Description of Clinical Characteristics of VAP Patients in MIMIC Database
Background: Ventilator-associated pneumonia (VAP) is a common and serious nosocomial infection of intensive-care units (ICUs). Accurate, timely diagnosis enables early VAP patients to receive appropriate therapies and reduce the occurrence of complication. However, so far clinical datas regarding th...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2019-02-01
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| Series: | Frontiers in Pharmacology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fphar.2019.00062/full |
| _version_ | 1818200668649816064 |
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| author | Qingqing Liu Qingqing Liu Jin Yang Jin Yang Jun Zhang Jun Zhang Fanfan Zhao Fanfan Zhao Xiaojie Feng Xiaojie Feng Xue Wang Jun Lyu Jun Lyu |
| author_facet | Qingqing Liu Qingqing Liu Jin Yang Jin Yang Jun Zhang Jun Zhang Fanfan Zhao Fanfan Zhao Xiaojie Feng Xiaojie Feng Xue Wang Jun Lyu Jun Lyu |
| author_sort | Qingqing Liu |
| collection | DOAJ |
| description | Background: Ventilator-associated pneumonia (VAP) is a common and serious nosocomial infection of intensive-care units (ICUs). Accurate, timely diagnosis enables early VAP patients to receive appropriate therapies and reduce the occurrence of complication. However, so far clinical datas regarding the epidemiology and mortality of VAP are still limited. Medical Information Mart for Intensive Care (MIMIC) database is a free, open and public resource about ICU research database. MIMIC database is a free, open, public database that collects information on more than 40,000 ICU patients who are predominantly white people. Therefore, the purpose of the present study is to observe and describe the clinical characteristics of VAP patients in ICU from the MIMIC database.Method: A total of 418 patients were enrolled in the study. General information, ventilator use information, microbiology information, antibiotic use information, and some nursing-related information were extracted to describe and analyze the clinical features of VAP patients.Results: The results of the study showed that patients with one or three pathogens were the most. The main pathogens were YEAST (16.71%), STAPH AUREUS COAG+ (11.63%), Staphylococcus, COAGULASE NEGATIVE (8.68%), GRAM NEGATIVE ROD (S) (6.14%), and Pseudomonas aeruginosa (5.73%). Patients using 4 antibiotics were the most. The top five antibiotics in the largest proportion were synthetic antibacterials (24.66%), peptides (20.13%), cephalosporins (19.60%), penicillins (13.54%), and aminoglycosides (5.27%).Conclusion: This study summarizes the common pathogens of VAP and the antibiotics commonly used in the treatment of VAP by describing the clinical information of 418 patients with VAP in the MIMIC database. In clinical treatment, we should pay attention to aseptic operation, develop appropriate antibacterial measures, closely monitor the pathogens of VAP infection, and use antibiotics in a timely manner to control the occurrence and development of VAP. |
| first_indexed | 2024-12-12T02:41:19Z |
| format | Article |
| id | doaj.art-9973eb58e9c949ada90584beeec3cd77 |
| institution | Directory Open Access Journal |
| issn | 1663-9812 |
| language | English |
| last_indexed | 2024-12-12T02:41:19Z |
| publishDate | 2019-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Pharmacology |
| spelling | doaj.art-9973eb58e9c949ada90584beeec3cd772022-12-22T00:41:10ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122019-02-011010.3389/fphar.2019.00062437952Description of Clinical Characteristics of VAP Patients in MIMIC DatabaseQingqing Liu0Qingqing Liu1Jin Yang2Jin Yang3Jun Zhang4Jun Zhang5Fanfan Zhao6Fanfan Zhao7Xiaojie Feng8Xiaojie Feng9Xue Wang10Jun Lyu11Jun Lyu12Clinical Research Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, ChinaSchool of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, ChinaClinical Research Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, ChinaSchool of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, ChinaClinical Research Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, ChinaSchool of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, ChinaClinical Research Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, ChinaSchool of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, ChinaClinical Research Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, ChinaSchool of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, ChinaICU, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, ChinaClinical Research Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, ChinaSchool of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, ChinaBackground: Ventilator-associated pneumonia (VAP) is a common and serious nosocomial infection of intensive-care units (ICUs). Accurate, timely diagnosis enables early VAP patients to receive appropriate therapies and reduce the occurrence of complication. However, so far clinical datas regarding the epidemiology and mortality of VAP are still limited. Medical Information Mart for Intensive Care (MIMIC) database is a free, open and public resource about ICU research database. MIMIC database is a free, open, public database that collects information on more than 40,000 ICU patients who are predominantly white people. Therefore, the purpose of the present study is to observe and describe the clinical characteristics of VAP patients in ICU from the MIMIC database.Method: A total of 418 patients were enrolled in the study. General information, ventilator use information, microbiology information, antibiotic use information, and some nursing-related information were extracted to describe and analyze the clinical features of VAP patients.Results: The results of the study showed that patients with one or three pathogens were the most. The main pathogens were YEAST (16.71%), STAPH AUREUS COAG+ (11.63%), Staphylococcus, COAGULASE NEGATIVE (8.68%), GRAM NEGATIVE ROD (S) (6.14%), and Pseudomonas aeruginosa (5.73%). Patients using 4 antibiotics were the most. The top five antibiotics in the largest proportion were synthetic antibacterials (24.66%), peptides (20.13%), cephalosporins (19.60%), penicillins (13.54%), and aminoglycosides (5.27%).Conclusion: This study summarizes the common pathogens of VAP and the antibiotics commonly used in the treatment of VAP by describing the clinical information of 418 patients with VAP in the MIMIC database. In clinical treatment, we should pay attention to aseptic operation, develop appropriate antibacterial measures, closely monitor the pathogens of VAP infection, and use antibiotics in a timely manner to control the occurrence and development of VAP.https://www.frontiersin.org/article/10.3389/fphar.2019.00062/fullventilator-associated pneumoniaVAPantibioticpathogenic bacteriaMIMIC database |
| spellingShingle | Qingqing Liu Qingqing Liu Jin Yang Jin Yang Jun Zhang Jun Zhang Fanfan Zhao Fanfan Zhao Xiaojie Feng Xiaojie Feng Xue Wang Jun Lyu Jun Lyu Description of Clinical Characteristics of VAP Patients in MIMIC Database Frontiers in Pharmacology ventilator-associated pneumonia VAP antibiotic pathogenic bacteria MIMIC database |
| title | Description of Clinical Characteristics of VAP Patients in MIMIC Database |
| title_full | Description of Clinical Characteristics of VAP Patients in MIMIC Database |
| title_fullStr | Description of Clinical Characteristics of VAP Patients in MIMIC Database |
| title_full_unstemmed | Description of Clinical Characteristics of VAP Patients in MIMIC Database |
| title_short | Description of Clinical Characteristics of VAP Patients in MIMIC Database |
| title_sort | description of clinical characteristics of vap patients in mimic database |
| topic | ventilator-associated pneumonia VAP antibiotic pathogenic bacteria MIMIC database |
| url | https://www.frontiersin.org/article/10.3389/fphar.2019.00062/full |
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