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Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

ABSTRACT: OBJECTIVE:To assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (Early Warning System 2.0). DESIGN:Prospective observational study. SETTING:Tertiary teaching hospital in Philadelphia, PA. PATIENTS:Non-ICU admissions November-December 2016. INTERVENTIONS:During a 6-week study period conducted 5 months after Early Warning System 2.0 alert implementation, nurses and providers were surveyed twice about their perceptions of the alert's helpfulness and impact on care, first within 6 hours of the alert, and again 48 hours after the alert. MEASUREMENTS AND MAIN RESULTS:For the 362 alerts triggered, 180 nurses (50% response rate) and 107 providers (30% response rate) completed the first survey. Of these, 43 nurses (24% response rate) and 44 providers (41% response rate) completed the second survey. Few (24% nurses, 13% providers) identified new clinical findings after responding to the alert. Perceptions of the presence of sepsis at the time of alert were discrepant between nurses (13%) and providers (40%). The majority of clinicians reported no change in perception of the patient's risk for sepsis (55% nurses, 62% providers). A third of nurses (30%) but few providers (9%) reported the alert changed management. Almost half of nurses (42%) but less than a fifth of providers (16%) found the alert helpful at 6 hours. CONCLUSIONS:In general, clinical perceptions of Early Warning System 2.0 were poor. Nurses and providers differed in their perceptions of sepsis and alert benefits. These findings highlight the challenges of achieving acceptance of predictive and machine learning-based sepsis alerts.

SUBMITTER: Ginestra JC

PROVIDER: S-EPMC6791738 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

Ginestra Jennifer C JC Giannini Heather M HM Schweickert William D WD Meadows Laurie L Lynch Michael J MJ Pavan Kimberly K Chivers Corey J CJ Draugelis Michael M Donnelly Patrick J PJ Fuchs Barry D BD Umscheid Craig A CA

Critical care medicine 20191101 11

<h4>Objective</h4>To assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (Early Warning System 2.0).<h4>Design</h4>Prospective observational study.<h4>Setting</h4>Tertiary teaching hospital in Philadelphia, PA.<h4>Patients</h4>Non-ICU admissions November-December 2016.<h4>Interventions</h4>During a 6-week study period conducted 5 months after Early Warning System 2.0 alert implementation, nurses and providers were surveyed twice ...[more]

PMID: 31135500

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Project description:The role of recombinant activated protein C (aPC) during sepsis is still controversial. It showed anti-inflammatory effect and improved the microvascular perfusion in experimental models of septic shock. The present study was aimed at testing the hypothesis that recombinant aPC therapy improves the microcirculation during severe sepsis.Prospective observational study on patients admitted in a 12-beds intensive care unit of a university hospital from July 2010 to December 2011, with severe sepsis and at least two sepsis-induced organ failures occurring within 48 hours from the onset of sepsis, who received an infusion of aPC (24 mcg/kg/h for 96 hours) (aPC group). Patients with contraindications to aPC administration were also monitored (no-aPC group).At baseline (before starting aPC infusion, T0), after 24 hours (T1a), 48 hours (T1b), 72 hours (T1c) and 6 hours after the end of aPC infusion (T2), general clinical and hemodynamic parameters were collected and the sublingual microcirculation was evaluated with sidestream dark-field imaging. Total vessel density (TVD), perfused vessel density (PVD), De Backer score, microvascular flow index (MFIs), the proportion of perfused vessels (PPV) and the flow heterogeneity index (HI) were calculated for small vessels. The perfused boundary region (PBR) was measured as an index of glycocalyx damage. Variables were compared between time points and groups using non parametric or parametric statistical tests, as appropriate.In the 13 aPC patients mean arterial pressure (MAP), base excess, lactate, PaO2/FiO2 and the Sequential Organ Failure Assessment (SOFA) score significantly improved over time, while CI and ITBVI did not change. MFIs, TVD, PVD, PPV significantly increased over time and the HI decreased (p?<?0.05 in all cases), while the PBR did not change. No-aPC patients (n?=?9) did not show any change in the microcirculation over time. A positive correlation was found between MFIs and MAP. TVD, PVD and De Backer score negatively correlated with norepinephrine dose, and the SOFA score negatively correlated with MFIs, TVD and PVD.aPC significantly improves the microcirculation in patients with severe sepsis/septic shock.NCT01806428.

Project description:ObjectivesTo assess the prevalence of immunocompromised diagnoses among children with severe sepsis and septic shock, and to determine the association between immunocompromised diagnoses and clinical outcomes after adjustment for demographics and illness severity.DesignRetrospective multicenter cohort study.SettingEighty-three centers in the Virtual Pediatric Systems database.PatientsChildren with severe sepsis or septic shock admitted to a participating PICU between January 1, 2012, and December 31, 2016.InterventionsNone.Measurements and main resultsAcross 83 centers, we identified 10,768 PICU admissions with an International Classification of Diseases, 9th Revision, Clinical Modification code for severe sepsis or septic shock; 3,021 of these patients (28%) had an immunocompromised diagnosis. To evaluate variation across centers and determine factors associated with PICU mortality, we used mixed-effect logistic regression models. Among patients without hematopoietic cell transplant, congenital immunodeficiency (adjusted odds ratio, 1.90; 95% CI, 1.24-2.92), multiple prior malignancies (adjusted odds ratio, 1.86; 95% CI, 1.15-2.99), and hemophagocytic lymphohistiocytosis (adjusted odds ratio, 3.09; 95% CI, 1.91-4.98) were associated with an increased odds of PICU mortality. Among patients with prior hematopoietic cell transplant, liquid malignancy (adjusted odds ratio, 3.15; 95% CI, 2.09-4.74), congenital immunodeficiency (adjusted odds ratio, 6.94; 95% CI, 3.84-12.53), multiple prior malignancies (adjusted odds ratio, 3.54; 95% CI, 1.80-6.95), and hemophagocytic lymphohistiocytosis (adjusted odds ratio, 2.79; 95% CI, 1.36-5.71) were associated with an increased odds of PICU mortality. PICU mortality varied significantly by center, and a higher mean number of sepsis patients per month in a center was associated with lower PICU mortality (adjusted odds ratio, 0.94; 95% CI, 0.90-0.98). PICU resource utilization varied by immunocompromised diagnosis and history of hematopoietic cell transplant, and among survivors immunocompromised patients have shorter median PICU length of stay compared with patients without immunocompromised diagnoses (p < 0.001).ConclusionsImmunocompromised diagnoses are present in 28% of children with severe sepsis or septic shock. Multiple prior malignancies, hemophagocytic lymphohistiocytosis, congenital immunodeficiency, and hematopoietic cell transplant are independently associated with an increased odds of PICU mortality in children with severe sepsis or septic shock. Significant variation exists in PICU mortality among centers despite adjustment for immunocompromised diagnoses, known risk factors for sepsis-related mortality, and center-level sepsis volume.

Project description:INTRODUCTION: Altered pharmacokinetics (PK) in critically ill patients can result in insufficient serum ?-lactam concentrations when standard dosages are administered. Previous studies on ?-lactam PK have generally excluded the most severely ill patients, or were conducted during the steady-state period of treatment. The aim of our study was to determine whether the first dose of piperacillin-tazobactam, ceftazidime, cefepime, and meropenem would result in adequate serum drug concentrations in patients with severe sepsis and septic shock. METHODS: Open, prospective, multicenter study in four Belgian intensive care units. All consecutive patients with a diagnosis of severe sepsis or septic shock, in whom treatment with the study drugs was indicated, were included. Serum concentrations of the antibiotics were determined by high-pressure liquid chromatography (HPLC) before and 1, 1.5, 4.5 and 6 or 8 hours after administration. RESULTS: 80 patients were treated with piperacillin-tazobactam (n = 27), ceftazidime (n = 18), cefepime (n = 19) or meropenem (n = 16). Serum concentrations remained above 4 times the minimal inhibitory concentration (T > 4 × MIC), corresponding to the clinical breakpoint for Pseudomonas aeruginosa defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST), for 57% of the dosage interval for meropenem (target MIC = 8 ?g/mL), 45% for ceftazidime (MIC = 32 ?g/mL), 34% for cefepime (MIC = 32 ?g/mL), and 33% for piperacillin-tazobactam (MIC = 64 ?g/mL). The number of patients who attained the target PK profile was 12/16 for meropenem (75%), 5/18 for ceftazidime (28%), 3/19 (16%) for cefepime, and 12/27 (44%) for piperacillin-tazobactam. CONCLUSIONS: Serum concentrations of the antibiotic after the first dose were acceptable only for meropenem. Standard dosage regimens for piperacillin-tazobactam, ceftazidime and cefepime may, therefore, be insufficient to empirically cover less susceptible pathogens in the early phase of severe sepsis and septic shock.

Dataset Information

Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

Publications

Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

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