RESUMEN
BACKGROUND: Despite the need for specific weaning strategies in neurological patients, evidence is generally insufficient or lacking. We aimed to describe the evolution over time of weaning and extubation practices in patients with acute brain injury compared with patients who are mechanically ventilated (MV) due to other reasons. METHODS: We performed a secondary analysis of three prospective, observational, multicenter international studies conducted in 2004, 2010, and 2016 in adults who had need of invasive MV for more than 12 h. We collected data on baseline characteristics, variables related to management ventilator settings, and complications while patients were ventilated or until day 28. RESULTS: Among the 20,929 patients enrolled, we included 12,618 (60%) who started the weaning from MV, of whom 1722 (14%) were patients with acute brain injury. In the acutely brain-injured cohort, 538 patients (31%) did not undergo planned extubation, defined as the need for a tracheostomy without an attempt of extubation, accidental extubation, and death. Among the 1184 planned extubated patients with acute brain injury, 202 required reintubation (17%). Patients with acute brain injury had a higher odds for unplanned extubation (odds ratio [OR] 1.35, confidence interval for 95% [CI 95%] 1.19-1.54; p < 0.001), a higher odds of failure after the first attempt of weaning (spontaneous breathing trial or gradual reduction of ventilatory support; OR 1.14 [CI 95% 1.01-1.30; p = 0.03]), and a higher odds for reintubation (OR 1.41 [CI 95% 1.20-1.66; p < 0.001]) than patients without brain injury. Patients with hemorrhagic stroke had the highest odds for unplanned extubation (OR 1.47 [CI 95% 1.22-1.77; p < 0.001]), of failed extubation after the first attempt of weaning (OR 1.28 [CI 95% 1.06-1.55; p = 0.009]), and for reintubation (OR 1.49 [CI 95% 1.17-1.88; p < 0.001]). In relation to weaning evolution over time in patients with acute brain injury, the risk for unplanned extubation showed a downward trend; the risk for reintubation was not associated to time; and there was a significant increase in the percentage of patients who underwent extubation after the first attempt of weaning from MV. CONCLUSIONS: Patients with acute brain injury, compared with patients without brain injury, present higher odds of undergoing unplanned extubated after weaning was started, lower odds of being extubated after the first attempt, and a higher risk of reintubation.
Asunto(s)
Lesiones Encefálicas , Desconexión del Ventilador , Adulto , Humanos , Estudios Prospectivos , Extubación Traqueal , Intubación Intratraqueal , Lesiones Encefálicas/terapia , Respiración ArtificialRESUMEN
OBJECTIVES: To describe the changes in ventilator management over time in patients with neurologic disease at ICU admission and to estimate factors associated with 28-day hospital mortality. DESIGN: Secondary analysis of three prospective, observational, multicenter studies. SETTING: Cohort studies conducted in 2004, 2010, and 2016. PATIENTS: Adult patients who received mechanical ventilation for more than 12 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among the 20,929 patients enrolled, we included 4,152 (20%) mechanically ventilated patients due to different neurologic diseases. Hemorrhagic stroke and brain trauma were the most common pathologies associated with the need for mechanical ventilation. Although volume-cycled ventilation remained the preferred ventilation mode, there was a significant (p < 0.001) increment in the use of pressure support ventilation. The proportion of patients receiving a protective lung ventilation strategy was increased over time: 47% in 2004, 63% in 2010, and 65% in 2016 (p < 0.001), as well as the duration of protective ventilation strategies: 406 days per 1,000 mechanical ventilation days in 2004, 523 days per 1,000 mechanical ventilation days in 2010, and 585 days per 1,000 mechanical ventilation days in 2016 (p < 0.001). There were no differences in the length of stay in the ICU, mortality in the ICU, and mortality in hospital from 2004 to 2016. Independent risk factors for 28-day mortality were age greater than 75 years, Simplified Acute Physiology Score II greater than 50, the occurrence of organ dysfunction within first 48 hours after brain injury, and specific neurologic diseases such as hemorrhagic stroke, ischemic stroke, and brain trauma. CONCLUSIONS: More lung-protective ventilatory strategies have been implemented over years in neurologic patients with no effect on pulmonary complications or on survival. We found several prognostic factors on mortality such as advanced age, the severity of the disease, organ dysfunctions, and the etiology of neurologic disease.
Asunto(s)
Unidades de Cuidados Intensivos/estadística & datos numéricos , Enfermedades del Sistema Nervioso/mortalidad , Enfermedades del Sistema Nervioso/terapia , Respiración Artificial/métodos , Respiración Artificial/tendencias , Adulto , Factores de Edad , Anciano , Lesiones Traumáticas del Encéfalo/mortalidad , Lesiones Traumáticas del Encéfalo/terapia , Femenino , Accidente Cerebrovascular Hemorrágico/mortalidad , Accidente Cerebrovascular Hemorrágico/terapia , Mortalidad Hospitalaria/tendencias , Humanos , Accidente Cerebrovascular Isquémico/mortalidad , Accidente Cerebrovascular Isquémico/terapia , Tiempo de Internación/tendencias , Masculino , Persona de Mediana Edad , Estudios Multicéntricos como Asunto , Ventilación no Invasiva/tendencias , Estudios Observacionales como Asunto , Estudios Prospectivos , Factores de Riesgo , Puntuación Fisiológica Simplificada Aguda , Traqueotomía/estadística & datos numéricos , Traqueotomía/tendencias , Desconexión del Ventilador/tendenciasRESUMEN
No accurate and rapid diagnostic test exists for tuberculous meningitis (TBM), leading to delayed diagnosis. We leveraged data from multiple studies to improve the predictive performance of diagnostic models across different populations, settings, and subgroups to develop a new predictive tool for TBM diagnosis. We conducted a systematic review to analyze eligible datasets with individual-level participant data (IPD). We imputed missing data and explored three approaches: stepwise logistic regression, classification and regression tree (CART), and random forest regression. We evaluated performance using calibration plots and C-statistics via internal-external cross-validation. We included 3,761 individual participants from 14 studies and nine countries. A total of 1,240 (33%) participants had "definite" (30%) or "probable" (3%) TBM by case definition. Important predictive variables included cerebrospinal fluid (CSF) glucose, blood glucose, CSF white cell count, CSF differential, cryptococcal antigen, HIV status, and fever presence. Internal validation showed that performance varied considerably between IPD datasets with C-statistic values between 0.60 and 0.89. In external validation, CART performed the worst (C = 0.82), and logistic regression and random forest had the same accuracy (C = 0.91). We developed a mobile app for TBM clinical prediction that accounted for heterogeneity and improved diagnostic performance (https://tbmcalc.github.io/tbmcalc). Further external validation is needed.