K-Means Clustering Identifies Diverse Clinical Phenotypes in COVID-19 Patients: Implications for Mortality Risks and Remdesivir Impact.

INTRODUCTION: The impact of remdesivir on mortality in patients with COVID-19 is still controversial. We aimed to identify clinical phenotype clusters of COVID-19 hospitalized patients with highest benefit from remdesivir use and validate these findings in an external cohort. METHODS: We included consecutive patients hospitalized between February 2020 and February 2021 for COVID-19. The derivation cohort comprised subjects admitted to Hospital Clinic of Barcelona. The validation cohort included patients from Hospital Universitari Mutua de Terrassa (Terrassa) and Hospital Universitari La Fe (Valencia), all tertiary centers in Spain. We employed K-means clustering to group patients according to reverse transcription polymerase chain reaction (rRT-PCR) cycle threshold (Ct) values and lymphocyte counts at diagnosis, and pre-test symptom duration. The impact of remdesivir on 60-day mortality in each cluster was assessed. RESULTS: A total of 1160 patients (median age 66, interquartile range (IQR) 55-78) were included. We identified five clusters, with mortality rates ranging from 0 to 36.7%. Highest mortality rate was observed in the cluster including patients with shorter pre-test symptom duration, lower lymphocyte counts, and lower Ct values at diagnosis. The absence of remdesivir administration was associated with worse outcome in the high-mortality cluster (10.5% vs. 36.7%; p < 0.001), comprising subjects with higher viral loads. These results were validated in an external multicenter cohort of 981 patients. CONCLUSIONS: Patients with COVID-19 exhibit varying mortality rates across different clinical phenotypes. K-means clustering aids in identifying patients who derive the greatest mortality benefit from remdesivir use.

Real-Life Comparison of Antivirals for SARS-CoV-2 Omicron Infection in Patients With Hematologic Malignancies.

BACKGROUND: We aimed to describe a cohort of hematologic patients with COVID-19 treated with antivirals early. METHODS: Non-interventional chart review study. Comparison of baseline characteristics and outcomes in high-risk hematologic patients treated with remdesivir between December 2021 and April 2022 versus those treated with nirmatrelvir/ritonavir between May and August 2022. RESULTS: Eighty-three patients were analyzed. Forty-two received remdesivir, and 41 nirmatrelvir/ritonavir. Patients with remdesivir were younger, vaccinated with lower number of doses, and received prior corticosteroids less frequently and sotrovimab, hyperimmune plasma and corticosteroids more often. Viral shedding median (IQR) duration was 18 (13-23) and 11 (8-21) days in the remdesivir and nirmatrelvir/ritonavir groups, respectively (p = 0.004). Median (IQR) Ct values before treatment were similar in both groups. Within 5 days of treatment, median (IQR) Ct values were 26 (23-29) and 33 (30-37) in the remdesivir and nirmatrelvir/ritonavir groups, respectively (p < 0.0001). All patients were hospitalized for remdesivir administration and only four (9.8%) in the nirmatrelvir/ritonavir group. The overall outcomes in this cohort of COVID-19 patients with Omicron variant was good, as no patient needed oxygen or ICU admission. One patient in remdesivir group died from septic shock. No severe adverse event was recorded in both treatment groups. CONCLUSIONS: Patients with hematologic malignancies and non-severe COVID-19 who received nirmatrelvir/ritonavir experienced faster decrease in viral load and shorter viral shedding. Furthermore, besides the advantage of oral administration, nirmatrelvir/ritonavir administration reduced the need of hospital admission.

Identifying the most important data for research in the field of infectious diseases: thinking on the basis of artificial intelligence / Identificación de los datos más importantes para el desarrollo de inteligencia artificial en el campo de las enfermedades infecciosas

Objectives. Clinical data on which artificial intelligence (AI) algorithms are trained and tested provide the basis to im prove diagnosis or treatment of infectious diseases (ID). We aimed to identify important data for ID research to prioritise efforts being undertaken in AI programmes. Material and methods. We searched for 1,000 articles from high-impact ID journals on PubMed, selecting 288 of the latest articles from 10 top journals. We classified them into structured or unstructured data. Variables were homogenised and grouped into the following categories: epidemiology, ad mission, demographics, comorbidities, clinical manifestations, laboratory, microbiology, other diagnoses, treatment, out comes and other non-categorizable variables. Results. 4,488 individual variables were collected, from the 288 articles. 3,670 (81.8%) variables were classified as structured data whilst 818 (18.2%) as unstructured data. From the structured data, 2,319 (63.2%) variables were classified as direct—retrievable from electronic health records—whilst 1,351 (36.8%) were indirect. The most frequent unstructured data were related to clinical manifestations and were repeated across articles. Data on demographics, comorbidities and mi crobiology constituted the most frequent group of variables. Conclusions. This article identified that structured vari ables have comprised the most important data in research to generate knowledge in the field of ID. Extracting these data should be a priority when a medical centre intends to start an AI programme for ID. We also documented that the most important unstructured data in this field are those related to clinical manifestations. Such data could easily undergo some structuring with the use of semi-structured medical records focusing on a few symptoms (AU)

Objetivos. Los datos clínicos sobre los que se entrenan y prueban los algoritmos de inteligencia artificial (IA) proporcio nan la base para mejorar el diagnóstico o el tratamiento de las enfermedades infecciosas (EI). Nuestro objetivo es identificar datos importantes para la investigación de las enfermedades infecciosas con el fin de priorizar los esfuerzos realizados en los programas de IA. Material y métodos. Se buscaron 1.000 artículos de re vistas de EI de alto impacto en PubMed, seleccionando 288 de los últimos artículos en 10 revistas de primer nivel. Los clasifi camos en datos estructurados o no estructurados. Las variables se homogeneizaron y agruparon en las siguientes categorías: epidemiología, ingreso, demografía, comorbilidades, manifes taciones clínicas, laboratorio, microbiología, otros diagnósticos, tratamiento, desenlace y otras variables no categorizables. Resultados. Se recogieron 4.488 variables individuales, pro cedentes de 288 artículos. 3670 (81,8%) variables se clasificaron como datos estructurados, mientras que 818 (18,2%) como da tos no estructurados. De los datos estructurados, 2.319 (63,2%) variables se clasificaron como directas -recuperables a partir de historias clínicas electrónicas-, mientras que 1.351 (36,8%) fueron indirectas. Los datos no estructurados más frecuentes estaban re lacionados con las manifestaciones clínicas y se repetían en todos los artículos. Los datos sobre demografía, comorbilidades y micro biología constituyeron el grupo más frecuente de variables Conclusiones. Este artículo identificó que las variables es tructuradas han constituido los datos más importantes en la investigación para generar conocimiento en el campo de la EI. La extracción de estos datos debería ser una prioridad cuando un centro médico pretende iniciar un programa de IA para la EI (AU)

High Rate of Inappropriate Antibiotics in Patients with Hematologic Malignancies and Pseudomonas aeruginosa Bacteremia following International Guideline Recommendations.

Optimal coverage of Pseudomonas aeruginosa is challenging in febrile neutropenic patients due to a progressive increase in antibiotic resistance worldwide. We aimed to detail current rates of resistance to antibiotics recommended by international guidelines for P. aeruginosa isolated from bloodstream infections (BSI) in patients with hematologic malignancies. Secondarily, we aimed to describe how many patients received inappropriate empirical antibiotic treatment (IEAT) and its impact on mortality. We conducted a retrospective, multicenter cohort study of the last 20 BSI episodes caused by P. aeruginosa in patients with hematologic malignancies from across 14 university hospitals in Spain. Of the 280 patients with hematologic malignancies and BSI caused by P. aeruginosa, 101 (36%) had strains resistant to at least one of the ß-lactam antibiotics recommended in international guidelines, namely, cefepime, piperacillin-tazobactam, and meropenem. Additionally, 21.1% and 11.4% of the strains met criteria for MDR and XDR P. aeruginosa, respectively. Even if international guidelines were followed in most cases, 47 (16.8%) patients received IEAT and 66 (23.6%) received inappropriate ß-lactam empirical antibiotic treatment. Thirty-day mortality was 27.1%. In the multivariate analysis, pulmonary source (OR 2.22, 95% CI 1.14 to 4.34) and IEAT (OR 2.67, 95% CI 1.37 to 5.23) were factors independently associated with increased mortality. We concluded that P. aeruginosa-causing BSI in patients with hematologic malignancies is commonly resistant to antibiotics recommended in international guidelines, which is associated with frequent IEAT and higher mortality. New therapeutic strategies are needed. IMPORTANCE Bloodstream infection (BSI) caused by P. aeruginosa is related with an elevated morbidity and mortality in neutropenic patients. For this reason, optimal antipseudomonal coverage has been the basis of all historical recommendations in the empirical treatment of febrile neutropenia. However, in recent years the emergence of multiple types of antibiotic resistances has posed a challenge in treating infections caused by this microorganism. In our study we postulated that P. aeruginosa-causing BSI in patients with hematologic malignancies is commonly resistant to antibiotics recommended in international guidelines. This observation is associated with frequent IEAT and increased mortality. Consequently, there is a need for a new therapeutic strategy.

Current outcomes of SARS-CoV-2 Omicron variant infection in high-risk haematological patients treated early with antivirals.

OBJECTIVES: We aimed to describe the clinical outcomes and duration of viral shedding in high-risk patients with haematological malignancies hospitalized with COVID-19 during Omicron variant predominance who received early treatment with antivirals. METHODS: We conducted a prospective observational study on high-risk haematological patients admitted in our hospital between December 2021 and March 2022. We performed detection techniques on viral subgenomic mRNAs until negative results were obtained to document active, prolonged viral replication. RESULTS: This analysis included 60 consecutive adults with high-risk haematological malignancies and COVID-19. All of these patients underwent early treatment with remdesivir. Thirty-two (53%) patients received combined antiviral strategies, with sotrovimab or hyperimmune plasma being added to remdesivir. The median length of viral replication-as measured by real-time RT-PCR and/or subgenomic RNA detection-was 20 (IQR 14-28) days. Prolonged viral replication (6 weeks after diagnosis) was documented in six (10%) patients. Only two patients had prolonged infection for more than 2 months. Overall mortality was 5%, whereas COVID-19-related mortality was 0%. CONCLUSIONS: Current outcomes of high-risk patients with haematological malignancies hospitalized with COVID-19 during Omicron variant predminance are good with the use of early antiviral strategies. Persistent viral shedding is uncommon.

Pseudomonas aeruginosa Bloodstream Infection, Resistance, and Mortality: Do Solid Organ Transplant Recipients Do Better or Worse?

BACKGROUND: The prevalence of antimicrobial resistance of Pseudomonas aeruginosa (P. aeruginosa) in solid organ transplant (SOT) recipients is higher than that of the general population. However, the literature supporting this statement is scarce. Identifying patients at risk of carbapenem resistance (CR) is of great importance, as CR strains more often receive inappropriate empiric antibiotic therapy, which is independently associated with mortality in bloodstream infections (BSIs). METHODS: We prospectively recorded data from all consecutive BSIs from January 1991 to July 2019 using a routine purpose-designed surveillance database. The following variables were included: age, sex, type of transplant, use of vascular and urinary catheters, presence of neutropenia, period of diagnosis, treatment with steroids, origin of BSI, source of bacteremia, septic shock, ICU admission, mechanical ventilation, previous antibiotic treatment, treatment of bacteremia, and 30-day all-cause mortality. RESULTS: We identified 2057 episodes of P. aeruginosa BSI. Of these, 265 (13%) episodes corresponded to SOT recipients (130 kidney transplants, 105 liver, 9 hearts, and 21 kidney-pancreas). Hematologic malignancy [OR 2.71 (95% CI 1.33-5.51), p = 0.006] and prior carbapenem therapy [OR 2.37 (95% CI 1.46-3.86), p < 0.001] were associated with a higher risk of having a CR P. aeruginosa BSI. Age [OR 1.03 (95% CI 1.02-1.04) p < 0.001], urinary catheter [OR 2.05 (95% CI 0.37-3.06), p < 0.001], shock at onset [OR 6.57 (95% CI 4.54-9.51) p < 0.001], high-risk source [OR 4.96 (95% CI 3.32-7.43) p < 0.001], and bacteremia caused by CR strains [OR 1.53 (95% CI 1.01-2.29) p = 0.036] were associated with increased mortality. Correct empirical therapy was protective [OR 0.52 (95% CI 0.35-0.75) p = 0.001]. Mortality at 30 days was higher in non-SOT patients (21% vs. 13%, p = 0.002). SOT was not associated with a higher risk of having a CR P. aeruginosa BSI or higher mortality. CONCLUSIONS: In our cohort of 2057 patients with P. aeruginosa BSIs, hematologic malignancies and previous carbapenem therapy were independently associated with a risk of presenting CR P. aeruginosa BSI. Age, urinary catheter, high-risk source, bacteremia caused by carbapenem-resistant strains, and severity of the infection were independently associated with mortality, whereas correct empirical therapy was a protective factor. An increasing trend in the resistance of P. aeruginosa was found, with >30% of the isolates being resistant to carbapenems in the last period. SOT was not associated with a higher risk of carbapenem-resistant BSIs or higher mortality.

Resistance to empirical ß-lactams recommended in febrile neutropenia guidelines in Gram-negative bacilli bloodstream infections in Spain: a multicentre study.

OBJECTIVES: To describe current resistance to the ß-lactams empirically recommended in the guidelines in bloodstream infection (BSI) episodes caused by Gram-negative bacilli (GNB). METHODS: Retrospective, multicentre cohort study of the last 50 BSI episodes in haematological patients across 14 university hospitals in Spain. Rates of inappropriate empirical antibiotic therapy (IEAT) and impact on mortality were evaluated. RESULTS: Of the 700 BSI episodes, 308 (44%) were caused by GNB, mainly Escherichia coli (141; 20.1%), Klebsiella spp. (56; 8%) and Pseudomonas aeruginosa (48; 6.9%). Among GNB BSI episodes, 80 (26%) were caused by MDR isolates. In those caused by Enterobacterales, 25.8% were ESBL producers and 3.5% were carbapenemase producers. Among P. aeruginosa BSI episodes, 18.8% were caused by MDR isolates. Overall, 34.7% of the isolated GNB were resistant to at least one of the three ß-lactams recommended in febrile neutropenia guidelines (cefepime, piperacillin/tazobactam and meropenem). Despite extensive compliance with guideline recommendations (91.6%), 16.6% of BSI episodes caused by GNB received IEAT, which was more frequent among MDR GNB isolates (46.3% versus 6.1%; P < 0.001). Thirty day mortality was 14.6%, reaching 21.6% in patients receiving IEAT. CONCLUSIONS: Current resistance to empirical ß-lactams recommended in febrile neutropenia guidelines is exceedingly high and IEAT rates are greater than desired. There is an urgent need to adapt guidelines to current epidemiology and better identify patients with a high risk of developing MDR GNB infection.

Bacterial co-infection at hospital admission in patients with COVID-19.

OBJECTIVES: We described the current incidence and risk factors of bacterial co-infection in hospitalized patients with COVID-19. METHODS: Observational cohort study was performed at the Hospital Clinic of Barcelona (February 2020-February 2021). All patients with COVID-19 who were admitted for >48 hours with microbiological sample collection and procalcitonin (PCT) determination within the first 48 hours were included. RESULTS: A total of 1125 consecutive adults met inclusion criteria. Co-infections were microbiologically documented in 102 (9.1%) patients. Most frequent microorganisms were Streptococcus pneumoniae (79%), Staphylococcus aureus (6.8%), and Haemophilus influenzae (6.8%). Test positivity was 1% (8/803) for blood cultures, 10.1% (79/780) for pneumococcal urinary antigen test, and 11.4% (15/132) for sputum culture. Patients with PCT higher than 0.2, 0.5, 1, and 2 ng/mL had significantly more co-infections than those with lower levels (p=0.017, p=0.031, p<0.001, and p<0.001, respectively). In multivariate analysis, oxygen saturation ≤94% (OR 2.47, CI 1.57-3.86), ferritin levels <338 ng/mL (OR 2.63, CI 1.69-4.07), and PCT higher than 0.2 ng/mL (OR 1.74, CI 1.11-2.72) were independent risk factors for co-infection at hospital admission owing to COVID-19. CONCLUSIONS: Bacterial co-infection in patients hospitalized for COVID-19 is relatively common. However, clinicians could spare antibiotics in patients with PCT values <0.2, especially with high ferritin values and oxygen saturation >94%.