old infants

OBJETIVO: Desenvolver um modelo preditivo capaz de identificar, ao final da primeira semana de vida, os recém-nascidos prematuros com maior probabilidade de evoluir para displasia broncopulmonar (DBP). MÉTODOS: Os dados foram coletados retrospectivamente entre janeiro de 1998 e julho de 2001, e prospectivamente de agosto de 2001 a julho de 2003. Foram incluídas todas as crianças nascidas na Instituição, com idade gestacional < 34 semanas e peso de nascimento < 1.500 g. Os principais fatores de risco foram submetidos inicialmente a uma análise univariada, seguida de regressão logística. As variáveis significativas foram utilizadas na montagem da fórmula para cálculo da probabilidade de ocorrência de DBP. O modelo foi calibrado, e a discriminação avaliada pela curva ROC. De agosto de 2003 a julho de 2005, o modelo foi aplicado em outra população para validação. RESULTADOS: Foram incluídas 247 crianças, das quais 68 evoluíram para DBP, sendo divididas da seguinte maneira: leve = 35 (51,4 por cento), moderada = 20 (29,4 por cento) e grave = oito (11,7 por cento). Quatro variáveis mantiveram significância em relação à DBP: idade gestacional < 30 semanas, persistência do canal arterial, ventilação mecânica > 2 dias e perda de > 15 por cento do peso de nascimento no sétimo dia de vida. Nos pacientes com todas as variáveis presentes, o modelo permitiu uma probabilidade de acerto de 93,7 por cento. Valores semelhantes foram obtidos com as 61 crianças utilizadas na validação do modelo. CONCLUSÕES O modelo preditivo desenvolvido em nossa população foi capaz de identificar com elevado grau de sensibilidade, ao final da primeira semana de vida, os recém-nascidos sob maior risco de evoluir para DBP.

OBJECTIVE: To develop a predictive model capable of identifying which premature infants have the greatest probability of presenting bronchopulmonary dysplasia (BPD), based on assessment at the end of their first week of life. METHODS: Data were collected retrospectively from January 1998 to July 2001, and prospectively from August 2001 to July 2003. All children born at the institution with gestational age < 34 weeks and birth weight < 1,500 g were included. The principal risk factors for BPD were subjected to univariate analysis followed by logistic regression. Significant variables were used to construct a formula to calculate the probability of BPD. The model was calibrated and its discriminative power assessed using receiver operating characteristic (ROC) curves. Between August 2003 and July 2005 the model was then applied to a different population for validation. RESULTS: The sample comprised 247 children, of whom 68 developed BPD, classified as follows: mild = 35 (51.4 percent), moderate = 20 (29.4 percent) and severe = 8 (11.7 percent). Four variables maintained significance with relation to BPD: gestational age < 30 weeks, persistent ductus arteriosus, mechanical ventilation > 2 days and loss of > 15 percent of birth weight on the seventh day of life. Where patients exhibited all of these variables, the model had a 93.7 percent probability of being correct. The model was further validated when using another sample of 61 newborns; similar figures were obtained. CONCLUSIONS: At the end of the first week of life, the predictive model developed from our population was capable of identifying newborn infants at increased risk of developing BPD with a high degree of sensitivity.

Bronchopulmonary dysplasia prediction model for 7-day-old infants.

OBJECTIVE: To develop a predictive model capable of identifying which premature infants have the greatest probability of presenting bronchopulmonary dysplasia (BPD), based on assessment at the end of their first week of life. METHODS: Data were collected retrospectively from January 1998 to July 2001, and prospectively from August 2001 to July 2003. All children born at the Institution with gestational age < 34 weeks and birth weight < 1,500 g were included. The principal risk factors for BPD were subjected to univariate analysis followed by logistic regression. Significant variables were used to construct a formula to calculate the probability of BPD. The model was calibrated and its discriminative power assessed using receiver operating characteristic (ROC) curves. Between August 2003 and July 2005 the model was then applied to a different population for validation. RESULTS: The sample comprised 247 children, of whom 68 developed BPD, classified as follows: mild = 35 (51.4%), moderate = 20 (29.4%) and severe = 8 (11.7 %). Four variables maintained significance with relation to BPD: gestational age < or = 30 weeks, persistent ductus arteriosus, mechanical ventilation > 2 days and loss of > 15% of birth weight on the seventh day of life. Where patients exhibited all of these variables, the model had a 93.7% probability of being correct. The model was further validated when using another sample of 61 newborns; similar figures were obtained. CONCLUSIONS: At the end of the first week of life, the predictive model developed from our population was capable of identifying newborn infants at increased risk of developing BPD with a high degree of sensitivity.

Prognosis of critically ill patients with cancer and acute renal dysfunction.

PURPOSE: To evaluate the outcomes of critically ill patients with cancer and acute renal dysfunction. PATIENTS AND METHODS: Prospective cohort study conducted at a 10-bed oncologic medical-surgical intensive care unit (ICU) over a 56-month period. RESULTS: Of 975 patients, 309 (32%) had renal dysfunction and were studied. Their mean age was 60.9 +/- 15.9 years; 233 patients (75%) had solid tumors and 76 (25%) had hematologic malignancies. During the ICU stay, 98 patients (32%) received dialysis. Renal dysfunction was multifactorial in 56% of the patients, and the main associated factors were shock/ischemia (72%) and sepsis (63%). Overall hospital and 6-month mortality rates were 64% and 73%, respectively. Among patients who required dialysis, mortality rates were lower in patients who received dialysis on the first day of ICU in comparison with those who required it thereafter. In a multivariable Cox model, age more than 60 years, uncontrolled cancer, impaired performance status, and more than two associated organ failures were associated with increased 6-month mortality. Renal function was completely re-established in 82% and partially re-established in 12%, and only 6% of survivors required chronic dialysis. CONCLUSION: Acute renal dysfunction is frequent in critically ill patients with cancer. Although mortality rates are high, selected patients can benefit from ICU care and advanced organ support. When evaluating prognosis and the appropriateness of dialysis in these patients, older age, functional capacity, cancer status and the severity of associated organ failures are important variables to take into consideration.

Effect of age on survival of critically ill patients with cancer.

OBJECTIVES: To estimate the effects of age on 6-month survival of critically ill patients with cancer. DESIGN: Prospective cohort study analyzed using Cox proportional hazard models. SETTING: Ten-bed oncologic medical-surgical intensive care unit. PATIENTS: Eight hundred sixty-two patients with cancer, excluding bone marrow transplant patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The mean age was 57.8+/-16.2 yrs. The hospital and 6-month mortality rates were 48% and 58%, respectively. Age was independently associated with increased mortality (hazard ratio, 1.015; 95% confidence interval, 1.009-1.021). Martingale residual analysis, however, suggested an inflection point in the effect of age, with an upward trend for patients aged>60 yrs. Therefore, patients were stratified in two groups: young (60 yrs, n=431, 50%). In young patients, uncontrolled cancer, mechanical ventilation, and number of organ failures were associated with poor outcome, whereas surgery before intensive care unit admission was protective. The variables associated with increased mortality for elderly patients were performance status 3-4, uncontrolled cancer, number of organ failures, and the presence of a severe comorbidity. In this group, age was associated with a lower survival rate. In general, the effect of covariates on the outcome was higher in the elderly group. CONCLUSIONS: Aging was associated with increased mortality, especially for patients>60 yrs. The severity of organ failures and the presence of uncontrolled cancer were the main predictive factors, but there were important differences among the outcome predictors for young and elderly patients. Our results suggest that selected older patients with cancer can benefit from intensive care.

Characteristics and outcomes of cancer patients requiring mechanical ventilatory support for >24 hrs.

OBJECTIVES: To describe the characteristics of a large cohort of cancer patients receiving mechanical ventilation for >24 hrs and to identify clinical features predictive of in-hospital death. DESIGN: Prospective cohort study. SETTING: Ten-bed oncologic medical-surgical intensive care unit. PATIENTS: A total of 463 consecutive patients were included over a 45-month period. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data were collected on the day of admission to the intensive care unit. The intensive care unit and hospital mortality rates were 50% and 64%, respectively. There were 359 (78%) patients with solid tumors and 104 (22%) with hematologic malignancies; 35 (8%) patients had leukopenia. Sepsis (63%), coma (15%), invasion or compression by tumor (11%), pulmonary embolism (7%), and cardiopulmonary arrest (6%) were the main reasons for mechanical ventilation. The independent unfavorable risk factors for mortality were older age (odds ratio, 3.09; 95% confidence interval, 1.61-5.93, for patients 40-70 yrs old, and odds ratio, 9.26; 95% confidence interval, 4.16-20.58, for patients >70 yrs old); performance status 3-4 (odds ratio, 2.51; 95% confidence interval, 1.40-4.51); cancer recurrence/progression (odds ratio, 3.43; 95% confidence interval, 1.81-6.53); Pao2/Fio2 ratio <150 (odds ratio, 2.64; 95% confidence interval, 1.40-4.99); Sequential Organ Failure Assessment score (excluding respiratory domain, each 4 points; odds ratio, 2.34; 95% confidence interval, 1.70-3.24); and airway/pulmonary invasion or compression by tumor as a reason for mechanical ventilation (odds ratio, 5.73; 95% confidence interval, 1.92-17.08). CONCLUSIONS: Severity of acute organ failures, poor performance status, cancer status, and older age were the main determinants of mortality. The appropriate use of such easily available clinical characteristics may avoid forgoing intensive care for patients with a chance of survival.

Impact of two different comorbidity measures on the 6-month mortality of critically ill cancer patients.

OBJECTIVE: To evaluate the impact of two different comorbidity measures on the 6-month mortality of severely ill cancer patients. DESIGN AND SETTING: Prospective cohort study in a ten-bed oncological medical-surgical intensive care unit (ICU). PATIENTS: A total of 772 consecutive patients were included over a 45-month period. The mean age was 57.6+/-16.4 years, and 642 (83%) patients had solid tumors. MEASUREMENTS AND RESULTS: Data were collected on admission and during ICU stay. Comorbidities were evaluated using the Charlson Comorbidity Index (CCI) and the Adult Comorbidity Evaluation (ACE-27). The ICU, hospital, and 6-month mortality rates were 34%, 47%, and 58%, respectively. The most frequent comorbidities were hypertension (33%), diabetes mellitus (8%), and chronic pulmonary disease (7%). There were important differences between the two indices regarding the comorbidity evaluation. Using the ACE-27, 389 patients (50%) had comorbid ailments that were classified as mild (31%), moderate (14%), and severe (5%) according to the comorbidity severity. According to the CCI, 212 patients (27%) had a comorbidity, and their median score was 1 (1-2). In the multivariable Cox proportional hazard models only the presence of a severe comorbidity by the ACE-27 was associated with increased mortality. The CCI was not independently associated with the outcome. Other outcome predictors were older age, poor performance status, active cancer, need of mechanical ventilation, and severity of acute organ failures. CONCLUSIONS: Severe comorbidities must be considered in the outcome evaluation of ICU cancer patients. The ACE-27 seems to be a useful instrument for prognostic assessment in this population.

Performance of six severity-of-illness scores in cancer patients requiring admission to the intensive care unit: a prospective observational study.

INTRODUCTION: The aim of this study was to evaluate the performance of five general severity-of-illness scores (Acute Physiology and Chronic Health Evaluation II and III-J, the Simplified Acute Physiology Score II, and the Mortality Probability Models at admission and at 24 hours of intensive care unit [ICU] stay), and to validate a specific score - the ICU Cancer Mortality Model (CMM) - in cancer patients requiring admission to the ICU. METHODS: A prospective observational cohort study was performed in an oncological medical/surgical ICU in a Brazilian cancer centre. Data were collected over the first 24 hours of ICU stay. Discrimination was assessed by area under the receiver operating characteristic curves and calibration was done using Hosmer-Lemeshow goodness-of-fit H-tests. RESULTS: A total of 1257 consecutive patients were included over a 39-month period, and 715 (56.9%) were scheduled surgical patients. The observed hospital mortality was 28.6%. Two performance analyses were carried out: in the first analysis all patients were studied; and in the second, scheduled surgical patients were excluded in order to better compare CMM and general prognostic scores. The results of the two analyses were similar. Discrimination was good for all of the six studied models and best for Simplified Acute Physiology Score II and Acute Physiology and Chronic Health Evaluation III-J. However, calibration was uniformly insufficient (P < 0.001). General scores significantly underestimated mortality (in comparison with the observed mortality); this was in contrast to the CMM, which tended to overestimate mortality. CONCLUSION: None of the model scores accurately predicted outcome in the present group of critically ill cancer patients. In addition, there was no advantage of CMM over the other general models.