Frequency and factors associated with hospital readmission after COVID-19 hospitalization: the importance of post-COVID diarrhea

Purpose: The aim of this study was to describe the incidence and risk factors for hospital readmission and infection during the months after COVID-19 hospital admission. Methods: This prospective study included adult patients who were hospitalized due to COVID-19 and had been discharged from April 2020 to August 2020. All patients had a medical evaluation with a structured questionnaire 6 to 11 months after hospital admission. The authors included only patients with confirmed COVID-19 by RT-PCR. Patients with pregnant/postpartum women, with a proven COVID-19 reinfection or incapable of answering the questionnaire were excluded. Results: A total of 822 patients completed the follow-up assessment, and 68% reported at least one recurrent symptom related to COVID-19. The most frequent symptom was myalgia (42%). Thirty-two percent of patients visited an emergency room after COVID-19 hospitalization, and 80 (10%) patients required re-hospitalization. Risk factors for hospital readmission were orotracheal intubation during COVID-19 hospitalization (p = 0.003, OR = 2.14), Charlson score (p = 0.002, OR = 1.21), congestive heart failure (p = 0.005, OR = 2.34), peripheral artery disease (p = 0.06, OR = 2.06) and persistent diarrhea after COVID-19 hospitalization discharge (p = 0.02, OR = 1.91). The main cause of hospital readmission was an infection, 43 (54%). Pneumonia was the most frequent infection (29%). Conclusions: The presence of symptoms after six months of COVID-19 diagnosis was frequent, and hospital readmission was relatively high

Characteristics of a hepatitis C patient cohort at a specialized tertiary care facility: Identifying criteria to improve the allocation of public health resources

OBJECTIVES: Our objective was to analyze, in a population treated for hepatitis C infection at a tertiary care treatment unit, the prevalence of comorbidities and extrahepatic manifestations, the range and degree of the clinical complexity and the associations between advanced liver disease and clinical variables. METHODS: Medical records from chronically infected hepatitis C patients seen at a dedicated treatment facility for complex cases in the Infectious Diseases Division of Hospital das Clı´nicas in Brazil were analyzed. Clinical complexity was defined as the presence of one or more of the following conditions: advanced liver disease (Metavir score F3 or F4 and/or clinical manifestations or ultrasound/endoscopy findings consistent with cirrhosis) or hepatocellular carcinoma and/or 3 or more extrahepatic manifestations and/or comorbidities concomitantly. RESULTS: Among the 1574 patients analyzed, only 41% met the definition of being clinically complex. Cirrhosis or hepatocarcinoma was identified in 22.2% and 1.8% of patients, respectively. According to multiple logistic regression analysis, male sex (p=0.007), age440 years (po0.001) and the presence of metabolic syndrome (p=0.008) were independently associated with advanced liver disease. CONCLUSION: The majority of patients did not meet the criteria for admittance to this specialized tertiary service, reinforcing the need to reevaluate public health policies. Enhanced utilization of existing basic and intermediate complexity units for the management of less complex hepatitis C cases could improve care and lower costs

Predicting the outcome for COVID-19 patients by applying time series classification to electronic health records

Abstract Background COVID-19 caused more than 622 thousand deaths in Brazil. The infection can be asymptomatic and cause mild symptoms, but it also can evolve into a severe disease and lead to death. It is difficult to predict which patients will develop severe disease. There are, in the literature, machine learning models capable of assisting diagnose and predicting outcomes for several diseases, but usually these models require laboratory tests and/or imaging. Methods We conducted a observational cohort study that evaluated vital signs and measurements from patients who were admitted to Hospital das Clínicas (São Paulo, Brazil) between March 2020 and October 2021 due to COVID-19. The data was then represented as univariate and multivariate time series, that were used to train and test machine learning models capable of predicting a patient’s outcome. Results Time series-based machine learning models are capable of predicting a COVID-19 patient’s outcome with up to 96% general accuracy and 81% accuracy considering only the first hospitalization day. The models can reach up to 99% sensitivity (discharge prediction) and up to 91% specificity (death prediction). Conclusions Results indicate that time series-based machine learning models combined with easily obtainable data can predict COVID-19 outcomes and support clinical decisions. With further research, these models can potentially help doctors diagnose other diseases

Lipase and factor V (but not viral load) are prognostic factors for the evolution of severe yellow fever cases

BACKGROUND Despite a highly efficacious vaccine, yellow fever (YF) is still a major threat in developing countries and a cause of outbreaks. In 2018, the Brazilian state of São Paulo witnessed a new YF outbreak in areas where the virus has not been detected before. OBJECTIVE The aim is to describe the clinical and laboratorial characteristics of severe cases of YF, evaluate viral to determine markers associated with fatal outcome. METHODS Acute severe YF cases (n = 62) were admitted to the Intensive Care Unit of a reference hospital and submitted to routine laboratorial evaluation on admission. YFV-RNA was detected in serum and urine by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and then sequenced. Patients were classified in two groups: survival or death. FINDINGS In the univariate analysis the following variables were associated with outcome: alanin aminotransferase (ALT), aspartat aminotransferase (AST), AST/ALT ratio, total bilirubin (TB), chronic kidney disease epidemiology collaboration (CKD-EPI), ammonia, lipase, factor V, international normalised ratio (INR), lactate and bicarbonate. Logistic regression model showed two independent variables associated with death: lipase [odds ratio (OR) 1.018, 95% confidence interval (CI) 1.007 to 1.030, p = 0.002], and factor V (OR -0.955, 95% CI 0.929 to 0.982, p = 0.001). The estimated lipase and factor V cut-off values that maximised sensitivity and specificity for death prediction were 147.5 U/L [area under the curve (AUC) = 0.879], and 56.5% (AUC = 0.913). MAIN CONCLUSIONS YF acute severe cases show a generalised involvement of different organs (liver, spleen, heart, kidneys, intestines and pancreas), and different parameters were related to outcome. Factor V and lipase are independent variables associated with death, reinforcing the importance of hemorrhagic events due to fulminant liver failure and pointing to pancreatitis as a relevant event in the outcome of the disease

The Molecular Characterization of Hepatitis A Virus Strains Circulating during Hepatitis A Outbreaks in São Paulo, Brazil, from September 2017 to May 2019

Outbreaks of hepatitis A may occur in countries of medium and high socioeconomic levels in which the population generally exhibits an increased susceptibility in young adults to this infection if they are not vaccinated against the hepatitis A virus (HAV). In Europe, an outbreak involved approximately 22 European countries with 4475 cases reported from 2016 to 2018; most of them were men who have sex with men (MSM). This outbreak expanded to North and South America, including Brazil, particularly in São Paulo city with 1547 reported cases from 2016 to 2019. In the present study, we characterized the HAV strains involved in the acute hepatitis A cases identified in the reference centers of São Paulo city during this outbreak. A total of 51 cases with positive anti-HAV IgM were included, 80.4% male, 68.6% of them between 20 and 40 years old and 41.7% MSM. HAV RNA was detected in 92% (47/51) of the cases. Subgenotype IA of HAV was identified and most of the strains were closely related to that isolated in outbreaks that occurred in different European countries in 2016. These results showed the epidemiological relation between these outbreaks and reinforce the need to implement vaccination against hepatitis A for the adult population, particularly for a population with a high-risk behavior

Additional file 1 of Correlating drug prescriptions with prognosis in severe COVID-19: first step towards resource management

Additional file 1 Table S1 List of drugs prescribed, frequency of prescription, and proportion of patients discharged alive who used the drug and Table S2 Twenty drugs mostly correlated with outcome according to feature selection --- age groups and weeks since the onset of symptoms