Non-Ventilated Hospital Acquired Pneumonia: Secondary Analysis Of Quantitative Research Data

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2024-09

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University of Birmingham

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Background: Non-ventilator hospital-acquired pneumonia (NV-HAP) considerably contributes to morbidity and mortality in hospitalized patients but has not been as extensively studied as ventilator-associated pneumonia (VAP). This study aimed to identify the patient characteristics and risk factors impact the length of hospital stay and 30-day mortality in NV-HAP patients. Method: This single-centre, retrospective cohort study was conducted at Queen Elizabeth Hospital, Birmingham, involving 113 patients diagnosed with NV-HAP between November 2019 and February 2020. Data were collected on demographics, comorbidities, smoking status, and age on admission. Descriptive analyses were followed by correlation tests, the Kruskal-Wallis test, and logistic regression to evaluate predictors of LOS and 30-day mortality. Results: The analysis showed a mean LOS of 21.16 days, with age displaying a significant correlation with prolonged hospitalisation. Despite a 30-day mortality rate of 5.3%, the logistic regression did not find any significant predictors of mortality. The models effectively predicted survival but failed to predict deaths, indicating limitations in current clinical factors in predicting early mortality in NV-HAP incidents. Conclusion: The study highlights the demand for improved predictive models incorporating broader clinical data to better understand and manage NV-HAP. The findings suggest that while comorbidity and age influence length of hospital stays , they are not sufficient for predicting short-term mortality.

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Non-ventilator hospital-acquired pneumonia (NV-HAP) Hospital-acquired infections Length of hospital stay (LOS) 30-day mortality Risk factors Patient characteristics Retrospective cohort study COVID-19 pandemic Comorbidity analysis Logistic regression Spearman’s rank-order correlation Kruskal-Wallis test Queen Elizabeth Hospital Birmingham Chest X-ray diagnosis Clinical outcomes

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