Camila Pacheco Silveira Martins da Mata
Biographic Data
| ID | 8410414 |
|---|---|
| NAME | Camila Pacheco Silveira Martins da Mata |
| GIVEN NAMES | Camila Pacheco Silveira Martins |
| FAMILY NAME | da Mata |
| SIGNATURE | DA MATA C P S M |
| AFFILIATIONS | Universidade Federal de Minas Gerais |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Algorithms for predicting Covid outcome using ready-to-use laboratorial and clinical data
The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging crisis affecting the public health system. The clinical features of COVID-19 can range from an asymptomatic state to acute respiratory syndrome and multiple organ dysfunction. Although some hematological and biochemical parameters are altered during moderate and severe COVID-19, there is still a lack of tools to combine these parameters to predict t…
Association between multidrug-resistant bacteria and outcomes in intensive care unit patients
Background In intensive care units (ICUs), infections by multidrug-resistant (MDR) microorganisms should be monitored to prevent healthcare-associated infections (HAIs). Methods From 2018 to 2020, we investigated all medical records of patients admitted to the ICU of a public university hospital. All patients colonized/infected by MDR microorganisms and submitted to active surveillance cultures (ASCs) were included. Results and discussion Male pa…
Relationship between clinical-epidemiological parameters and outcomes of patients with Covid-19 admitted to the intensive care unit
Background People in low-income countries, especially those with low socio-economic conditions, are likelier to test positive for SARS-CoV-2. The unequal conditions of public health systems also increase the infection rate and make early identification and treatment of at-risk patients difficult. Here, we aimed to characterize the epidemiological profile of COVID-19 patients in intensive care and identify laboratory and clinical markers associate…
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Relationship between clinical-epidemiological parameters and outcomes of patients with Covid-19 admitted to the intensive care unit
Background People in low-income countries, especially those with low socio-economic conditions, are likelier to test positive for SARS-CoV-2. The unequal conditions of public health systems also increase the infection rate and make early identification and treatment of at-risk patients difficult. Here, we aimed to characterize the epidemiological profile of COVID-19 patients in intensive care and identify laboratory and clinical markers associate…
Algorithms for predicting Covid outcome using ready-to-use laboratorial and clinical data
The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging crisis affecting the public health system. The clinical features of COVID-19 can range from an asymptomatic state to acute respiratory syndrome and multiple organ dysfunction. Although some hematological and biochemical parameters are altered during moderate and severe COVID-19, there is still a lack of tools to combine these parameters to predict t…
Association between multidrug-resistant bacteria and outcomes in intensive care unit patients
Background In intensive care units (ICUs), infections by multidrug-resistant (MDR) microorganisms should be monitored to prevent healthcare-associated infections (HAIs). Methods From 2018 to 2020, we investigated all medical records of patients admitted to the ICU of a public university hospital. All patients colonized/infected by MDR microorganisms and submitted to active surveillance cultures (ASCs) were included. Results and discussion Male pa…
Intensive care medicine (3 works) · Medicine (3 works) · Intensive care unit (2 works) · Internal Medicine (2 works) · Pathology (2 works) · 2019-20 coronavirus outbreak (1 work) · Antibiotic Resistance in Bacteria (1 work) · Antibiotic Use and Resistance (1 work) · Artificial Intelligence in Healthcare (1 work) · Biology (1 work)