Evidence map›Paper›PMID 23884510›Full record

ReviewNeurocritical care2014

Informatics for neurocritical care: challenges and opportunities.

Ahilan Sivaganesan, Geoffrey T Manley, Michael C Huang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Neurocritical care, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Guideline
  3. Article
  4. Article
  5. Trending autoregulatory indices during treatment for traumatic brain injury.Journal of clinical monitoring and computing · 2016
    Article
  6. Review
  7. Cost-Effective Machine Learning Based Clinical Pre-Test Probability Strategy for DVT Diagnosis in Neurological Intensive Care Unit.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ahilan SivaganesanDepartment of Neurological Surgery, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA.
Geoffrey T Manley
Michael C Huang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurocritical care relies on the continuous, real-time measurement of numerous physiologic parameters. While our capability to obtain such measurements from patients has grown markedly with multimodal monitoring in many neurologic or neurosurgical intensive care units (ICUs), our ability to transform the raw data into actionable information is limited. One reason is that the proprietary nature of medical devices and software often prevents neuro-ICUs from capturing and centrally storing high-density data. Also, ICU alarm systems are often unreliable because the data that are captured are riddled with artifacts. Informatics is the process of acquiring, processing, and interpreting these complex arrays of data. The development of next-generation informatics tools allows for detection of complex physiologic events and brings about the possibility of decision support tools to improve neurocritical care. Although many different approaches to informatics are discussed and considered, here we focus on the Bayesian probabilistic paradigm. It quantifies the uncertainty inherent in neurocritical care instead of ignoring it, and formalizes the natural clinical thought process of updating prior beliefs using incoming patient data. We review this and other opportunities, as well as challenges, for the development and refinement of informatics tools in neurocritical care.

Indexed as

Decision Support Systems, ClinicalHumansIntensive Care UnitsMedical InformaticsMonitoring, PhysiologicNeurologyNeurosurgery

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.