医学
耐受性
机械通风
重症监护室
重症监护
观察研究
肠外营养
肠内给药
麻醉
禁忌症
内科学
重症监护医学
不利影响
病理
替代医学
作者
José Luis Flordelís Lasierra,Juan Carlos Montejo,Juan Carlos Lopez‐Delgado,Paola Zárate Chug,Fátima Martínez Lozano‐Aranaga,C. Lorencio,M.L. Bordejé Laguna,Silmary Maichle,Luis Juan Terceros Almanza,María Victoria Trasmonte Martínez,L Mateu Campos,Luis Serviá,C. Vaquerizo Alonso,Belén Vila García
摘要
Enteral nutrition (EN) in critically ill patients requiring vasoactive drug (VAD) support is controversial. This study assesses the tolerability and safety of EN in such patients.This prospective observational study was conducted in 23 intensive care units (ICUs) over 30 months. Inclusion criteria were a need for VADs and/or mechanic circulatory support (MCS) over a minimum of 48 h, a need for ≥48 h of mechanical ventilation, an estimated life expectancy >72 h, and ≥72 h of ICU stay. Patients with refractory shock were excluded. EN was performed according to established protocols during which descriptive, daily hemodynamic and efficacy, and safety data were collected. An independent research group conducted the statistical analysis.Of 200 patients included, 30 (15%) required MCS and 145 (73%) met early multiorgan dysfunction criteria. Mortality was 24%. Patients needed a mean dose of norepinephrine in the first 48 h of 0.71 mcg/kg/min (95% CI, 0.63-0.8) targeting a mean arterial pressure of 68 mm Hg (95% CI, 67-70) during the first 48 h. EN was started 34 h (95% CI, 31-37) after ICU admission. Mean energy and protein delivered by EN/patient/day were 1159 kcal (95% CI, 1098-1220) and 55.6 g (95% CI, 52.4-58.7), respectively. Daily energy balance during EN/patient/day was -432 (95% CI, -496 to -368). One hundred and fifty-four (77%) patients experienced EN-related complications. However, severe complications, such as mesenteric ischemia, were recorded in only one (0.5%) patient.EN in these patients seems feasible, safe, and unrelated to serious complications. Reaching the energy target only through EN is difficult.
科研通智能强力驱动
Strongly Powered by AbleSci AI