Evidence map›Paper›PMID 30200162›Full record

Trial reportMedicine2018

Surveillance or no surveillance for deep venous thrombosis and outcomes of critically ill patients: A study protocol and statistical analysis plan.

Yaseen M Arabi, Karen E A Burns, Fahad Al-Hameed, Sami Alsolamy, Mohammed Almaani, Yasser Mandourah, Ghaleb A Almekhlafi, Ali Al Bshabshe, Mohammed Alshahrani, Imran Khalid and 9 more

Abstract readComparative StudyMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. 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

19 authors.

Yaseen M ArabiIntensive Care Department, College of Medicine-Riyadh, King Saud Bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia Interdepartmental Division of Critical Care Medicine, St Michael's Hospital, Li Ka Shing Knowledge Institute, Toronto, Canada Department of Intensive Care, College of Medicine-Jeddah, King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Jeddah Intensive Care and Emergency Medicine Departments, College of Medicine-Riyadh, King Saud Bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center Department of Pulmonary & Critical Care Medicine King Fahad Medical City, King Saud Bin Abdulaziz University for Health Sciences Department of Intensive Care Services, Prince Sultan Military Medical City, Riyadh Department of Critical Care Medicinem, King Khalid University, Asir Central Hospital, Abha Department of Emergency and Critical Care, Imam Abdulrahman Bin Faisal University, Dammam Critical Care Section, Department of Medicine, King Faisal Specialist Hospital & Research Center, Jeddah Critical Care Medicine Department, King Faisal Specialist Hospital and Research Centre, Riyadh, Kingdom of Saudi Arabia Department of Anesthesiology and Critical Care, King George's Medical University, Lucknow, India Department of Pulmonary & Critical Care Medicine, King Fahad Medical City, Riyadh Intensive Care and Pulmonary Medicine, King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Al Ahsa Department Biostatistics and Bioinformatics Research Office, King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia.
Karen E A Burns
Fahad Al-Hameed
Sami Alsolamy
Mohammed Almaani
Yasser Mandourah
Ghaleb A Almekhlafi
Ali Al Bshabshe
Mohammed Alshahrani
Imran Khalid
Hassan Hawa
Zia Arshad
Hani Lababidi
Abdulsalam Al Aithan
Jesna Jose
Sheryl Ann I Abdukahil
Lara Y Afesh
Abdulaziz Al-Dawood
and the PREVENT trial Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSurveillance ultrasounds in critically ill patients detect many deep venous thrombi (DVTs) that would otherwise go unnoticed. However, the impact of surveillance for DVT on mortality among critically ill patients remains unclear.

designWe are conducting a multicenter, multinational randomized controlled trial that examines the effectiveness of adjunct intermittent pneumatic compression use with pharmacologic thromboprophylaxis compared to pharmacologic thromboprophylaxis alone on the incidence of proximal lower extremity DVT in critically ill patients (the PREVENT trial). Enrolled patients undergo twice weekly surveillance ultrasounds of the lower extremities as part of the study procedures. We plan to compare enrolled patients who have surveillance ultrasounds to patients who meet the eligibility criteria but are not enrolled (eligible non-enrolled patients) and only who will have ultrasounds performed at the clinical team's discretion. We hypothesize that twice-weekly ultrasound surveillance for DVT in critically ill patients who are receiving thromboprophylaxis will have more DVTs detected, and consequently, fewer pulmonary emboli and lower all-cause 90-day mortality. DISCUSSION: We developed a detailed a priori plan to guide the analysis of the proposed study and enhance the validity of its results.

Indexed as

Critical IllnessMonitoring, PhysiologicUltrasonographyData Interpretation, StatisticalFibrinolytic AgentsHumansIntermittent Pneumatic Compression DevicesInternationalityLower ExtremityPatient SelectionTreatment OutcomeVenous ThrombosisFibrinolytic Agents

Identifiers

PMID30200162
PMCPMC6133421

What OpenQuestion holds

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LicenceCC BY
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.