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巴西某大学医院新冠后患者的社会人口学特征、诊断和护理。

Sociodemographic profile, diagnoses and nursing care in post-COVID-19 patients in a Brazilian university hospital.

机构信息

Universidade Federal do Rio Grande do Sul. Porto Alegre, Rio Grande do Sul, Brazil.

Universidade Federal de Santa Catarina. Florianópolis, Santa Catarina, Brazil.

出版信息

Rev Bras Enferm. 2023 Jul 31;76Suppl 1(Suppl 1):e20220730. doi: 10.1590/0034-7167-2022-0730. eCollection 2023.

DOI:10.1590/0034-7167-2022-0730
PMID:37531483
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10389647/
Abstract

OBJECTIVES

to analyze the sociodemographic profile, diagnoses and nursing care of post-COVID-19 patients admitted to a university hospital in southern Brazil.

METHODS

a retrospective cohort study. The sample consisted of 1,467 medical records, from January 2020 to January 2021.

RESULTS

from the analyzed medical records, the most prevalent profiles, respectively, included: males (52.9%); white (81.1%); with Impaired Physiological Balance Syndrome* Nursing Diagnosis (77.3%); nursing care implementing aerosol precautions (94.5%); implementing droplet precautions (93.4%); checking vital signs (91.9%); applying standard disinfectant to equipment and surfaces (89.6%).

CONCLUSIONS

the analysis of the sociodemographic profile, diagnoses and nursing care of patients in this study may contribute to implementing the Nursing Process in the coronavirus pandemic context.

摘要

目的

分析巴西南部一所大学附属医院收治的新冠后患者的社会人口学特征、诊断和护理情况。

方法

回顾性队列研究。样本包括 2020 年 1 月至 2021 年 1 月的 1467 份病历。

结果

在所分析的病历中,最常见的特征分别为:男性(52.9%);白人(81.1%);患有生理平衡障碍综合征*护理诊断(77.3%);实施气溶胶预防措施的护理(94.5%);实施飞沫预防措施的护理(93.4%);检查生命体征(91.9%);使用标准消毒剂对设备和表面进行消毒(89.6%)。

结论

分析本研究中患者的社会人口学特征、诊断和护理情况,有助于在冠状病毒大流行背景下实施护理程序。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e477/10389647/9f1b9f4cac34/0034-7167-reben-76-s1-e20220730-gf02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e477/10389647/b3f18af5aecb/0034-7167-reben-76-s1-e20220730-gf01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e477/10389647/9f1b9f4cac34/0034-7167-reben-76-s1-e20220730-gf02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e477/10389647/b3f18af5aecb/0034-7167-reben-76-s1-e20220730-gf01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e477/10389647/9f1b9f4cac34/0034-7167-reben-76-s1-e20220730-gf02.jpg

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A predictive model for fall risk in hospitalized adults: A case-control study.
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J Adv Nurs. 2019 Mar;75(3):563-572. doi: 10.1111/jan.13882. Epub 2018 Nov 19.