Evidence map›Paper›PMID 32242824›Full record

ArticleJMIR medical informatics2020

Identifying the Characteristics of Patients With Cervical Degenerative Disease for Surgical Treatment From 17-Year Real-World Data: Retrospective Study.

Si Zheng, Yun Xia Wu, Jia Yang Wang, Yan Li, Zhong Jun Liu, Xiao Guang Liu, Geng Ting Dang, Yu Sun, Jiao Li

Abstract read
In one paragraph

Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Article
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  6. Overcoming cancer therapeutic bottleneck by drug repurposing.Signal transduction and targeted therapy · 2020
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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

9 authors.

Si Zheng *Institute of Medical Information & Library, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-9834-9774
Yun Xia Wu *Orthopaedic Department, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-9166-187X
Jia Yang WangInstitute of Medical Information & Library, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0003-1734-2835
Yan LiOrthopaedic Department, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-2380-9975
Zhong Jun LiuOrthopaedic Department, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-4038-3101
Xiao Guang LiuOrthopaedic Department, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0003-3238-1154
Geng Ting DangOrthopaedic Department, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0003-3711-0206
Yu SunOrthopaedic Department, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0003-1034-3798
Jiao LiInstitute of Medical Information & Library, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0001-6391-8343

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReal-world data (RWD) play important roles in evaluating treatment effectiveness in clinical research. In recent decades, with the development of more accurate diagnoses and better treatment options, inpatient surgery for cervical degenerative disease (CDD) has become increasingly more common, yet little is known about the variations in patient demographic characteristics associated with surgical treatment.

objectiveThis study aimed to identify the characteristics of surgical patients with CDD using RWD collected from electronic medical records.

methodsThis study included 20,288 inpatient surgeries registered from January 1, 2000, to December 31, 2016, among patients aged 18 years or older, and demographic data (eg, age, sex, admission time, surgery type, treatment, discharge diagnosis, and discharge time) were collected at baseline. Regression modeling and time series analysis were conducted to analyze the trend in each variable (total number of inpatient surgeries, mean age at surgery, sex, and average length of stay). A P value <.01 was considered statistically significant. The RWD in this study were collected from the Orthopedic Department at Peking University Third Hospital, and the study was approved by the institutional review board.

resultsOver the last 17 years, the number of inpatient surgeries increased annually by an average of 11.13%, with some fluctuations. In total, 76.4% (15,496/20,288) of the surgeries were performed in patients with CDD aged 41 to 65 years, and there was no significant change in the mean age at surgery. More male patients were observed, and the proportions of male and female patients who underwent surgery were 64.7% (13,126/20,288) and 35.3% (7162/20,288), respectively. However, interestingly, the proportion of surgeries performed among female patients showed an increasing trend (P<.001), leading to a narrowing sex gap. The average length of stay for surgical treatment decreased from 21 days to 6 days and showed a steady decline from 2012 onward.

conclusionsThe RWD showed its capability in supporting clinical research. The mean age at surgery for CDD was consistent in the real-world population, the proportion of female patients increased, and the average length of stay decreased over time. These results may be valuable to guide resource allocation for the early prevention and diagnosis, as well as surgical treatment of CDD.

Indexed as

average length of staycervical degenerative diseaseinpatient surgerymean age at surgeryreal-world datasex

Identifiers

PMID32242824
PMCPMC7165306

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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.