Retrospective evaluation of a decision support system for controlled mechanical ventilation

Abstract

Management of mechanical ventilation in intensive care patients is complicated by conflicting clinical goals. Decision support systems (DSS) may support clinicians in finding the correct balance. The objective of this study was to evaluate a computerized model-based DSS for its advice on inspired oxygen fraction, tidal volume and respiratory frequency. The DSS was retrospectively evaluated in 16 intensive care patient cases, with physiological models fitted to the retrospective data and then used to simulate patient response to changes in therapy. Sensitivity of the DSS's advice to variations in cardiac output (CO) was evaluated. Compared to the baseline ventilator settings set as part of routine clinical care, the system suggested lower tidal volumes and inspired oxygen fraction, but higher frequency, with all suggestions and the model simulated outcome comparing well with the respiratory goals of the Acute Respiratory Distress Syndrome Network from 2000. Changes in advice with CO variation of about 20% were negligible except in cases of high oxygen consumption. Results suggest that the DSS provides clinically relevant and rational advice on therapy in agreement with current 'best practice', and that the advice is robust to variation in CO.

Simulations for Mechanical Ventilation in Children: Review and Future Prospects

“…The model is fitted to patient's clinical conditions via several measurements including arterial blood sample drawn at the clinical FiO 2 ; assessment of O 2 consumption and CO 2 production; measurement of anatomical dead space from volumetric capnography; measurement of pulmonary shunt from a procedure of varying FiO 2 in steps and measuring ventilation, metabolism, and oxygenation status at each step; calculation of dynamic compliance from PIP, PEEP, and Vt. After the model is fitted to the patient, the clinical decision support system connected to the model tests several combinations of FiO 2 , respiratory rate, and tidal volume and proposes the settings with the best clinical impact. The simulations obtained were shown to be close to ARDS network recommendations in a retrospective study using data from real patients [29, 30]. …”

Computerized decision support in adult and pediatric critical care

“…CDS for mechanical ventilation in adults and children has already shown good agreement with clinician recommendations [71,76,77] . In the future, these CDS tools could provide independent control of ventilator settings based on patient specific data.…”

“…Ventilator fraction of inspired oxygen [41] Pressure support ventilation [42] Antibiotic recommendation [43,44] Blood glucose control [46][47][48] Sepsis [21] Heparin dosing after myocardial infarction [45] Research Mortality prediction [29] Prediction of fluid requirement [53] Predictive alerts for hemodynamic instability [49][50][51] Ventilator settings [76] Prediction of dialysis need [52] Insulin e-protocol [54,85] Pediatric and neonatal critical care Diagnostic ISABEL (www.isabelhealthcare.com) [59,86] SimulConsult (www.simulconsult.com) [87] MEDITEL pediatric diagnostic system [58] Outcome prediction and severity of illness [55][56][57] Alert and Reminder Drug interaction [62] Prescription errors and adverse drug events [18,61] Parenteral nutrition orders [61] NICU pulse oximeter [60] Protocol/Procedure Blood transfusions [63] Medications [61] Parenteral nutrition [64] Management Oxygen in ventilated newborns [68] Antibiotic recommendation [44,65] Blood glucose control [69] Medication information databases [88] Medication dosing calculators [61] Ventilator management in neonates [66,67] Research Virtual PICU (www.pi...…”

Multiparametric modeling of the ineffective efforts in assisted ventilation within an ICU

“…An ICU decision support system, based on fuzzy logic and expert knowledge, has been proposed [12] concerning mechanical ventilation options with respect to different disease states. In [9], computerized physiological models and utility/penalty functions were employed as separate factors of the system. The case of assisted (as opposed to controlled) ventilation is now receiving more attention, due to the evidence of benefits [13].…”