Intensive care medicine · 2001
Results of respiratory mechanics analysis in the critically ill depend on the method employed.
Сравнительное исследованиеСтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Ruiz-Ferrón F, Rucabado Aguilar L, Ruiz Navarro S, Ramirez Puerta R, Parra Alonso S, Muñoz Muñoz J L
Аннотация
OBJECTIVE: To compare the measurements of total resistance and dynamic elastance determined by different techniques of respiratory mechanics analysis based on the time or frequency domains.
DESIGN: Prospective study.
SETTING: A 12-bed medical and surgical intensive care unit in a 700-bed university hospital.
PATIENTS: Eighteen sedoparalyzed patients who needed controlled mechanical ventilation for acute or chronic acute respiratory failure.
MEASUREMENTS: The total resistance and dynamic elastance in the time domain were determined by the occlusion technique and by multiple linear regression. The Fourier analysis was used to study the impedance of the respiratory system for elastance and resistance values in the frequency domain.
RESULTS: The ANOVA analysis of the elastance variable showed no statistical differences (Ef: 41.4+/-19.0 cmH(2)O/l, Emlr: 40.8+/-17.2 cmH(2)O/l Edyn,occ: 39.5+/-14.0 cmH(2)O/l; ns) and the correlation was very good (r=0.8-0.9). The total resistances were less with multiple linear regression (13.5+/-9.3 cmH(2)O/l per s, p<0.05) than Rmax (17.0+/-11.9 cmH(2)O/l per s) or Rf (17.6+/-10.2 cmH(2)O/l per s). There were no differences between Rmax and Rf (p=0.7) and the correlation between resistances was 0.7-0.9. The agreement analysis for variables without statistical differences showed the following limits: Edyn,occ-f: -17 to 13 cmH(2)O/l; Edyn,occ-mlr: -12 to 9 cmH(2)O/l; Emlr-f: -6 to 8 cmH(2)O/l; Rmax-f: -18 to 19 cmH(2)O/l per s. This last range was related to the autoPEEP level (r=0.9).
CONCLUSION: The wide agreement limits show that respiratory mechanics analysis is very dependent on the measurement technique used, particularly for resistance, perhaps due to the higher dependence on frequency.
DESIGN: Prospective study.
SETTING: A 12-bed medical and surgical intensive care unit in a 700-bed university hospital.
PATIENTS: Eighteen sedoparalyzed patients who needed controlled mechanical ventilation for acute or chronic acute respiratory failure.
MEASUREMENTS: The total resistance and dynamic elastance in the time domain were determined by the occlusion technique and by multiple linear regression. The Fourier analysis was used to study the impedance of the respiratory system for elastance and resistance values in the frequency domain.
RESULTS: The ANOVA analysis of the elastance variable showed no statistical differences (Ef: 41.4+/-19.0 cmH(2)O/l, Emlr: 40.8+/-17.2 cmH(2)O/l Edyn,occ: 39.5+/-14.0 cmH(2)O/l; ns) and the correlation was very good (r=0.8-0.9). The total resistances were less with multiple linear regression (13.5+/-9.3 cmH(2)O/l per s, p<0.05) than Rmax (17.0+/-11.9 cmH(2)O/l per s) or Rf (17.6+/-10.2 cmH(2)O/l per s). There were no differences between Rmax and Rf (p=0.7) and the correlation between resistances was 0.7-0.9. The agreement analysis for variables without statistical differences showed the following limits: Edyn,occ-f: -17 to 13 cmH(2)O/l; Edyn,occ-mlr: -12 to 9 cmH(2)O/l; Emlr-f: -6 to 8 cmH(2)O/l; Rmax-f: -18 to 19 cmH(2)O/l per s. This last range was related to the autoPEEP level (r=0.9).
CONCLUSION: The wide agreement limits show that respiratory mechanics analysis is very dependent on the measurement technique used, particularly for resistance, perhaps due to the higher dependence on frequency.
Предметные рубрики MeSH
Acute DiseaseAgedAged, 80 and overAnalysis of VarianceBiasChronic DiseaseCritical IllnessData Interpretation, StatisticalFourier AnalysisHumansLinear ModelsLung ComplianceMiddle AgedNumerical Analysis, Computer-AssistedPositive-Pressure Respiration, IntrinsicProspective StudiesRespiration, ArtificialRespiratory InsufficiencyRespiratory MechanicsSeverity of Illness IndexSignal Processing, Computer-Assisted