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大流行期间需要持续肾脏替代治疗的非 COVID-19 患者的重症监护系统的维持:单中心经验。

Maintenance of the critical care system during the pandemic in non-COVID-19 patients requiring continuous renal replacement therapy: a single center experience.

机构信息

Department of Internal Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea.

Divison of Nephrology, Biomedical Research Institute, Pusan National University Hospital, 305 Gudeok-ro, Seo-gu, Busan, 602-739, South Korea.

出版信息

BMC Emerg Med. 2022 Aug 1;22(1):138. doi: 10.1186/s12873-022-00693-7.

DOI:10.1186/s12873-022-00693-7
PMID:35915412
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9342846/
Abstract

BACKGROUND

During the COVID-19 pandemic, maintenance of essential healthcare systems became very challenging. We describe the triage system of our institute, and assess the quality of care provided to critically ill non-COVID-19 patients requiring continuous renal replacement therapy (CRRT) during the pandemic.

METHODS

We introduced an emergency triage pathway early in the pandemic. We retrospectively reviewed the medical records of patients who received CRRT in our hospital from January 2016 to March 2021. We excluded end-stage kidney disease patients on maintenance dialysis. Patients were stratified as medical and surgical patients. The time from hospital arrival to intensive care unit (ICU) admission, the time from hospital arrival to intervention/operation, and the in-hospital mortality rate were compared before (January 2016 to December 2019) and during (January 2021 to March 2021) the pandemic.

RESULTS

The mean number of critically ill patients who received CRRT annually in the surgical department significantly decreased during the pandemic in (2016-2019: 76.5 ± 3.1; 2020: 56; p < 0.010). Age, sex, and the severity of disease at admission did not change, whereas the proportions of medical patients with diabetes (before: 44.4%; after: 56.5; p < 0.005) and cancer (before: 19.4%; after: 32.3%; p < 0.001) increased during the pandemic. The time from hospital arrival to ICU admission and the time from hospital arrival to intervention/operation did not change. During the pandemic, 59.6% of surgical patients received interventions/operations within 6 hours of hospital arrival. In Cox's proportional hazard modeling, the hazard ratio associated with the pandemic was 1.002 (0.778-1.292) for medical patients and 1.178 (0.783-1.772) for surgical patients.

CONCLUSION

Our triage system maintained the care required by critically ill non-COVID-19 patients undergoing CRRT at our institution.

摘要

背景

在 COVID-19 大流行期间,维持基本医疗体系变得极具挑战性。我们描述了本研究所的分诊系统,并评估了在大流行期间需要连续肾脏替代治疗(CRRT)的危重病非 COVID-19 患者的护理质量。

方法

我们在大流行早期引入了紧急分诊途径。我们回顾性地审查了 2016 年 1 月至 2021 年 3 月在我院接受 CRRT 的患者的病历。我们排除了维持性透析的终末期肾病患者。患者分为内科和外科患者。比较大流行前后(2016 年 1 月至 2019 年 12 月和 2021 年 1 月至 2021 年 3 月)从医院到达 ICU 入院的时间、从医院到达干预/手术的时间以及院内死亡率。

结果

外科部门每年接受 CRRT 的危重病患者数量在大流行期间明显减少(2016-2019 年:76.5 ± 3.1;2020 年:56 人;p < 0.010)。年龄、性别和入院时疾病的严重程度没有改变,而患有糖尿病的内科患者比例(之前:44.4%;之后:56.5%;p < 0.005)和癌症(之前:19.4%;之后:32.3%;p < 0.001)增加。从医院到达 ICU 入院和从医院到达干预/手术的时间没有改变。大流行期间,59.6%的外科患者在到达医院后 6 小时内接受了干预/手术。在 Cox 比例风险模型中,与大流行相关的风险比为 1.002(0.778-1.292)内科患者和 1.178(0.783-1.772)外科患者。

结论

我们的分诊系统维持了在我们机构接受 CRRT 的危重病非 COVID-19 患者所需的护理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/8a7e3a332755/12873_2022_693_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/458c6a216288/12873_2022_693_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/86ff97f9ebdb/12873_2022_693_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/72add976309b/12873_2022_693_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/8a7e3a332755/12873_2022_693_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/458c6a216288/12873_2022_693_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/86ff97f9ebdb/12873_2022_693_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/72add976309b/12873_2022_693_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d37/9344738/8a7e3a332755/12873_2022_693_Fig4_HTML.jpg

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