Evidence map›Paper›PMID 20144379›Full record

ReviewJournal of diabetes science and technology2009

An overview of preoperative glucose evaluation, management, and perioperative impact.

Ann M Sheehy, Robert A Gabbay

Abstract readReview
In one paragraph

Review in Journal of diabetes science and technology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. [Expert consensus on the implementation of enhanced recovery after surgery in percutaneous endoscopic interlaminar lumbar decompression/discectomy (2020)].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2020
    Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
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.

Ann M SheehyDepartment of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53792, USA. asr@medicine.wisc.edu
Robert A Gabbay

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Perioperative hyperglycemia is a common phenomenon affecting patients both with and without a known prior history of diabetes. Despite an exponential rise in publications and studies of inpatient hyperglycemia over the last decade, many questions still exist as to what defines optimal care of these patients. Initial enthusiasm for tight glycemic control has waned as the unanticipated reality of hypoglycemia and mortality has been realized in some prospective studies. The recent dramatic modification of national practice guidelines to endorse more modest inpatient glycemic targets highlights the dynamic nature of current knowledge as the next decade approaches. This review discusses perioperative hyperglycemia and the categories of patients affected by it. It reviews current recommendations for ambulatory diabetes screening and its importance in preoperative patient care. Finally, it concludes with a review of current practice guidelines, as well as a discussion of future direction and goals for inpatient perioperative glycemic control.

Indexed as

Mass ScreeningBiomarkersBlood GlucoseDiabetes MellitusGlycated HemoglobinHumansHyperglycemiaHypoglycemiaHypoglycemic AgentsInpatientsInsulinPerioperative CarePractice Guidelines as TopicPredictive Value of TestsPreoperative CareRisk AssessmentBiomarkersBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanHypoglycemic AgentsInsulin

Identifiers

PMID20144379
PMCPMC2787025

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.