Evidence map›Paper›PMID 33841695›Full record

ArticleAmerican journal of translational research2021

The effect of conservative therapy combined with rehabilitation nursing on elderly compression fracture patients.

Xiaoqin Liu, Ying Cai

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Observational
  2. Article
  3. 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

2 authors at 1 institution in 1 country.

Xiaoqin LiuDepartment of Nursing, Affiliated Hospital of Gansu University of Traditional Chinese Medicine Lanzhou 730020, Gansu Province, China.
Ying CaiDepartment of Rehabilitation Orthopedics, Affiliated Hospital of Gansu University of Traditional Chinese Medicine Lanzhou 730020, Gansu Province, China.
Gansu University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the effect of rehabilitation nursing combined with conservative therapy on patients undergoing compression fracture surgery.

methods86 patients with compression fractures admitted to our hospital for rehabilitation from November 2018 to November 2019 were recruited as the study cohort. The patients were provided with conservative traditional Chinese medicine treatment along with rehabilitation methods such as rehabilitation nursing, lumbar pillows, and the prevention and cure of complications. The post-treatment effects and related influencing factors were observed.

resultsA single-factor analysis showed the significant effect of the rehabilitation measures combined with the conservative treatment. Specifically, 80.23% of the patients positively responded to management with lumbar pillows, and the response rates of the other methods, including rehabilitation nursing, conservative TCM treatment, the prevention of complications, and the go-to-ground activity were 68.60%, 52.33%, 94.19%, and 73.26%, respectively. The response rates of the patients who did not undergo the combined treatment were 19.77%, 31.40%, 46.67%, 5.81%, and 26.74%, respectively. The differences were statistically significant (

conclusionRehabilitation nursing combined with conservative treatment can shorten the healing period and improve functional recovery in elderly compression fracture patients.

Indexed as

compression fracturesConservative therapyrehabilitation nursing

Identifiers

PMID33841695
PMCPMC8014345
OpenAlexW3155243634

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.