Identification of risk factors and development of a predictive model for bloodstream infection in intensive care unit COVID-19 patients
Copyright © 2023 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved..
OBJECTIVES: To identify risk factors for nosocomial bloodstream infections (BSIs) in intensive care unit (ICU) patients with COVID-19 and to build a predictive model for BSIs.
PATIENTS AND METHODS: The retrospective case-control study included 236 ICU COVID-19 patients with BSIs group and 234 patients in the control group. Demographic and laboratory data, comorbidities, drug use, invasive procedures and identified pathogens were recorded separately for patients directly admitted and transferred to ICU. Fine and Gray's multi-variate competing risk model was used to build a predictive model for patients transferred to ICU.
RESULTS: The risk factors were: interleukin inhibitors (HR = 6.1 (95% CI: 2.0-18.5)) and dexamethasone (HR = 3.0 (95% CI: 1.3-7.1)) use in previous hospitalization, glomerular filtration rate <60 mL/min per 1.73 m2 (HR = 4.0 (95% CI: 2.1-7.6)) and blood glucose >9 mmol/L (HR = 2.5 (95% CI: 1.4-4.6)) in patients directly admitted to ICU; and dexamethasone use in previous hospitalization (HR = 4.5 (95% CI: 1.8-11)), the total dexamethasone dose before transfer to ICU (HR = 1.2 (95% CI: 1.06-1.37)), diabetes mellitus (HR = 1.4 (95% CI: 1.1-1.9)), alanine transaminase (ALT) ≥35.5 U/L on hospital admission (HR = 1.5 (95% CI: 1.1-2.1)), and the use of low-flow oxygen versus high-flow oxygen therapy or non-invasive mechanical ventilation on admission to ICU ((HR = 2.7 (95% CI: 5.6-11.1)) in patients transferred to ICU. A predictive model had sensitivity of 63-73% and specificity of 71-83% at different times of ICU stay.
CONCLUSIONS: Our findings may help clinicians detect patients at high risk of developing BSIs.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:139 |
|---|---|
| Enthalten in: |
The Journal of hospital infection - 139(2023) vom: 20. Sept., Seite 150-157 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Strelkova, D [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
7S5I7G3JQL |
|---|
| Anmerkungen: |
Date Completed 28.08.2023 Date Revised 28.08.2023 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1016/j.jhin.2023.06.026 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM359792421 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM359792421 | ||
| 003 | DE-627 | ||
| 005 | 20231226081631.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.jhin.2023.06.026 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1199.xml |
| 035 | |a (DE-627)NLM359792421 | ||
| 035 | |a (NLM)37478910 | ||
| 035 | |a (PII)S0195-6701(23)00216-5 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Strelkova, D |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Identification of risk factors and development of a predictive model for bloodstream infection in intensive care unit COVID-19 patients |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 28.08.2023 | ||
| 500 | |a Date Revised 28.08.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved. | ||
| 520 | |a OBJECTIVES: To identify risk factors for nosocomial bloodstream infections (BSIs) in intensive care unit (ICU) patients with COVID-19 and to build a predictive model for BSIs | ||
| 520 | |a PATIENTS AND METHODS: The retrospective case-control study included 236 ICU COVID-19 patients with BSIs group and 234 patients in the control group. Demographic and laboratory data, comorbidities, drug use, invasive procedures and identified pathogens were recorded separately for patients directly admitted and transferred to ICU. Fine and Gray's multi-variate competing risk model was used to build a predictive model for patients transferred to ICU | ||
| 520 | |a RESULTS: The risk factors were: interleukin inhibitors (HR = 6.1 (95% CI: 2.0-18.5)) and dexamethasone (HR = 3.0 (95% CI: 1.3-7.1)) use in previous hospitalization, glomerular filtration rate <60 mL/min per 1.73 m2 (HR = 4.0 (95% CI: 2.1-7.6)) and blood glucose >9 mmol/L (HR = 2.5 (95% CI: 1.4-4.6)) in patients directly admitted to ICU; and dexamethasone use in previous hospitalization (HR = 4.5 (95% CI: 1.8-11)), the total dexamethasone dose before transfer to ICU (HR = 1.2 (95% CI: 1.06-1.37)), diabetes mellitus (HR = 1.4 (95% CI: 1.1-1.9)), alanine transaminase (ALT) ≥35.5 U/L on hospital admission (HR = 1.5 (95% CI: 1.1-2.1)), and the use of low-flow oxygen versus high-flow oxygen therapy or non-invasive mechanical ventilation on admission to ICU ((HR = 2.7 (95% CI: 5.6-11.1)) in patients transferred to ICU. A predictive model had sensitivity of 63-73% and specificity of 71-83% at different times of ICU stay | ||
| 520 | |a CONCLUSIONS: Our findings may help clinicians detect patients at high risk of developing BSIs | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Bacteraemia | |
| 650 | 4 | |a Bloodstream infection | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a Nosocomial infection | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 7 | |a Dexamethasone |2 NLM | |
| 650 | 7 | |a 7S5I7G3JQL |2 NLM | |
| 700 | 1 | |a Rachina, S |e verfasserin |4 aut | |
| 700 | 1 | |a Fedina, L |e verfasserin |4 aut | |
| 700 | 1 | |a Vlasenko, A |e verfasserin |4 aut | |
| 700 | 1 | |a Tetevina, M |e verfasserin |4 aut | |
| 700 | 1 | |a Drogashevskaya, D |e verfasserin |4 aut | |
| 700 | 1 | |a Chesnokova, M |e verfasserin |4 aut | |
| 700 | 1 | |a Kuleshov, V |e verfasserin |4 aut | |
| 700 | 1 | |a Burmistrova, E |e verfasserin |4 aut | |
| 700 | 1 | |a Sychev, I |e verfasserin |4 aut | |
| 700 | 1 | |a Ananicheva, N |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t The Journal of hospital infection |d 1993 |g 139(2023) vom: 20. Sept., Seite 150-157 |w (DE-627)NLM012638692 |x 1532-2939 |7 nnns |
| 773 | 1 | 8 | |g volume:139 |g year:2023 |g day:20 |g month:09 |g pages:150-157 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.jhin.2023.06.026 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 139 |j 2023 |b 20 |c 09 |h 150-157 | ||