Effectiveness of automated alerting system compared to usual care for the management of sepsis

Abstract

There is a large body of evidence showing that delayed initiation of sepsis bundle is associated with adverse clinical outcomes in patients with sepsis. However, it is controversial whether electronic automated alerts can help improve clinical outcomes of sepsis. Electronic databases are searched from inception to December 2021 for comparative effectiveness studies comparing automated alerts versus usual care for the management of sepsis. A total of 36 studies are eligible for analysis, including 6 randomized controlled trials and 30 non-randomized studies. There is significant heterogeneity in these studies concerning the study setting, design, and alerting methods. The Bayesian meta-analysis by using pooled effects of non-randomized studies as priors shows a beneficial effect of the alerting system (relative risk [RR]: 0.71; 95% credible interval: 0.62 to 0.81) in reducing mortality. The automated alerting system shows less beneficial effects in the intensive care unit (RR: 0.90; 95% CI: 0.73–1.11) than that in the emergency department (RR: 0.68; 95% CI: 0.51–0.90) and ward (RR: 0.71; 95% CI: 0.61–0.82). Furthermore, machine learning-based prediction methods can reduce mortality by a larger magnitude (RR: 0.56; 95% CI: 0.39–0.80) than rule-based methods (RR: 0.73; 95% CI: 0.63–0.85). The study shows a statistically significant beneficial effect of using the automated alerting system in the management of sepsis. Interestingly, machine learning monitoring systems coupled with better early interventions show promise, especially for patients outside of the intensive care unit.

Accuracy and Systematic Biases of Heart Rate Measurements by Consumer-Grade Fitness Trackers in Postoperative Patients: Prospective Clinical Trial

“…Moreover, ongoing efforts on developing artificial intelligence models are using data collected from consumer-grade wearables in order to detect and to predict cardiovascular-related diseases [ 34 ]. A further meta-analysis focusing on the early detection of sepsis concluded that even mortality is reduced (risk ratio 0.56) by automated alerts when comparing artificial intelligence–based continuous vital sign monitoring systems to standard care [ 4 ]. However, wearables provide the possibility of early diagnosis and therefore of initiating timely therapies, but obviously do not alone constitute a therapeutic tool [ 35 ].…”

“…Particularly, patients undergoing surgical procedures are a vulnerable patient cohort requiring close monitoring. Recently, 2 systematic reviews demonstrated that, based on continuous measuring of vital parameters in hospitalized patients, the length of stay in the hospital [ 3 ] and, in combination with automated alerting systems, even mortality [ 4 ] could be reduced. Such reports raise the evident question to which degree fitness trackers could be used in hospitalized patients for continuous monitoring of vital signs.…”

Effects of Albumin Supplements on In-Hospital Mortality in Patients with Sepsis or Septic Shock: A Systemic Review and Meta-Analysis

“…In the future, more randomized controlled studies (RCTs) with long-termfollow-ups are needed to further explore the role of albumin supplements in these critically ill patients. Meanwhile, different evidence weights should be paid special attention to when both RCT and non-RCT studies (NRS) were included for analysis [ 35 ]. Third, since the concentrations of albumin used in different studies are varied, it inevitably causes a certain bias in the results.…”

Artificial intelligence clinical trials and critical appraisal: a necessity

“…These trials should compare novel interventions to the existing standard of care to evaluate comparative-effectiveness. 13 These trials should be as rigorous, if not more so, than for trials evaluating the effect of new pharmacological therapeutics or other medical devices. Guidelines have also been published to assist with this critical appraisal process.…”