Publications by authors named "G Meco"
Article Synopsis
- - Multiple system atrophy (MSA) is a severe disease with varying motor and autonomic symptoms, and previous studies have linked certain clinical factors to reduced survival rates.
- - Researchers analyzed 210 MSA patients over 17 years to create a survival risk model using clinical factors like age at symptom onset and early autonomic failure.
- - They developed a nomogram to predict individual survival probabilities over 7 years, which showed good accuracy and could enhance patient counseling and treatment strategies.
Background: Pneumocystis jirovecii pneumonia (PJP) is an opportunistic, life-threatening disease commonly affecting immunocompromised patients. The distribution of predisposing diseases or conditions in critically ill patients admitted to intensive care unit (ICU) and subjected to diagnostic work-up for PJP has seldom been explored.
Materials And Methods: The primary objective of the study was to describe the characteristics of ICU patients subjected to diagnostic workup for PJP.
Article Synopsis
- The study looked at how carbapenem resistance in a type of bacteria called Klebsiella pneumoniae affects how many people survive after getting a blood infection.
- Out of 426 patients, 25% had a more dangerous version of the bacteria, and those patients had higher death rates compared to those with a less resistant version.
- The research showed that the type of treatment given didn't really change the survival chances, suggesting that in certain areas, the treatment might be good enough for both types of bacteria.
With the wide diffusion of web technology, dedicated electronic Case Report Forms (eCRFs) became the main tool for collecting patient data. The focus of this work is to thoroughly consider the data quality in every aspect of the design of the eCRF, with the result of having multiple steps of validation that should produce a diligent and multidisciplinary approach towards every step of data acquisition. This goal affects every aspect of the system design.
View Article and Find Full Text PDFBackground: Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis.
Methods: Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method.