Acute lung injury prediction score: derivation and validation in a population based sample (original) (raw)
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Egyptian Journal of Chest Diseases and Tuberculosis, 2013
Background: Acute lung injury (ALI) is an example of a critical care syndrome with few therapeutic modalities once the syndrome is fully established, and little has been done on the prevention of ALI. Aim of the work: The aim of this work was to early identify the onset of acute lung injury (ALI) on admission and to prospectively evaluate the lung injury prediction score (LIPS). Patients and methods: The study was carried out on 100 patients who aged >18 years, patients who had one or more of the acute lung injury (ALI) predisposing conditions on admission or within 6 h after were subjected to lung injury prediction score (LIPS). Results: Acute lung injury developed in 15 patients, 11 patients (73.3%) had LIPS >3, while 4 patients (26.7%) had LIPS 63 and only 4.70% of those who didn't develop ALI had LIPS >3, with a statistically significant relationship between patients above and below LIPS value of 3 (P = 0.000), LIPS cutoff value of P3.5 on admission had a 73% sensitivity and 95% specificity with an area under the receiver operating curve of 0.883 (95% CI 0.782 to 0.984). Sepsis and pneumonia were the most frequent risk factors (60%). Conclusions: Lung injury predictive score (LIPS) could early predict patients at risk to develop ALI on admission, Hyperbilirubinemia, high blood urea level and abnormal chest X-ray on admission were not included in the original LIPS but had significant association with development of ALI.
International Journal of Emergency Medicine, 2012
Background: Early identification of patients at risk of developing acute lung injury (ALI) is critical for potential preventive strategies. We aimed to derive and validate an acute lung injury prediction score (EDLIPS) in a multicenter sample of emergency department (ED) patients. Methods: We performed a subgroup analysis of 4,361 ED patients enrolled in the previously reported multicenter observational study. ED risk factors and conditions associated with subsequent ALI development were identified and included in the EDLIPS model. Scores were derived and validated using logistic regression analyses. The model was assessed with the area under the receiver-operating curve (AUC) and compared to the original LIPS model (derived from a population of elective high-risk surgical and ED patients) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score. Results: The incidence of ALI was 7.0% (303/4361). EDLIPS discriminated patients who developed ALI from those who did not with an AUC of 0.78 (95% CI 0.75, 0.82), better than the APACHE II AUC 0.70 (p ≤ 0.001) and similar to the original LIPS score AUC 0.80 (p = 0.07). At an EDLIPS cutoff of 5 (range −0.5, 15) positive and negative likelihood ratios (95% CI) for ALI development were 2.74 (2.43, 3.07) and 0.39 (0.30, 0.49), respectively, with a sensitivity 0.72(0.64, 0.78), specificity 0.74 (0.72, 0.76), and positive and negative predictive value of 0.18 (0.15, 0.21) and 0.97 (0.96, 0.98). Conclusion: EDLIPS may help identify patients at risk for ALI development early in the course of their ED presentation. This novel model may detect at-risk patients for treatment optimization and identify potential patients for ALI prevention trials.
Early Identification of Patients at Risk of Acute Lung Injury
American Journal of Respiratory and Critical Care Medicine, 2011
Rationale: Accurate, early identification of patients at risk for developing acute lung injury (ALI) provides the opportunity to test and implement secondary prevention strategies. Objectives: To determine the frequency and outcome of ALI development in patients at risk and validate a lung injury prediction score (LIPS). Methods: In this prospective multicenter observational cohort study, predisposing conditions and risk modifiers predictive of ALI development were identified from routine clinical data available during initial evaluation. The discrimination of the model was assessed with area under receiver operating curve (AUC). The risk of death from ALI was determined after adjustment for severity of illness and predisposing conditions. Measurements and Main Results: Twenty-two hospitals enrolled 5,584 patients at risk. ALI developed a median of 2 (interquartile range 1-4) days after initial evaluation in 377 (6.8%; 148 ALI-only, 229 adult respiratory distress syndrome) patients. The frequency of ALI varied according to predisposing conditions (from 3% in pancreatitis to 26% after smoke inhalation). LIPS discriminated patients who developed ALI from those who did not with an AUC of 0.80 (95% confidence interval, 0.78-0.82). When adjusted for severity of illness and predisposing conditions, development of ALI increased the risk of in-hospital death (odds ratio, 4.1; 95% confidence interval, 2.9-5.7). Conclusions: ALI occurrence varies according to predisposing conditions and carries an independently poor prognosis. Using routinely available clinical data, LIPS identifies patients at high risk for ALI early in the course of their illness. This model will alert clinicians about the risk of ALI and facilitate testing and implementation of ALI prevention strategies. Clinical trial registered with www.clinicaltrials.gov (NCT00889772).
Towards the prevention of acute lung injury: a population based cohort study protocol
BMC emergency …, 2010
Background: Acute lung injury (ALI) is an example of a critical care syndrome with limited treatment options once the condition is fully established. Despite improved understanding of pathophysiology of ALI, the clinical impact has been limited to improvements in supportive treatment. On the other hand, little has been done on the prevention of ALI. Olmsted County, MN, geographically isolated from other urban areas offers the opportunity to study clinical pathogenesis of ALI in a search for potential prevention targets. Methods/Design: In this population-based observational cohort study, the investigators identify patients at high risk of ALI using the prediction model applied within the first six hours of hospital admission. Using a validated system-wide electronic surveillance, Olmsted County patients at risk are followed until ALI, death or hospital discharge. Detailed in-hospital (second hit) exposures and meaningful short and long term outcomes (qualityadjusted survival) are compared between ALI cases and high risk controls matched by age, gender and probability of developing ALI. Time sensitive biospecimens are collected for collaborative research studies. Nested case control comparison of 500 patients who developed ALI with 500 matched controls will provide an adequate power to determine significant differences in common hospital exposures and outcomes between the two groups. Discussion: This population-based observational cohort study will identify patients at high risk early in the course of disease, the burden of ALI in the community, and the potential targets for future prevention trials.
Predictors of Acute Lung Injury
2013
This report is published in the interest of scientific and technical information exchange, and its publication does not constitute the Government's approval or disapproval of its ideas or findings.
An alternative method of acute lung injury classification for use in observational studies
Chest, 2010
In observational studies using acute lung injury (ALI) as an outcome, a spectrum of lung injury and diffi cult-to-interpret chest radiographs (CXRs) may hamper efforts to uncover risk factor associations. We assessed the impact of excluding patients with diffi cult-to-classify or equivocal ALI diagnosis on clinical and genetic risk factor associations for ALI after trauma.
Critical care medicine, 2011
An independent cohort of acute lung injury (ALI) patients was used to evaluate the external validity of a simple prediction model for short-term mortality previously developed using data from ARDS Network (ARDSNet) trials. ... Data for external validation were obtained from a prospective cohort study of ALI patients from 13 ICUs at four teaching hospitals in Baltimore, Maryland. ... Of the 508 non-trauma, ALI patients eligible for this analysis, 234 (46%) died in-hospital. Discrimination of the ARDSNet prediction model for inhospital mortality, evaluated by the area under the ...
Epidemiology and outcome of acute lung injury
Objectives: To reexamine the epidemiology of acute lung injury (ALI) in European intensive care units (ICUs). Design and setting: A 2-month inception cohort study in 78 ICUs of 10 European countries. Patients: All patients admitted for more than 4 h were screened for ALI and followed up to 2 months. Measurements and main results: Acute lung injury occurred in 463 (7.1%) of 6,522 admissions and 16.1% of all mechanically ventilated patients; 65.4% cases occurred on ICU admission. Among 136 patients initially presenting with "mild ALI" (200< PaO 2 /FiO 2 £300), 74 (55%) evolved to acute respiratory distress syndrome (ARDS) within 3 days. Sixty-two patients (13.4%) remained with mild ALI and 401 had ARDS. The crude ICU and hospital mortalities were 22.6% and 32.7% (p<0.001), and 49.4% and 57.9% (p=0.0005), respectively, for mild ALI and ARDS. ARDS patients initially received a mean tidal volume of 8.3±1.9 ml/kg and a mean PEEP of 7.7±3.6 cmH 2 O; air leaks occurred in 15.9%. After multivariate analysis, mortality was associated with age (odds ratio (OR) =1.2 per 10 years; 95% confidence interval (CI): 1.05-1.36), immuno-incompetence (OR: 2.88; Cl: 1.57-5.28), the severity scores SAPS II (OR: 1.16