Evidence map›Paper›PMID 39280106›Full record

ReviewJournal of healthcare engineering2022

Meta-Analysis of the Prognostic Value of Narcotrend Monitoring of Different Depths of Anesthesia and Different Bispectral Index (BIS) Values for Cognitive Dysfunction after Tumor Surgery in Elderly Patients.

Na Chen, Jing Lu

RetractedAbstract readReviewRetracted Publication
In one paragraph

Review in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Na ChenSchool of Anesthesiology, Weifang Medical University, Weifang, China.
Jing LuDepartment of Anesthesiology, Linyi People's Hospital, Linyi, China.ORCID https://orcid.org/0000-0003-2539-6358

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To study the effect of Narcotrend monitoring on the incidence of early postoperative cognitive dysfunction (POCD) under different bispectral index (BIS) conditions and the effect of different depths of anesthesia on the incidence of POCD. Methods: We performed a literature search of PubMed, Embase, OVID (database system made by Ovid Technologies, USA), CBM (Chinese Biomedical Literature database), CNKI (China National Knowledge Infrastructure), Wanfang, and VIP databases (full-text database of Chinese sci-tech journals), etc., from the date of the establishment of the database until December 31, 2020. Our meta-analysis was focused on the collection and study of Narcotrend monitoring of different depths of anesthesia. We carefully read the abstracts and full texts of randomized controlled trials on the incidence of POCD in the early postoperative period, and their references were tracked. Data extraction and quality evaluation of the included literature were also performed, and RevMan 5.3 software was used for analysis. Results: In the end, eight articles were included, with a total of 714 patients. The meta-analysis results showed that four articles (255 patients) compared the state of deep anesthesia (BIS 30-40) with conventional anesthesia (BIS 40-60 earlier) after POCD. Also, the incidence of POCD on the first day after deep anesthesia (Narcotrend stage (NTS): negative correlation is currently the most appropriate EEG description; Nd can subdivide the original EEG into six stages and 15 levels (Nd Sg, NTS), namely, A (state of wakefulness) state, B0 B2 (sedated state), C0 C2 (light anesthetic state), D0 D2 (general anesthesia), and E0-E1) was significantly lower than that of conventional anesthesia (NTS DO-D1) (odds ratio (OR) = 0.21, 95% confidence interval (CI): 0.13-0.35,

Identifiers

PMID39280106
PMCPMC11401709

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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.