Evidence map›Paper›PMID 37824333›Full record

ReviewCritical reviews in biomedical engineering2023

Review of Enhanced Handheld Surgical Drills.

David E Usevitch, Rachel S Bronheim, Miguel A Cartagena-Reyes, Carlos Ortiz-Babilonia, Adam Margalit, Amit Jain, Mehran Armand

Open access · greenAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Critical reviews in biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 39% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

7 authors at 3 institutions in 2 countries.

David E UsevitchLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD; Department of Orthopedic Surgery, Johns Hopkins University, Baltimore, MD.
Rachel S BronheimDepartment of Orthopedic Surgery, Johns Hopkins University, Baltimore, MD.
Miguel A Cartagena-ReyesDepartment of Orthopedic Surgery, Johns Hopkins University, Baltimore, MD.
Carlos Ortiz-BabiloniaDepartment of Orthopedic Surgery, Johns Hopkins University, Baltimore, MD.
Adam MargalitDepartment of Orthopedic Surgery, Johns Hopkins University, Baltimore, MD.
Amit JainDepartment of Orthopedic Surgery, Johns Hopkins University, Baltimore, MD.
Mehran ArmandLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD; Department of Orthopedic Surgery, Johns Hopkins University, Baltimore, MD.
Johns Hopkins University · USJohns Hopkins Medicine · USUniversity of Puerto Rico System · PR

Funding

Training In Orthopaedic Team ScienceT32AR067708 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI JONES, LYNNE C., SHAFIQ, BABAR · 2015 to 2024
$2.0M
NIAMS NIH HHS T32 AR067708
6 · The paper itself

Abstract

The handheld drill has been used as a conventional surgical tool for centuries. Alongside the recent successes of surgical robots, the development of new and enhanced medical drills has improved surgeon ability without requiring the high cost and consuming setup times that plague medical robot systems. This work provides an overview of enhanced handheld surgical drill research focusing on systems that include some form of image guidance and do not require additional hardware that physically supports or guides drilling. Drilling is reviewed by main contribution divided into audio-, visual-, or hardware-enhanced drills. A vision for future work to enhance handheld drilling systems is also discussed.

Indexed as

Surgical Equipment

Identifiers

PMID37824333
PMCPMC10874117
OpenAlexW4385756767

What OpenQuestion holds

Textmetadata
LicenceTDM
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.