A Novel Risk Predictive Scoring Model for Predicting Subsequent Infection After Carbapenem-Resistant Gram-Negative Bacteria Colonization in Hematological Malignancy Patients

内科学 医学 粘膜炎 低蛋白血症 肺炎克雷伯菌 殖民地化 败血症 恶性肿瘤 抗生素 胃肠病学 多元分析 化疗 生物 微生物学 生物化学 大肠杆菌 基因
作者
Qiuling Wu,Chenjing Qian,Hua Yin,Fang Liu,Yaohui Wu,Weiming Li,Linghui Xia,Ling Ma,Mei Hong
出处
期刊:Frontiers in Oncology [Frontiers Media]
卷期号:12 被引量:7
标识
DOI:10.3389/fonc.2022.897479
摘要

This study investigated the high-risk factors associated with the increased vulnerability for subsequent clinical CR-GNB infection in carbapenem-resistant Gram-negative bacteria (CR-GNB)-colonized hematological malignancy (HM) patients and built a statistical model to predict subsequent infection.All adult HM patients with positive rectoanal swabs culture for CR-GNB between January 2018 and June 2020 were prospectively followed to assess for any subsequent CR-GNB infections and to investigate the risk factors and clinical features of subsequent infection.A total of 392 HM patients were enrolled. Of them, 46.7% developed a subsequent clinical CR-GNB infection, with 42 (10.7%) cases of confirmed infection and 141 (36%) cases of clinically diagnosed infection. Klebsiella pneumoniae was the dominant species. The overall mortality rate of patients colonized and infected with CR-GNB was 8.6% and 43.7%. A multivariate analysis showed that remission induction chemotherapy and the duration of agranulocytosis, mucositis, and hypoalbuminemia were significant predictors of subsequent infection after CR-GNB colonization. According to our novel risk-predictive scoring model, the high-risk group were >3 times more likely to develop a subsequent infection in comparison with the low-risk group.Our risk-predictive scoring model can early and accurately predict a subsequent CR-GNB infection in HM patients with CR-GNB colonization. The early administration of CR-GNB-targeted empirical therapy in the high-risk group is strongly recommended to decrease their mortality.

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
木子林希儿完成签到,获得积分10
刚刚
1秒前
Dawn完成签到,获得积分10
1秒前
曙光发布了新的文献求助10
2秒前
WZYY完成签到 ,获得积分10
2秒前
3秒前
5秒前
luchong发布了新的文献求助10
5秒前
HaoyuHu完成签到,获得积分10
5秒前
旸羽发布了新的文献求助20
6秒前
粗暴的鱼发布了新的文献求助10
6秒前
7秒前
大气的襄完成签到,获得积分10
8秒前
求求完成签到,获得积分10
8秒前
情怀应助二柱子采纳,获得10
9秒前
虚幻的灵完成签到 ,获得积分10
9秒前
9秒前
AAA完成签到 ,获得积分10
10秒前
10秒前
one完成签到 ,获得积分10
11秒前
12秒前
鸢尾绘画完成签到 ,获得积分10
13秒前
14秒前
蒋大少发布了新的文献求助10
14秒前
14秒前
俏皮诺言完成签到,获得积分10
14秒前
CYJ完成签到,获得积分10
15秒前
可靠的书桃完成签到,获得积分10
15秒前
二柱子发布了新的文献求助10
16秒前
大米发布了新的文献求助10
17秒前
smart发布了新的文献求助10
18秒前
蒋大少完成签到,获得积分10
19秒前
Lucas应助突然采纳,获得10
19秒前
19秒前
20秒前
summer完成签到,获得积分10
20秒前
甜心椰奶莓莓完成签到 ,获得积分10
20秒前
21秒前
0731完成签到,获得积分10
22秒前
22秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
CLSI M07 2024 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 7249050
求助须知:如何正确求助?哪些是违规求助? 8871833
关于积分的说明 18720141
捐赠科研通 6928334
什么是DOI,文献DOI怎么找? 3198591
关于科研通互助平台的介绍 2373978
邀请新用户注册赠送积分活动 2173264