scholarly journals Hospital-acquired complications in critically ill patients

2021 ◽  
Vol 23 (3) ◽  
pp. 285-291
Author(s):  
Graeme J Duke ◽  
◽  
Frank Shann ◽  
Cameron I Knott ◽  
Felix Oberender ◽  
...  
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Medical Records ◽  
Peer Group ◽  
Intraclass Correlation ◽  
Patient Characteristics ◽  
Tertiary Referral ◽  
Hospital Site ◽  
Administrative Dataset ◽  
Hospital Acquired

BACKGROUND: The national hospital-acquired complications (HAC) system has been promoted as a method to identify health care errors that may be mitigated by clinical interventions. OBJECTIVES: To quantify the rate of HAC in multiday stay adults admitted to major hospitals. DESIGN: Retrospective observational analysis of 5-year (July 2014 – June 2019) administrative dataset abstracted from medical records. SETTING: All 47 hospitals with on-site intensive care units (ICUs) in the State of Victoria. PARTICIPANTS: All adults (aged ≥ 18 years) stratified into planned or unplanned, surgical or medical, ICU or other ward, and by hospital peer group (tertiary referral, metropolitan, regional). MAIN OUTCOME MEASURES: HAC rates in ICU compared with ward, and mixed-effects regression estimates of the association between HAC and i) risk of clinical deterioration, and ii) admission hospital site (intraclass correlation coefficient [ICC] > 0.3). RESULTS: 211 120 adult ICU separations with mean hospital mortality of 7.3% (95% CI, 7.2–7.4%) reported 110 132 (42.6%) HAC events (commonly, delirium, infection, arrhythmia and respiratory failure) in 62 945 records (29.8%). Higher HAC rates were reported in elective (cardiac [50.3%] and non-cardiac [40.6%]) surgical subgroups compared with emergency medical subgroup (23.9%), and in tertiary (35.4%) compared with non-tertiary (22.7%) hospitals. HAC was strongly associated with on-admission patient characteristics (P < 0.001), but was weakly associated with hospital site (ICC, 0.08; 95% CI, 0.05–0.11). CONCLUSIONS: Critically ill patients have a high burden of HAC events, which appear to be associated with patient admission characteristics. HAC may an indicator of hospital admission complexity rather than hospital-acquired complications.

scholarly journals Factors Associated with Mortality in Critically Ill Patients Diagnosed with Hospital Acquired Infections

2020 ◽  
Vol Volume 13 ◽  
pp. 2811-2817
Author(s):  
Matheus L Otero ◽  
Rodrigo C Menezes ◽  
Isabella B B Ferreira ◽  
Francine L Issa ◽  
Gabriel Agareno ◽  
...  
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Hospital Acquired Infections ◽  
Factors Associated ◽  
Hospital Acquired

Hospital-Acquired Pneumonia in Critically Ill Patients

2004 ◽  
Vol 3 (2) ◽  
pp. 123-131 ◽  
Author(s):  
Olivier Leroy ◽  
Agn??s Meybeck ◽  
Thibaud d???Escrivan ◽  
Patrick Devos ◽  
Eric Kipnis ◽  
...  
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Hospital Acquired Pneumonia ◽  
Hospital Acquired

The role and limitations of scoring systems

2016 ◽  
Author(s):  
Hannah Wunsch ◽  
Andrew A. Kramer
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Molecular Level ◽  
Severity Of Illness ◽  
Scoring Systems ◽  
Patient Characteristics ◽  
Clinical Assessments ◽  
Risk Of Death ◽  
Individual Care ◽  
Severity Scores

Scoring systems for critically-ill patients provide a measure of the severity of illness of patients admitted to intensive care units (ICUs). They are primarily based on patient characteristics, physiological derangement, and/or clinical assessments. Severity scores themselves allow for risk-adjusting outcomes, but they can also be used to provide a prediction of the overall risk of death, length of stay, or other outcome for critically ill patients. This allows for comparison of outcomes between different cohorts of patients or between observed and predicted ICU performance. There are a number of general ICU scoring systems that are in use. All scoring systems have limitations. Future scoring systems may include prediction of longer-term outcomes, and assimilation of granular data temporally and at the molecular level that could result in more personalized severity scores to help guide individual care decisions.

Oral Care in Critically Ill Patients Requiring Noninvasive Ventilation: An Evidence-Based Review

2021 ◽  
Vol 41 (4) ◽  
pp. 66-70
Author(s):  
Jace D. Johnny ◽  
Zachary Drury ◽  
Tracey Ly ◽  
Janel Scholine
Keyword(s):  
Critically Ill ◽  
Noninvasive Ventilation ◽  
Critically Ill Patients ◽  
Oral Care ◽  
Preventive Measure ◽  
Standard Of Care ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Hospital Acquired Pneumonia ◽  
Hospital Acquired

Topic Hospital-acquired pneumonia commonly develops after 48 hours of hospitalization and can be divided into non–ventilator-acquired and ventilator-acquired pneumonia. Prevention of non–ventilator-acquired pneumonia requires a multimodal approach. Implementation of oral care bundles can reduce the incidence of ventilator-acquired pneumonia, but the literature on oral care in other populations is limited. Clinical Relevance Use of noninvasive ventilation is increasing owing to positive outcomes. The incidence of non–ventilator-acquired pneumonia is higher in patients receiving noninvasive ventilation than in the general hospitalized population but remains lower than that of ventilator-acquired pneumonia. Non–ventilator-acquired pneumonia increases mortality risk and hospital length of stay. Purpose To familiarize nurses with the evidence regarding oral care in critically ill patients requiring noninvasive ventilation. Content Covered No standard of oral care exists for patients requiring noninvasive ventilation owing to variation in study findings, definitions, and methods. Oral care decreases the risk of hospital-acquired pneumonia and improves comfort. Nurses perform oral care less often for nonintubated patients, as it is perceived as primarily a comfort measure. The potential risks of oral care for patients receiving noninvasive ventilation have not been explored. Further research is warranted before this practice can be fully implemented. Conclusion Oral care is a common preventive measure for non–ventilator-acquired pneumonia and may improve comfort. Adherence to oral care is lower for patients not receiving mechanical ventilation. Further research is needed to identify a standard of care for oral hygiene for patients receiving noninvasive ventilation and assess the risk of adverse events.

scholarly journals Low-Copy Number Polymorphism in DEFA1/DEFA3 Is Associated with Susceptibility to Hospital-Acquired Infections in Critically Ill Patients

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Jialian Zhao ◽  
Qiang Gu ◽  
Lifeng Wang ◽  
Weize Xu ◽  
Lihua Chu ◽  
...  
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Copy Number ◽  
Predictive Ability ◽  
Copy Number Variations ◽  
Copy Number Polymorphism ◽  
Hospital Acquired Infections ◽  
Low Copy Number ◽  
Genes Encoding ◽  
Hospital Acquired

DEFA1/DEFA3, genes encoding human neutrophil peptides (HNP) 1–3, display wide-ranging copy number variations (CNVs) and is functionally associated with innate immunity and infections. To identify potential associations between DEFA1/DEFA3 CNV and hospital-acquired infections (HAIs), we enrolled 106 patients with HAIs and 109 controls in the intensive care unit (ICU) and examined their DEFA1/DEFA3 CNVs. DEFA1/DEFA3 copy number ranged from 2 to 16 per diploid genome in all 215 critically ill patients, with a median of 7 copies. In HAIs, DEFA1/DEFA3 CNV varied from 2 to 12 with a median of 6, which was significantly lower than that in controls (2 to 16 with a median of 8, p=0.017). Patients with lower DEFA1/DEFA3 copy number (CNV < 7) were far more common in HAIs than in controls (52.8% in HAIs versus 35.8% in controls; p=0.014; OR, 2.010; 95% CI, 1.164–3.472). The area under the receiver operating characteristic (AUROC) of DEFA1/DEFA3 CNV combined with clinical characteristics to predict the incidence of HAIs was 0.763 (95% CI 0.700–0.827), showing strong predictive ability. Therefore, lower DEFA1/DEFA3 copy number contributes to higher susceptibility to HAIs in critically ill patients, and DEFA1/DEFA3 CNV is a significant hereditary factor for predicting HAIs.

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