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.

Improving management of febrile neutropenia in oncology patients: the role of artificial intelligence and machine learning.

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) have the potential to revolutionize the management of febrile neutropenia (FN) and drive progress toward personalized medicine. AREAS COVERED: In this review, we detail how the collection of a large number of high-quality data can be used to conduct precise mathematical studies with ML and AI. We explain the foundations of these techniques, covering the fundamentals of supervised and unsupervised learning, as well as the most important challenges, e.g. data quality, 'black box' model interpretation and overfitting. To conclude, we provide detailed examples of how AI and ML have been used to enhance predictions of chemotherapy-induced FN, detection of bloodstream infections (BSIs) and multidrug-resistant (MDR) bacteria, and anticipation of severe complications and mortality. EXPERT OPINION: There is promising potential of implementing accurate AI and ML models whilst managing FN. However, their integration as viable clinical tools poses challenges, including technical and implementation barriers. Improving global accessibility, fostering interdisciplinary collaboration, and addressing ethical and security considerations are essential. By overcoming these challenges, we could transform personalized care for patients with FN.

Infection epidemiology in relation to different therapy phases in patients with haematological malignancies receiving CAR T-cell therapy.

BACKGROUND: We described the real-life epidemiology and causes of infections on the different therapy phases in patients undergoing chimeric antigen receptor (CAR) T-cells directed towards CD19+ or BCMA+ cells. METHODS: All consecutive patients receiving CAR T-cell therapy at our institution were prospectively followed-up. We performed various comparative analyses of all patients and subgroups with and without infections. RESULTS: Ninety-one adults mainly received CAR T-cell therapy for acute leukaemia (53%) and lymphoma (33%). We documented a total of 77 infections in 47 (52%) patients, 37 (48%) during the initial neutropenic phase and 40 (52%) during the non-neutropenic phase. Infections during the neutropenic phase were mainly due to bacterial (29, 78%): catheter infections (11 [38%] cases), endogenous source (5 [17%]), and Clostridioides difficile (5 [17%]). Patients receiving corticosteroids after CAR T-cell therapy had a higher risk of endogenous infection (100% vs. 16%; p = .006). During the non-neutropenic phase, bacterial infections remained very frequent (24, 60%), mainly with catheter source (8, 33%). Respiratory tract infections were common (17, 43%). CONCLUSIONS: Infections after CAR T-cell therapy were frequent. During the neutropenic phase, it is essential to prevent nosocomial infections and balance the use of antibiotics to lower endogenous bacteraemia and Clostridial infection rates.

Multiplex real-time PCR FilmArray performance in the diagnosis of meningoencephalitis: lights and shadows.

PURPOSE: We aimed to evaluate the performance of the FilmArray (FA) meningitis/encephalitis (ME) panel. Secondarily, we analyzed the false positive (FP) and false negative (FN) results, as well as the predictive values of the technique, regarding the cerebrospinal fluid (CSF) characteristics. METHODS: FA is a multiplex real-time PCR detecting 14 of the most common ME pathogens in CSF. All FA performed at our hospital (2018-2022) were retrospectively reviewed. FA was compared to conventional techniques and its performance was assessed based on the final diagnosis of the episode. RESULTS: FA was performed in 313 patients with suspicion of ME. Most patients had altered mental status (65.2%) and fever (61%). Regarding CSF characteristics, 49.8% and 53.7% presented high CSF proteins and pleocytosis, respectively. There were 84 (26.8%) positive FA results, mainly for HSV-1 (10.9%), VZV (5.1%), Enterovirus (2.6%), and S. pneumoniae (1.9%). In the 136 cases where both FA and routine methods were performed, there was a 25.7% lack of agreement. We identified 6.6% FN results, but 28.6% FP, mainly due to HSV-1. This resulted in a high negative predictive value (NPV) of 93.4%, but a positive predictive value (PPV) of 73%. Remarkably, PPV as low as 36.9%, and 70.2%, were found in cases without pleocytosis, or lack of high CSF protein levels, respectively. CONCLUSION: FA was associated with high NPV, but frequent FP results and low PPV, particularly for HSV-1, and especially in patients without high CSF protein levels or pleocytosis.

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)

The Etiology, Antibiotic Therapy and Outcomes of Bacteremic Skin and Soft-Tissue Infections in Onco-Hematological Patients.

OBJECTIVES: to assess the current epidemiology, antibiotic therapy and outcomes of onco- hematological patients with bacteremic skin and soft-tissue infections (SSTIs), and to identify the risk factors for Gram-negative bacilli (GNB) infection and for early and overall mortality. METHODS: episodes of bacteremic SSTIs occurring in cancer patients at two hospitals were prospectively recorded and retrospectively analyzed. RESULTS: Of 164 episodes of bacteremic SSTIs, 53% occurred in patients with solid tumors and 47% with hematological malignancies. GNB represented 45.5% of all episodes, led by Pseudomonas aeruginosa (37.8%). Multidrug resistance rate was 16%. Inadequate empirical antibiotic therapy (IEAT) occurred in 17.7% of episodes, rising to 34.6% in those due to resistant bacteria. Independent risk factors for GNB infection were corticosteroid therapy and skin necrosis. Early and overall case-fatality rates were 12% and 21%, respectively. Risk factors for early mortality were older age, septic shock, and IEAT, and for overall mortality were older age, septic shock and resistant bacteria. CONCLUSIONS: GNB bacteremic SSTI was common, particularly if corticosteroid therapy or skin necrosis. IEAT was frequent in resistant bacteria infections. Mortality occurred mainly in older patients with septic shock, resistant bacteria and IEAT. These results might guide empirical antibiotic therapy in this high-risk population.

Epidemiology and risk factors for recurrence in biliary source bloodstream infection episodes in oncological patients.

We aimed to describe the characteristics and outcomes of biliary source bloodstream infections (BSIs) in oncological patients. Secondarily, we analyzed risk factors for recurrent BSI episodes. All episodes of biliary source BSIs in oncological patients were prospectively collected (2008-2019) and retrospectively analyzed. Logistic regression analyses were performed. A rule to stratify patients into risk groups for recurrent biliary source BSI was conducted. Four hundred biliary source BSIs were documented in 291 oncological patients. The most frequent causative agents were Escherichia coli (42%) and Klebsiella spp. (27%), and 86 (21.5%) episodes were caused by multidrug-resistant Gram-negative bacilli (MDR-GNB). The rates of MDR-GNB increased over time. Overall, 73 patients developed 118 recurrent BSI episodes. Independent risk factors for recurrent BSI episodes were prior antibiotic therapy (OR 3.781, 95% CI 1.906-7.503), biliary prosthesis (OR 2.232, 95% CI 1.157-4.305), prior admission due to suspected biliary source infection (OR 4.409, 95% CI 2.338-8.311), and BSI episode caused by an MDR-GNB (OR 2.857, 95% CI 1.389-5.874). With these variables, a score was generated that predicted recurrent biliary source BSI with an area under the receiver operating characteristic (ROC) curve of 0.819. Inappropriate empirical antibiotic treatment (IEAT) was administered in 23.8% of patients, and 30-d mortality was 19.5%. As a conclusion, biliary source BSI in oncological patients is mainly caused by GNB, with high and increasing MDR rates, frequent IEAT, and high mortality. Recurrent BSI episodes are frequent. A simple score to identify recurrent episodes was developed to potentially establish prophylactic strategies. IMPORTANCE This study shows that biliary source bloodstream infections (BSIs) in oncological patients are mainly caused by Gram-negative bacilli (GNB), with high and increasing rates of multidrug resistance. Importantly, recurrent biliary source BSI episodes were very frequent and associated with delays in chemotherapy, high rates of inappropriate empirical antibiotic therapy, and high 30-d mortality (19.5%). Using the variable independently associated with recurrent BSI episodes, a score was generated that predicted recurrent biliary source BSI with high accuracy. This score could be used to establish prophylactic strategies and lower the risk of relapsing episodes and the associated morbidity and mortality.

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.

Breakthrough invasive fungal infection among patients with haematologic malignancies: A national, prospective, and multicentre study.

OBJECTIVES: We describe the current epidemiology, causes, and outcomes of breakthrough invasive fungal infections (BtIFI) in patients with haematologic malignancies. METHODS: BtIFI in patients with ≥ 7 days of prior antifungals were prospectively diagnosed (36 months across 13 Spanish hospitals) according to revised EORTC/MSG definitions. RESULTS: 121 episodes of BtIFI were documented, of which 41 (33.9%) were proven; 53 (43.8%), probable; and 27 (22.3%), possible. The most frequent prior antifungals included posaconazole (32.2%), echinocandins (28.9%) and fluconazole (24.8%)-mainly for primary prophylaxis (81%). The most common haematologic malignancy was acute leukaemia (64.5%), and 59 (48.8%) patients had undergone a hematopoietic stem-cell transplantation. Invasive aspergillosis, principally caused by non-fumigatus Aspergillus, was the most frequent BtIFI with 55 (45.5%) episodes recorded, followed by candidemia (23, 19%), mucormycosis (7, 5.8%), other moulds (6, 5%) and other yeasts (5, 4.1%). Azole resistance/non-susceptibility was commonly found. Prior antifungal therapy widely determined BtIFI epidemiology. The most common cause of BtIFI in proven and probable cases was the lack of activity of the prior antifungal (63, 67.0%). At diagnosis, antifungal therapy was mostly changed (90.9%), mainly to liposomal amphotericin-B (48.8%). Overall, 100-day mortality was 47.1%; BtIFI was either the cause or an essential contributing factor to death in 61.4% of cases. CONCLUSIONS: BtIFI are mainly caused by non-fumigatus Aspergillus, non-albicans Candida, Mucorales and other rare species of mould and yeast. Prior antifungals determine the epidemiology of BtIFI. The exceedingly high mortality due to BtIFI warrants an aggressive diagnostic approach and early initiation of broad-spectrum antifungals different than those previously used.

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.

Real-life epidemiology and current outcomes of hospitalized adults with invasive fungal infections.

We aimed to describe the current epidemiology of both hosts with invasive fungal infections (IFIs) and causative fungi. And, detail outcomes of these infections at 12 weeks in a real-life cohort of hospitalized patients. The study was retrospective and observational to describe IFI diagnosed in a tertiary hospital (February 2017-December 2021). We included all consecutive patients meeting criteria for proven or probable IFI according to EORTC-MSG and other criteria. A total of 367 IFIs were diagnosed. 11.7% were breakthrough infections, and 56.4% were diagnosed in the intensive care unit. Corticosteroid use (41.4%) and prior viral infection (31.3%) were the most common risk factors for IFI. Lymphoma and pneumocystis pneumonia were the most common baseline and fungal diseases. Only 12% of IFI occurred in patients with neutropenia. Fungal cultures were the most important diagnostic tests (85.8%). The most frequent IFIs were candidemia (42.2%) and invasive aspergillosis (26.7%). Azole-resistant Candida strains and non-fumigatus Aspergillus infections represented 36.1% and 44.5% of the cases, respectively. Pneumocystosis (16.9%), cryptococcosis (4.6%), and mucormycosis (2.7%) were also frequent, as well as mixed infections (3.4%). Rare fungi accounted for 9.5% of infections. Overall, IFI mortality at 12 weeks was 32.2%; higher rates were observed for Mucorales (55.6%), Fusarium (50%), and mixed infections (60%). We documented emerging changes in both hosts and real-life IFI epidemiology. Physicians should be aware of these changes to suspect infections and be aggressive in diagnoses and treatments. Currently, outcomes for such clinical scenarios remain extremely poor.

Current epidemiology of the host and fungi and IFI treatments are changing. Real-life data on this subject are scarce. We present our most recent evidence to highlight the importance of the ongoing challenges that require further investigation and clinical adjustments.

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.

New treatments for multidrug-resistant non-fermenting Gram-negative bacilli Infections

Ceftolozane/tazobactam, ceftazidime/avibactam and cefiderocol belong to a novel generation of antibiotics that correspond with the β-lactam family. It is necessary to having new options in treating infections caused by Gram-negative, non-fermenting multidrug-resistant bacilli due to the significant increase in multidrug resistance in the last decades. Knowing the main characteristics of each drug is key for correct use. (AU)

Impact of SARS-CoV-2 viral load and duration of symptoms before hospital admission on the mortality of hospitalized COVID-19 patients.

PURPOSE: Assess the impact of viral load estimated by cycle threshold (Ct) of reverse transcription real time-polymerase chain reaction (rRT-PCR) and the days from symptoms onset on mortality in hospitalized patients with COVID19. METHODS: Retrospective observational study of 782 patients with a positive rRT-PCR from a nasopharyngeal swab was performed within the first 24 h from admission. Demographic data, clinical manifestations and laboratory parameters were collected. Uni- and multivariate analyses were performed to identify factors associated with mortality at 60 days. RESULTS: Ct was divided into three groups and the mortality rate decreased from 27.3 to 20.7% and 9.8% for Ct values of ≤ 20, 21-25 and > 25, respectively (P = 0.0001). The multivariate analysis identified as predictors of mortality, a Ct value < 20 (OR 3.13, CI 95% 1.38-7.10), between 21-25 (OR 2.47, CI 95% 1.32-4.64) with respect to a Ct value > 25. Days from symptoms onset is a variable associated with mortality as well (DSOA) ≤ 6 (OR 1.86, CI 95% 1.00-3.46), among other factors. Patients requiring hospital admission within 6 DSOA with a Ct value ≤ 25 had the highest mortality rate (28%). CONCLUSIONS: The inclusion of Ct values and DSOA in the characterization of study populations could be a useful tool to evaluate the efficacy of antivirals.

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.

Clinical Presentation and Outcome of COVID-19 in a Latin American Versus Spanish Population: Matched Case-Control Study.

INTRODUCTION: Increased mortality has been reported in the Latin American population. The objective is to compare the clinical characteristics and outcome of Latin American and Spanish populations in a cohort of patients hospitalized with COVID-19 during the first year of the pandemic. METHODS: We retrospectively analysed all the Latin American patients (born in South or Central America) hospitalized in our centre from February 2020 to February 2021 and compared them with an age- and gender-matched group of Spanish subjects. Variables included were demographics, co-morbidities, clinical and analytical parameters at admission and treatment received. The primary outcomes were ICU admission and mortality at 60 days. A conditional regression analysis was performed to evaluate the independent baseline predictors of both outcomes. RESULTS: From the 3216 patients in the whole cohort, 216 pairs of case-controls (Latin American and Spanish patients, respectively) with same age and gender were analysed. COPD was more frequent in the Spanish group, while HIV was more prevalent in the Latin American group. Other co-morbidities showed no significant difference. Both groups presented with similar numbers of days from symptom onset, but the Latin American population had a higher respiratory rate (21 vs. 20 bpm, P = 0.041), CRP (9.13 vs. 6.22 mg/dl, P = 0.001), ferritin (571 vs. 383 ng/ml, P = 0.012) and procalcitonin (0.10 vs. 0.07 ng/ml, P = 0.020) at admission and lower cycle threshold of PCR (27 vs. 28.8, P = 0.045). While ICU admission and IVM were higher in the Latin American group (17.1% vs. 13% and 9.7% vs. 5.1%, respectively), this was not statistically significant. Latin American patients received remdesivir and anti-inflammatory therapies more often, and no difference in the 60-day mortality rate was found (3.2% for both groups). CONCLUSION: Latin American patients with COVID-19 have more severe disease than Spanish patients, requiring ICU admission, antiviral and anti-inflammatory therapies more frequently. However, the mortality rate was similar in both groups.

C-reactive protein cut-off for early tocilizumab and dexamethasone prescription in hospitalized patients with COVID-19.

Dexamethasone and tocilizumab have been associated with reduction in mortality, however, the beneficial effect is not for all patients and the impact on viral replication is not well defined. We hypostatized that C-reactive protein (CRP) could help in the identification of patients requiring anti-inflammatory therapy. Patients admitted for > 48 h in our hospital for a confirmed or suspected infection by SARS-CoV-2 from February 2020 to February 2021 were retrospectively evaluated. The primary outcome was mortality at 30 days. Demographics and the most relevant variables related with the outcome were included. CRP was stratified by percentiles. Univariate and multivariate analysis were performed. A total of 3218 patients were included with a median (IQR) age of 66 (74-78) years and 58.9% were males. The rate of intensive care unit admission was 24.4% and the 30-day mortality rate was 11.8%. Within the first 5 days from admission, 1018 (31.7%) patients received dexamethasone and 549 tocilizumab (17.1%). The crude analysis showed a mortality reduction in patients receiving dexamethasone when CRP was > 13.75 mg/dL and > 3.5 mg/dL for those receiving tocilizumab. Multivariate analysis identified the interaction of CRP > 13.75 mg/dL with dexamethasone (OR 0.57; CI 95% 0.37-0.89, P = 0014) and CRP > 3.5 mg/dL with tocilizumab (0.65; CI95%:0.44-0.95, P = 0.029) as independent predictors of mortality. Our results suggest that dexamethasone and tocilizumab are associated with a reduction in mortality when prescribed to patients with a certain inflammatory activity assessed by C-reactive protein.