ReviewCritical care clinics2015
Using what you get: dynamic physiologic signatures of critical illness.
Review in Critical care clinics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 25 citations in OpenAlex.
- Building the future of ICU care: Is our digital foundation strong enough? A multicentre survey of Australian and New Zealand intensive care units.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2025Article
- Pupillary dynamics predict long-term outcome in a cohort of acute traumatic brain injury coma patients.Annals of clinical and translational neurology · 2023Article
- Satellite-Linked Remote Physiologic Monitoring During Simulated Rural Ground Ambulance and Rotor Wing Transports.Mayo Clinic proceedings. Digital health · 2023Article
- Novel approaches to capturing and using continuous cardiorespiratory physiological data in hospitalized children.Pediatric research · 2023Review
- Intelligent Clinical Decision Support.Sensors (Basel, Switzerland) · 2022Article
- Timing errors and temporal uncertainty in clinical databases-A narrative review.Frontiers in digital health · 2022Review
- Signatures of illness in children requiring unplanned intubation in the pediatric intensive care unit: A retrospective cohort machine-learning study.Frontiers in pediatrics · 2022Article
- Principles for Real-World Implementation of Bedside Predictive Analytics Monitoring.Applied clinical informatics · 2021Article
- Coronavirus Disease 2019 Calls for Predictive Analytics Monitoring-A New Kind of Illness Scoring System.Critical care explorations · 2020Article
- Wearable Sensors Incorporating Compensatory Reserve Measurement for Advancing Physiological Monitoring in Critically Injured Trauma Patients.Sensors (Basel, Switzerland) · 2020Review
- Dynamic properties of glucose complexity during the course of critical illness: a pilot study.Journal of clinical monitoring and computing · 2020Observational
- Organ System Network Disruption Is Associated With Poor Prognosis in Patients With Chronic Liver Failure.Frontiers in physiology · 2020Article
- Organ system network analysis and biological stability in critically ill patients.Critical care (London, England) · 2019Article
- Systems Medicine-Complexity Within, Simplicity Without.Journal of healthcare informatics research · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The development and resolution of cardiopulmonary instability take time to become clinically apparent, and the treatments provided take time to have an impact. The characterization of dynamic changes in hemodynamic and metabolic variables is implicit in physiologic signatures. When primary variables are collected with high enough frequency to derive new variables, this data hierarchy can be used to develop physiologic signatures. The creation of physiologic signatures requires no new information; additional knowledge is extracted from data that already exist. It is possible to create physiologic signatures for each stage in the process of clinical decompensation and recovery to improve outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.