Evidence map›Paper›PMID 24498588›Full record

ArticleJournal of neurological surgery. Part B, Skull base2014

Magnetic resonance imaging criteria to predict complete excision of parasellar pituitary macroadenoma on postoperative imaging.

S E J Connor, F Wilson, K Hogarth

Abstract read
In one paragraph

Article in Journal of neurological surgery. Part B, Skull base, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Imaging of Resected Nonfunctioning Pituitary Adenomas: The Cost of Surveillance.Journal of neurological surgery. Part B, Skull base · 2015
    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.

S E J ConnorDepartment of Neuroradiology, King's College Hospital, London, United Kingdom.
F WilsonDepartment of Paediatric Radiology, Starship Children's Health, Auckland, New Zealand.
K HogarthDepartment of Neuroradiology, John Radcliffe Hospital, Oxford University Hospitals NHS Trust, Headley Way, Headington, Oxford, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose To evaluate preoperative magnetic resonance imaging (MRI) criteria for their ability to predict the complete removal of parasellar pituitary macroadenoma on the 3-month postoperative MRI. Methods Dedicated pre- and postoperative pituitary MRI studies were reviewed in 49 patients who had undergone transsphenoidal surgery for macroadenomas with potential unilateral parasellar involvement. Twelve preoperative MRI findings and postoperative MRI outcomes were statistically compared. Results Depiction of the inferolateral (positive predictive value [PPV]: 0.6; negative predictive value [NPV], 0.92) and lateral (PPV: 0.65; NPV: 0.85) compartments of the cavernous sinus and the percentage of intracavernous carotid artery encasement (PPV: 0.63; NPV, 1.0 for <50% encasement) were the only criteria significantly predictive of parasellar tumor complete resection. The odds ratios indicated that depiction of the lateral venous or inferolateral venous compartments increased the likelihood of a complete resection by 6 times, whereas for every 25% reduction in intracavernous carotid artery encasement, the chance of a complete resection increased 3.4 times. Conclusion The preoperative MR imaging features that are useful in predicting the complete removal of the parasellar component of a pituitary adenoma as assessed by postoperative MRI are (1) depiction of the lateral and inferolateral compartment of the cavernous sinus and (2) decreasing encasement of the intracavernous carotid artery.

Indexed as

macroadenomamagnetic resonance imagingpituitarypostoperative

Identifiers

PMID24498588
PMCPMC3912140

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Registered trials

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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.