Analysis of the Status Quo and Influencing Factors of Revisiting Patients After Pituitary Tumor Resection: Based on a Chinese Patient Population

医学 优势比 逻辑回归 倾向得分匹配 多元分析 可能性 单变量分析 内科学 人口 垂体瘤 病历 单变量 多元统计 住所 人口学 环境卫生 统计 数学 社会学
作者
Wei Wang,Xiaoxu Han
出处
期刊:Journal of Craniofacial Surgery [Lippincott Williams & Wilkins]
标识
DOI:10.1097/scs.0000000000010635
摘要

Objective: To investigate the status of patients’ post-pituitary tumor resection and analyze influencing factors, providing evidence for improved long-term management. Methods: The authors screened 1209 patients who underwent pituitary tumor resection at Zhejiang University’s Second Affiliated Hospital from August 2020 to July 2022 using electronic medical records. Patients were classified into return visits (≥2 reviews/y or within 6 mo) and missing visit groups. Demographic and disease-related data were extracted from inpatient records, whereas return visits and prognosis data were collected from outpatient records and phone inquiries. Propensity score matching (1:1) was used to balance the groups, followed by univariate and multivariate logistic regression analyses to identify influencing factors. Results: Of the 1209 patients, 113 were unreachable. The study included 1095 patients, with 553 (50.5%) in the missing visit group and 542 (49.5%) in the return visit group. The authors matched 421 pairs, achieving balanced baseline data. Univariate analysis revealed significant differences in residence, unplanned readmission history, and current outcomes ( P < 0.05). Multivariate analysis identified unplanned readmission history (odds ratio = 0.495, 95% CI: 0.307–0.799) as a protective factor. City residents had higher return visit rates than those from other provinces (odds ratio = 0.269, 95% CI: 0.610–1.579). Conclusion: Postdischarge return rates for pituitary tumor resection patients are low and influenced by various factors. Improving return visit policies and systems is essential for facilitating outpatient follow-ups.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
FAN发布了新的文献求助10
刚刚
刚刚
刚刚
1秒前
冷静雨筠完成签到,获得积分10
2秒前
爱撒娇的思枫完成签到,获得积分10
2秒前
ky完成签到,获得积分10
3秒前
崖涯发布了新的文献求助10
4秒前
Two-Capitals发布了新的文献求助10
4秒前
专注的思菱完成签到,获得积分10
6秒前
科研通AI6.4应助stx采纳,获得10
6秒前
6秒前
8秒前
8秒前
李健应助cx330采纳,获得10
9秒前
stx完成签到,获得积分10
9秒前
赘婿应助科研小洁儿采纳,获得10
10秒前
曾真真幸运完成签到 ,获得积分10
11秒前
dian完成签到 ,获得积分10
11秒前
11秒前
深情安青应助王祖贤采纳,获得10
13秒前
13秒前
万能图书馆应助FAN采纳,获得10
13秒前
wanci应助霸气的老头采纳,获得10
13秒前
14秒前
猫猫虫完成签到,获得积分10
15秒前
醉玉颓山完成签到,获得积分10
15秒前
lyx发布了新的文献求助10
15秒前
yyl完成签到,获得积分10
18秒前
吃肯德基完成签到,获得积分10
19秒前
20秒前
20秒前
20秒前
ling发布了新的文献求助10
20秒前
21秒前
wmbgmt完成签到,获得积分10
22秒前
23秒前
科研通AI6.2应助2020采纳,获得10
24秒前
ramia完成签到 ,获得积分10
24秒前
请各位大佬帮帮小白完成签到,获得积分10
25秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
The Effective Clinical Neurologist 3ed 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7714605
求助须知:如何正确求助?哪些是违规求助? 9269877
关于积分的说明 20079143
捐赠科研通 7291026
什么是DOI,文献DOI怎么找? 3298245
关于科研通互助平台的介绍 2452447
邀请新用户注册赠送积分活动 2305594