Evidence map›Paper›PMID 16879726›Full record

ReviewCritical care (London, England)2006

Brain dysfunction in critically ill patients--the intensive care unit and beyond.

Nuala J Meyer, Jesse B Hall

Abstract readReview
In one paragraph

Review in Critical care (London, England), 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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.

  1. Trial
  2. Article
  3. Quantitative EEG signatures of delirium and coma in mechanically ventilated ICU patients.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2023
    Article
  4. Review
  5. Review
  6. Year in review 2006: Critical Care--Resource management.Critical care (London, England) · 2007
    Review
  7. 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

2 authors.

Nuala J MeyerPulmonary and Critical Care Medicine, Department of Medicine, University of Chicago, Illinois, USA.
Jesse B Hall

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Critical care physicians often find themselves prognosticating for their patients, attempting to predict patient survival as well as disability. In the case of neurologic injury, this can be especially difficult. A frequent cause of coma in the intensive care unit is resuscitation following cardiac arrest, for which mortality and severe neurologic disability remain high. Recent studies of the clinical examination, of serum markers such as neuron-specific enolase, and of somatosensory evoked potentials allow accurate and specific prediction of which comatose patients are likely to suffer a poor outcome. Using these tools, practitioners can confidently educate the family for the majority of patients who will die or remain comatose at 1 month. Delirium is a less dramatic form of neurologic injury but, when sought, is strikingly prevalent. In addition, delirium in the intensive care unit is associated with increased mortality and poorer functional recovery, prompting investigation into preventative and therapeutic strategies to counter delirium. Finally, neurologic damage may persist long after the patient's recovery from critical illness, as is the case for cognitive dysfunction detected months and years after critical illness. Psychiatric impairment including depression or post-traumatic stress disorder may also arise. Mechanisms contributing to each of these entities are reviewed.

Indexed as

Critical IllnessIntensive Care UnitsBiomarkersBrain DiseasesComaHumansRisk FactorsBiomarkers

Identifiers

PMID16879726
PMCPMC1751001

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.