Evidence map›Paper›PMID 36684287›Full record

ArticleFrontiers in surgery2022

How to predict the culprit segment in percutaneous transforaminal endoscopic surgery under local anesthesia for surgical treatment of lumbar degenerative diseases? Radiologic images or clinical symptoms.

Tianyao Zhou, Tianle Ma, Yutong Gu, Liang Zhang, Wu Che, Yichao Wang

Abstract read
In one paragraph

Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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

6 authors.

Tianyao ZhouDepartment of Orthopedic Surgery, Zhongshan Hospital Fudan University, Shanghai, China.
Tianle MaDepartment of Orthopedic Surgery, Zhongshan Hospital Fudan University, Shanghai, China.
Yutong GuDepartment of Orthopedic Surgery, Zhongshan Hospital Fudan University, Shanghai, China.
Liang ZhangDepartment of Orthopedic Surgery, Zhongshan Hospital Fudan University, Shanghai, China.
Wu CheDepartment of Orthopedic Surgery, Zhongshan Hospital Fudan University, Shanghai, China.
Yichao WangDepartment of Orthopedic Surgery, Zhongshan Hospital Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Percutaneous transforaminal endoscopic surgery (PTES) is a novel, minimally invasive technique used to treat lumbar degenerative diseases (LDDs). PTES under local anesthesia was performed to treat the culprit segment of LDDs predicted by radiologic images or clinical symptoms, and the efficacy, security, and feasibility were evaluated. Methods: Eighty-seven cases of LDDs with nerve root symptoms, which were not consistent with lumbar degenerative levels and degrees on MRI and CT, were treated with PTES under local anesthesia in a day surgery ward from January 2015 to December 2019. Forty-two patients, whose culprit segments were predicted by radiologic images, were included in group A. The other 45 patients, whose culprit segments were predicted by clinical symptoms, were included in group B. Leg pain VAS and ODI scores before and after PTES were recorded. The outcome was defined according to the MacNab grade at the 2-year follow-up. Postoperative complications were recorded. Results: In group A, 2 patients underwent PTES for one segment, 37 patients underwent PTES for two segments, and 3 patients underwent PTES for three segments. One of the one-segment PTES patients had no relief from symptoms and underwent another PTES for other culprit segments 3 months after surgery. In group B, 44 of 45 patients were treated using PTES for one segment and 1 patient was treated for two segments. Group B showed significantly less operative duration, less blood loss, and less fluoroscopy frequency than group A ( Conclusion: It is much more accurate to predict the culprit segment according to clinical symptoms than radiologic images in PTES under local anesthesia for surgical treatment of LDDs.

Indexed as

clinical symptomsculprit segmentlumbar degenerative diseaseminimally invasive surgeryradiologic imagestransforaminal endoscopic discectomy

Identifiers

PMID36684287
PMCPMC9852059

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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.