Gastrointestinal complications following cardiac surgery remain rare with an incidence <1% in a contemporary series. The key to a lower incidence of GICs lies in systematic application of preventive measures and new advances in intraoperative management. Identification of independent risk factors would facilitate the determination of patients who would benefit from additional perioperative monitoring. Future resources should therefore be redirected to mitigate GICs in high-risk patients.

Delirium is a common complication following cardiac surgery, and the predictors of delirium remain unclear. The authors performed a prospective observational analysis to develop a predictive model for postoperative delirium using demographic and procedural parameters. A total of 112 adult postoperative cardiac surgical patients were evaluated twice daily for delirium using the Richmond Agitation-Sedation Scale (RASS) and Confusion Assessment Model for the ICU (CAM-ICU). The incidence of delirium was 34% (n = 38). Increased age (odds ratio [OR] = 2.5; 95% confidence interval [CI] = 1.6-3.9; P < .0001, per 10 years) and increased duration of surgery (OR = 1.3; 95% CI = 1.1-1.5; P = .0002, per 30 minutes) were independently associated with postoperative delirium. Gender, BMI, diabetes mellitus, preoperative ejection fraction, surgery type, length of cardiopulmonary bypass, intraoperative blood component administration, Acute Physiology and Chronic Health Evaluation II score, Sequential Organ Failure Assessment score, and Charlson Comorbidity Index, were not independently associated with postoperative delirium.

Objectives: Past studies have examined numerous components of tele-ICU care to decipher which elements increase patient and institutional benefit. These factors include review of the patient chart within 1 hour, frequent collaborative data reviews, mechanisms for rapid laboratory/alert review, and interdisciplinary rounds. Previous meta-analyses have found an overall ICU mortality benefit implementing tele-ICU, however, subgroup analyses found few differences. The purpose of this systematic review and meta-analysis was to explore the effect of tele-ICU implementation with regard to ICU mortality and explore subgroup differences via observed and predicted mortality. Data Sources: We searched PubMed, Cochrane Library, Embase, and European Society of Intensive Care Medicine for articles related to tele-ICU from inception to September 18, 2018. Study Selection: We included all trials meeting inclusion criteria which looked at the effect of tele-ICU implementation on ICU mortality. Data Extraction: We abstracted study characteristics, patient characteristics, severity of illness scores, and ICU mortality rates. Data Synthesis: We included 13 studies from 2,766 abstracts identified from our search strategy. The before-after tele-ICU implementation pooled odds ratio for overall ICU mortality was 0.75 (95% CI, 0.65–0.88; p < 0.001). In subgroup analysis, the pooled odds ratio for ICU mortality between the greater than 1 versus less than 1 observed to predicted mortality ratios was 0.64 (95% CI, 0.52–0.77; p < 0.001) and 0.98 (95% CI, 0.81–1.18; p = 0.81), respectively. Test for interaction was significant (p = 0.002). Conclusions: After evaluating all included studies, tele-ICU implementation was associated with an overall reduction in ICU mortality. Subgroup analysis suggests that publications exhibiting observed to predicted ICU mortality ratios of greater than 1 before tele-ICU implementation was associated with a reduction in ICU mortality after tele-ICU implementation. No significant ICU mortality reduction was noted in the subgroup of observed to predicted ICU mortality ratio less than 1 before tele-ICU implementation. Future studies should confirm this finding using patient-level data.