RESUMEN
BACKGROUND: Intraoperative hypotension is common during noncardiac surgery and is associated with postoperative myocardial infarction, acute kidney injury, stroke, and severe infection. The Hypotension Prediction Index software is an algorithm based on arterial waveform analysis that alerts clinicians of the patient's likelihood of experiencing a future hypotensive event, defined as mean arterial pressure < 65 mmHg for at least 1 min. METHODS: Two analyses included (1) a prospective, single-arm trial, with continuous blood pressure measurements from study monitors, compared to a historical comparison cohort. (2) A post hoc analysis of a subset of trial participants versus a propensity score-weighted contemporaneous comparison group, using external data from the Multicenter Perioperative Outcomes Group (MPOG). The trial included 485 subjects in 11 sites; 406 were in the final effectiveness analysis. The post hoc analysis included 457 trial participants and 15,796 comparison patients. Patients were eligible if aged 18 years or older, American Society of Anesthesiologists (ASA) physical status 3 or 4, and scheduled for moderate- to high-risk noncardiac surgery expected to last at least 3 h. MEASUREMENTS: minutes of mean arterial pressure (MAP) below 65 mmHg and area under MAP < 65 mmHg. RESULTS: Analysis 1: Trial subjects (n = 406) experienced a mean of 9 ± 13 min of MAP below 65 mmHg, compared with the MPOG historical control mean of 25 ± 41 min, a 65% reduction (p < 0.001). Subjects with at least one episode of hypotension (n = 293) had a mean of 12 ± 14 min of MAP below 65 mmHg compared with the MPOG historical control mean of 28 ± 43 min, a 58% reduction (p< 0.001). Analysis 2: In the post hoc inverse probability treatment weighting model, patients in the trial demonstrated a 35% reduction in minutes of hypotension compared to a contemporaneous comparison group [exponentiated coefficient: - 0.35 (95%CI - 0.43, - 0.27); p < 0.001]. CONCLUSIONS: The use of prediction software for blood pressure management was associated with a clinically meaningful reduction in the duration of intraoperative hypotension. Further studies must investigate whether predictive algorithms to prevent hypotension can reduce adverse outcomes. TRIAL REGISTRATION: Clinical trial number: NCT03805217. Registry URL: https://clinicaltrials.gov/ct2/show/NCT03805217 . Principal investigator: Xiaodong Bao, MD, PhD. Date of registration: January 15, 2019.
RESUMEN
PURPOSE: To form a multifaceted picture of family caregiver economic costs in advanced cancer. METHODS: A multi-site cohort study collected prospective longitudinal data from caregivers of patients with advanced solid tumor cancers. Caregiver survey and out-of-pocket (OOP) receipt data were collected biweekly in-person for up to 24 weeks. Economic cost measures attributed to caregiving were as follows: amount of OOP costs, debt accrual, perceived economic situation, and working for pay. Descriptive analysis illustrates economic outcomes over time. Generalized linear mixed effects models asses the association of objective burden and economic outcomes, controlling for subjective burden and other factors. Objective burden is number of activities and instrumental activities of daily living (ADL/IADL) tasks, all caregiving tasks, and amount of time spent caregiving over 24 h. RESULTS: One hundred ninety-eight caregivers, 41% identifying as Black, were followed for a mean period of 16 weeks. Median 2-week out-of-pocket costs were $111. One-third of caregivers incurred debt to care for the patient and 24% reported being in an adverse economic situation. Whereas 49.5% reported working at study visit 1, 28.6% of caregivers at the last study visit reported working. In adjusted analysis, a higher number of caregiving tasks overall and ADL/IADL tasks specifically were associated with lower out-of-pocket expenses, a lower likelihood of working, and a higher likelihood of incurring debt and reporting an adverse economic situation. CONCLUSIONS: Most caregivers of cancer patients with advanced stage disease experienced direct and indirect economic costs. IMPLICATIONS FOR CANCER SURVIVORS: Results support the need to find solutions to lessen economic costs for caregivers of persons with advanced cancer.
RESUMEN
Medical errors from communication failures are enormous during the perioperative period of cardiac surgical patients. As caregivers change shifts or surgical patients change location within the hospital, key information is lost or misconstrued. After a baseline cognitive study of information need and caregiver workflow, we implemented an advanced clinical decision support tool of intelligent agents, medical logic modules, and text generators called the "Inference Engine" to summarize individual patient's raw medical data elements into procedural milestones, illness severity, and care therapies. The system generates two displays: 1) the continuum of care, multimedia abstract generation of intensive care data (MAGIC)-an expert system that would automatically generate a physician briefing of a cardiac patient's operative course in a multimodal format; and 2) the isolated point in time, "Inference Engine"-a system that provides a real-time, high-level, summarized depiction of a patient's clinical status. In our studies, system accuracy and efficacy was judged against clinician performance in the workplace. To test the automated physician briefing, "MAGIC," the patient's intraoperative course, was reviewed in the intensive care unit before patient arrival. It was then judged against the actual physician briefing and that given in a cohort of patients where the system was not used. To test the real-time representation of the patient's clinical status, system inferences were judged against clinician decisions. Changes in workflow and situational awareness were assessed by questionnaires and process evaluation. MAGIC provides 200% more information, twice the accuracy, and enhances situational awareness. This study demonstrates that the automation of clinical processes through AI methodologies yields positive results.
