Background: Patients undergoing major surgery are at risk of complications, so‐called serious adverse events (SAE). Continuous monitoring may detect deteriorating patients by recording abnormal vital signs. We aimed to assess the association between abnormal vital signs inspired by Early Warning Score thresholds and subsequent SAEs in patients undergoing major abdominal surgery.Methods: Prospective observational cohort study continuously monitoring heart rate, respiratory rate, peripheral oxygen saturation, and blood pressure for up to 96 h in 500 postoperative patients admitted to the general ward. Exposure variables were vital sign abnormalities, primary outcome was any serious adverse event occurring within 30 postoperative days. The primary analysis investigated the association between exposure variables per 24 h and subsequent serious adverse events.Results: Serious adverse events occurred in 37% of patients, with 38% occurring during monitoring. Among patients with SAE during monitoring, the median duration of vital sign abnormalities was 272 min (IQR 110–447), compared to 259 min (IQR 153–394) in patients with SAE after monitoring and 261 min (IQR 132–468) in the patients without any SAE (p = .62 for all three group comparisons). Episodes of heart rate ≥110 bpm occurred in 16%, 7.1%, and 3.9% of patients in the time before SAE during monitoring, after monitoring, and without SAE, respectively (p < .002). Patients with SAE after monitoring experienced more episodes of hypotension ≤90 mm Hg/24 h (p = .001).Conclusion: Overall duration of vital sign abnormalities at current thresholds were not significantly associated with subsequent serious adverse events, but more patients with tachycardia and hypotension had subsequent serious adverse events.Trial registration: Clinicaltrials.gov, identifier NCT03491137.

Continuous monitoring of high-risk patients and early prediction of severe outcomes is crucial to prevent avoidable deaths. Current clinical monitoring is primarily based on intermittent observation of vital signs and the early warning scores (EWS). The drawback is lack of time series dynamics and correlations among vital signs. This study presents an approach to real-time outcome prediction based on machine learning from continuous recording of vital signs. Systolic blood pressure, diastolic blood pressure, heart rate, pulse rate, respiration rate and peripheral blood oxygen saturation were continuously acquired by wearable devices from 292 post-operative high-risk patients. The outcomes from serious complications were evaluated based on review of patients' medical record. The descriptive statistics of vital signs and patient demographic information were used as features. Four machine learning models K-Nearest-Neighbors (KNN), Decision Trees (DT), Random Forest (RF), and Boosted Ensemble (BE) were trained and tested. In static evaluation, all four models had comparable prediction performance to that of the state of the art. In dynamic evaluation, the models trained from the static evaluation were tested with continuous data. RF and BE obtained the lower false positive rate (FPR) of 0.073 and 0.055 on no-outcome patients respectively. The four models KNN, DT, RF and BE had area under receiver operating characteristic curve (AUROC) of 0.62, 0.64, 0.65 and 0.64 respectively on outcome patients. RF was found to be optimal model with lower FPR on no-outcome patients and a higher AUROC on outcome patients. These findings are encouraging and indicate that additional investigations must focus on validating performance in a clinical setting before deployment of the real-time outcome prediction.

During 50 years of extracorporeal life support (ECLS), this highly invasive technology has left a considerable imprint on modern medicine, and it still confronts researchers, clinicians and policymakers with multifarious ethical challenges. After half a century of academic discussion about the ethics of ECLS, it seems appropriate to review the state of the argument and the trends in it. Through a comprehensive literature search on PubMed, we identified three ethical discourses: (1) trials and evidence accompanying the use of ECLS, (2) ECLS allocation, decision-making and limiting care, and (3) death on ECLS and ECLS in organ donation. All included articles were carefully reviewed, arguments extracted and grouped into the three discourses. This article provides a narrative synthesis of these arguments, evaluates the opportunities for mediation and substantiates the necessity of a shared decision-making approach at the limits of medical care.

BACKGROUND: Complications occur in a third of patients after major noncardiac surgery and are often preceded by vital sign deviations undetected by current vital sign monitoring practice, despite major advances in surgical and perioperative care. Continuous wireless vital sign monitoring with real-time alerts may allow for a reduction of vital sign abnormalities and complications. METHODS: Adult patients undergoing major noncardiac surgery were included and randomized to either standard of care (manual intermittent vital sign monitoring) vs standard of care plus continuous wireless vital sign monitoring with real-time vital sign alerts to staff smartphones at the general postoperative ward. The primary outcome was cumulative duration of severe vital sign deviations, including desaturation, tachy- and bradycardia, tachy- and bradypnea, hypo- and hypertension. Secondary outcomes included adverse events within 30 days. Patients and outcome assessors were blinded to the randomization. RESULTS: Four hundred patients were randomized, with 200 in the intervention and 200 in the control group, respectively. Median [interquartile range (IQR)] duration of severely deviating vital signs was 60 [25–136] vs 76 [28–192] min/d in the intervention versus control group, respectively (P = .19). Duration of Spo ₂ <88% had a mean reduction of 47 minutes per day (95% confidence interval [CI], 18–80, P = .02). Adverse events occurred in 42.5% vs 31.5% of patients within 30 days (P = .02), and serious adverse events in 34.5% vs 29.5% (P = .39). CONCLUSIONS: Continuous vital sign monitoring with real-time staff alerts did not significantly reduce cumulative severe vital sign deviations in this setup. Significant reductions in desaturations and adverse events were found, giving evidence to future studies in the use of continuous vital sign monitoring to improve patient outcomes.

Continuous vital sign monitoring at the general hospital ward has major potential advantages over intermittent monitoring but generates many alerts with risk of alert fatigue. We hypothesized that the number of alerts would be decreased using different filters. This study was an exploratory analysis of the alert reducing effect from adding two different filters to continuously collected vital sign data (peripheral oxygen saturation, blood pressure, heart rate and respiratory rate) in patients admitted after major surgery or severe medical disease. Filtered data were compared to data without artifact removal. Filter one consisted of artifact removal, filter two consisted of artifact removal plus duration criteria adjusted for severity of vital sign deviation. Alert thresholds were based on National Early Warning Score (NEWS) threshold. A population of 716 patients admitted for severe medical disease or major surgery with continous wireless vital sign monitoring at the generel ward with a mean monitoring time of 75.8 hours, were included for the analysis. Without artifact removal we found a median of 137 [IQR: 87-188] alerts per patient/day, artifact removal resulted in a median of 101 [IQR: 56-160] alerts per patient/day and with artifact removal combined with a duration-severity criterion we found a median of 19 [IQR: 9-34] alerts per patient/day. Reduction of alerts was 86.4% (p < 0.001) for values without artifact removal (137 alerts) vs. the duration criteria and a reduction (19 alerts) of 81.5% (p < 0.001) for the criteria with artifact removal (101 alerts) vs. the duration criteria (19 alerts). We conclude that a combination of artifact removal and duration-severity criteria approach substantially reduces alerts generated by continuous vital sign monitoring.