ArticleActa bio-medica : Atenei Parmensis2022
Hospital acquired infections in COVID-19 patients in sub intensive care unit: analysis of two waves of admissions.
Article in Acta bio-medica : Atenei Parmensis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- eHealth interventions for chronic pain: Protocol for a systematic review and meta-analysis.MethodsX · 2025Article
- Factors behind Antibiotic Therapy: A Survey of Primary Care Pediatricians in Lombardy.International journal of environmental research and public health · 2024Article
- Vaccination Open Day: A Cross-Sectional Study on the 2023 Experience in Lombardy Region, Italy.International journal of environmental research and public health · 2024Article
- How the COVID-19 Pandemic Affected Attendance at a Tertiary Orthopedic Center Emergency Department: A Comparison between the First and Second Waves.Diagnostics (Basel, Switzerland) · 2022Article
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Authors and funding
12 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimThe pandemic caused by SARS-COV-2 has increased Semi-Intensive Care Unit (SICU) admission, causing an increase in healthcare-associated infection (HAI). Mostly HAI reveals the same risk factors, but fewer studies have analyzed the possibility of multiple coinfections in these patients. The study aimed was to identify patterns of co-presence of different species describing at the same time the association between such patterns and patient demographics and, finally, comparing the patterns between the two cohorts of COVID-19 patients admitted at Policlinico during the first wave and the second one).
methodsAll the patients admitted to SICUs during two COVID-19 waves, from March to June 2020 months and from October to December 2020, were screened following the local infection control surveillance program; whoever manifested fever has undergone on microbiological culture to detect bacterial species. Statistical analysis was performed to observe the existence of microbiological patterns through DBSCAN method.
results246 patients were investigated and 83 patients were considered in our study because they presented infection symptoms with a mean age of 67 years and 33.7% of female patients. During the first and second waves were found respectively 10 and 8 bacterial clusters with no difference regarding the most frequent species.
conclusionsThe results show the importance of an analysis which considers the risk factors for the possibility of co- and superinfection (such as age and gender) to structure a good prognostic tool to predict which patients will encounter severe coinfections during hospitalization.
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