Seven-day antibiotic therapy for Enterobacterales bacteremia in high-risk neutropenic patients: toward a new paradigm.

PURPOSE: Data on short courses of antibiotic therapy for Enterobacterales bacteremia in high-risk neutropenic patients are limited. The aim of the study was to describe and compare the frequency of bacteremia relapse, 30-day overall and infection-related mortality, Clostridiodes difficile infection and length of hospital stay since bacteremia among those who received antibiotic therapy for 7 or 14 days. METHODS: This is a multicenter, prospective, observational cohort study in adult high-risk neutropenic patients with hematologic malignancies or hematopoietic stem cell transplant and monomicrobial Enterobacterales bacteremia. They received appropriate empirical antibiotic therapy, had a clinical response within 7 days, and infection source control. Clinical, epidemiological and outcomes variables were compared based on 7 or 14 days of AT. RESULTS: Two hundred patients were included (100, 7-day antibiotic therapy; 100, 14-day antibiotic therapy). Escherichia coli was the pathogen most frequently isolated (47.5%), followed by Klebsiella sp. (40.5%). Among those patients that received 7-day vs. 14-day antibiotic course, a clinical source of bacteremia was found in 54% vs. 57% (p = 0.66), multidrug-resistant Enterobacterales isolates in 28% vs. 30% (p = 0.75), and 40% vs. 47% (p = 0.31) received combined empirical antibiotic therapy. Overall mortality was 3% vs. 1% (p = 0.62), in no case related to infection; bacteremia relapse was 7% vs. 2% (p = 0.17), and length of hospital stay since bacteremia had a median of 9 days (IQR: 7-15) vs. 14 days (IQR: 13-22) (p = < 0.001). CONCLUSIONS: These data suggest that seven-day antibiotic therapy might be adequate for patients with high-risk neutropenia and Enterobacterales bacteremia, who receive appropriate empirical therapy, with clinical response and infection source control.

Ceftazidime-Avibactam Improves Outcomes in High-Risk Neutropenic Patients with Klebsiella pneumoniae Carbapenemase-Producing Enterobacterales Bacteremia.

Few studies have evaluated the efficacy of ceftazidime-avibactam (CA) for Klebsiella pneumoniae carbapenemase-producing Enterobacterales bacteremia (KPC-PEB) in high-risk neutropenic patients. This is a prospective multicenter observational study in high-risk neutropenic patients with multi-drug resistant Enterobacterales bacteremia. They were compared according to the resistance mechanism and definitive treatment provided: KPC-CPE treated with CA (G1), KPC-CPE treated with other antibiotics (G2), and patients with ESBL-producing Enterobacterales bacteremia who received appropriate definitive therapy (G3). Thirty-day mortality was evaluated using a logistic regression model, and survival was analyzed with Kaplan-Meier curves. A total of 238 patients were included: 18 (G1), 52 (G2), and 168 (G3). Klebsiella spp. (60.9%) and Escherichia coli (26.4%) were the Enterobacterales most frequently isolated, and 71% of the bacteremias had a clinical source. The resistance profile between G1 and G2 was colistin 35.3% vs. 36.5%, amikacin 16.7% vs. 40.4%, and tigeclycline 11.1% vs. 19.2%. The antibiotics prescribed in combination with G2 were carbapenems, colistin, amikacin, fosfomycin, tigecycline, and fluoroquinolones. Seven-day clinical response in G1 vs. G2 vs. G3 was 94.4% vs. 42.3% vs. 82.7%, respectively (p < 0.001). Thirty-day overall mortality in G1 vs. G2 vs. G3 was 22.2% vs. 53.8% vs. 11.9%, respectively (p < 0.001), and infection-related mortality was 5.5% vs. 51.9% vs. 7.7% (p < 0.001). The independent risk factors for mortality were Pitt score > 4: OR 3.63, 95% CI, 1.18-11.14 (p = 0.025) and KPC-PEB treated with other antibiotics: OR 8.85, 95% CI, 2.58-30.33 (p = 0.001), while 7-day clinical response was a protective factor for survival: OR 0.02, 95% CI, 0.01-0.08 (p < 0.001). High-risk neutropenic patients with KPC-CPE treated with CA had an outcome similar to those treated for ESBL-producing Enterobacterales, with higher 7-day clinical response and lower overall and infection-related mortality than those treated with other antibiotics. In view of these data, CA may be considered the preferred therapeutic option for KPC-PEB in high-risk neutropenic patients.

Development of a Clinical Score to Stratify the Risk for Carbapenem-Resistant Enterobacterales Bacteremia in Patients with Cancer and Hematopoietic Stem Cell Transplantation.

Identifying the risk factors for carbapenem-resistant Enterobacterales (CRE) bacteremia in cancer and hematopoietic stem cell transplantation (HSCT) patients would allow earlier initiation of an appropriate empirical antibiotic treatment. This is a prospective multicenter observational study in patients from 12 centers in Argentina, who presented with cancer or hematopoietic stem-cell transplant and developed Enterobacterales bacteremia. A multiple logistic regression model identified risk factors for CRE bacteremia, and a score was developed according to the regression coefficient. This was validated by the bootstrap resampling technique. Four hundred and forty-three patients with Enterobacterales bacteremia were included: 59 with CRE and 384 with carbapenem-susceptible Enterobacterales (CSE). The risk factors that were identified and the points assigned to each of them were: ≥10 days of hospitalization until bacteremia: OR 4.03, 95% CI 1.88-8.66 (2 points); previous antibiotics > 7 days: OR 4.65, 95% CI 2.29-9.46 (2 points); current colonization with KPC-carbapenemase-producing Enterobacterales: 33.08, 95% CI 11.74-93.25 (5 points). With a cut-off of 7 points, a sensitivity of 35.59%, specificity of 98.43%, PPV of 77.7%, and NPV of 90.9% were obtained. The overall performance of the score was satisfactory (AUROC of 0.85, 95% CI 0.80-0.91). Finally, the post-test probability of CRE occurrence in patients with none of the risk factors was 1.9%, which would virtually rule out the presence of CRE bacteremia.

Deleterious and Protective Psychosocial and Stress-Related Factors Predict Risk of Spontaneous Preterm Birth.

OBJECTIVES: The aim of the study was to: (1) Identify (early in pregnancy) psychosocial and stress-related factors that predict risk of spontaneous preterm birth (PTB, gestational age <37 weeks); (2) Investigate whether "protective" factors (e.g., happiness/social support) decrease risk; (3) Use the Dhabhar Quick-Assessment Questionnaire for Stress and Psychosocial Factors (DQAQ-SPF) to rapidly quantify harmful or protective factors that predict increased or decreased risk respectively, of PTB. STUDY DESIGN: This is a prospective cohort study. Relative risk (RR) analyses investigated association between individual factors and PTB. Machine learning-based interdependency analysis (IDPA) identified factor clusters, strength, and direction of association with PTB. A nonlinear model based on support vector machines was built for predicting PTB and identifying factors that most strongly predicted PTB. RESULTS: Higher levels of deleterious factors were associated with increased RR for PTB: General anxiety (RR = 8.9; 95% confidence interval [CI] = 2.0,39.6), pain (RR = 5.7; CI = 1.7,17.0); tiredness/fatigue (RR = 3.7; CI = 1.09,13.5); perceived risk of birth complications (RR = 4; CI = 1.6,10.01); self-rated health current (RR = 2.6; CI = 1.0,6.7) and previous 3 years (RR = 2.9; CI = 1.1,7.7); and divorce (RR = 2.9; CI = 1.1,7.8). Lower levels of protective factors were also associated with increased RR for PTB: low happiness (RR = 9.1; CI = 1.25,71.5); low support from parents/siblings (RR = 3.5; CI = 0.9,12.9), and father-of-baby (RR = 3; CI = 1.1,9.9). These factors were also components of the clusters identified by the IDPA: perceived risk of birth complications (p < 0.05 after FDR correction), and general anxiety, happiness, tiredness/fatigue, self-rated health, social support, pain, and sleep (p < 0.05 without FDR correction). Supervised analysis of all factors, subject to cross-validation, produced a model highly predictive of PTB (AUROC or area under the receiver operating characteristic = 0.73). Model reduction through forward selection revealed that even a small set of factors (including those identified by RR and IDPA) predicted PTB. CONCLUSION: These findings represent an important step toward identifying key factors, which can be assessed rapidly before/after conception, to predict risk of PTB, and perhaps other adverse pregnancy outcomes. Quantifying these factors, before, or early in pregnancy, could identify women at risk of delivering preterm, pinpoint mechanisms/targets for intervention, and facilitate the development of interventions to prevent PTB. KEY POINTS: · Newly designed questionnaire used for rapid quantification of stress and psychosocial factors early during pregnancy.. · Deleterious factors predict increased preterm birth (PTB) risk.. · Protective factors predict decreased PTB risk..

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning.

Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable, facilitating the development of precision medicine approaches. Objectives: The primary objectives were to jointly model multiple APOs and their connection to stress early in pregnancy, and to explore the underlying biology to guide development of accessible and measurable interventions. Materials and Methods: In a prospective cohort study, PSFs were assessed during the first trimester with an extensive self-filled questionnaire for 200 women. We used MML to simultaneously model, and predict APOs (severe preeclampsia, superimposed preeclampsia, gestational diabetes and early gestational age) as well as several risk factors (BMI, diabetes, hypertension) for these patients based on PSFs. Strongly interrelated stressors were categorized to identify potential therapeutic targets. Furthermore, for a subset of 14 women, we modeled the connection of PSFs to the maternal immune system to APOs by building corresponding ML models based on an extensive single cell immune dataset generated by mass cytometry time of flight (CyTOF). Results: Jointly modeling APOs in a MML setting significantly increased modeling capabilities and yielded a highly predictive integrated model of APOs underscoring their interconnectedness. Most APOs were associated with mental health, life stress, and perceived health risks. Biologically, stressors were associated with specific immune characteristics revolving around CD4/CD8 T cells. Immune characteristics predicted based on stress were in turn found to be associated with APOs. Conclusions: Elucidating connections among stress, multiple APOs simultaneously, and immune characteristics has the potential to facilitate the implementation of ML-based, individualized, integrative models of pregnancy in clinical decision making. The modifiable nature of stressors may enable the development of accessible interventions, with success tracked through immune characteristics.

Proposal of a clinical score to stratify the risk of multidrug-resistant gram-negative rods bacteremia in cancer patients

ABSTRACT Introduction: Multidrug-resistant gram-negative rods (MDR GNR) represent a growing threat for patients with cancer. Our objective was to determine the characteristics of and risk factors for MDR GNR bacteremia in patients with cancer and to develop a clinical score to predict MDR GNR bacteremia. Material and Methods: Multicenter prospective study analyzing initial episodes of MDR GNR bacteremia. Risk factors were evaluated using a multiple logistic regression (forward-stepwise selection) analysis including variables with a p < 0.10 in univariate analysis. Results: 394 episodes of GNR bacteremia were included, with 168 (42.6 %) being MDR GNR. Five variables were identified as independent risk factors: recent antibiotic use (OR = 2.8, 95 % CI 1.7-4.6, p = 0.001), recent intensive care unit admission (OR = 2.9, 95 % CI 1.1-7.8, p = 0.027), hospitalization ≥ 7 days prior to the episode of bacteremia (OR = 3.5, 95 % CI 2-6.2, p = 0.005), severe mucositis (OR = 5.3, 95 % CI 1.8-15.6, p = 0.002), and recent or previous colonization/infection with MDR GNR (OR = 2.3, 95 % CI 1.2-4.3, p = 0.028). Using a cut-off value of two points, the score had a sensitivity of 66.07 % (95 % CI 58.4-73.2 %), a specificity of 77.8 % (95 % CI 71.4-82.7 %), a positive predictive value of 68 % (95 % CI 61.9-73.4 %), and a negative predictive value of 75.9 % (95 % CI 71.6-79.7 %). The overall performance of the score was satisfactory (AUROC 0.78; 95 % CI 0.73-0.82). In the cases with one or none of the risk factors identified, the negative likelihood ratio was 0.18 and the post-test probability of having MDR GNR was 11.68 %. Conclusions: With the growing incidence of MDR GNR as etiologic agents of bacteremia in cancer patients, the development of this score could be a potential tool for clinicians.

Proposal of a clinical score to stratify the risk of multidrug-resistant gram-negative rods bacteremia in cancer patients.

INTRODUCTION: Multidrug-resistant gram-negative rods (MDR GNR) represent a growing threat for patients with cancer. Our objective was to determine the characteristics of and risk factors for MDR GNR bacteremia in patients with cancer and to develop a clinical score to predict MDR GNR bacteremia. MATERIAL AND METHODS: Multicenter prospective study analyzing initial episodes of MDR GNR bacteremia. Risk factors were evaluated using a multiple logistic regression (forward-stepwise selection) analysis including variables with a p<0.10 in univariate analysis. RESULTS: 394 episodes of GNR bacteremia were included, with 168 (42.6 %) being MDR GNR. Five variables were identified as independent risk factors: recent antibiotic use (OR=2.8, 95 % CI 1.7-4.6, p=0.001), recent intensive care unit admission (OR=2.9, 95 % CI 1.1-7.8, p=0.027), hospitalization ≥ 7 days prior to the episode of bacteremia (OR=3.5, 95 % CI 2-6.2, p=0.005), severe mucositis (OR=5.3, 95 % CI 1.8-15.6, p=0.002), and recent or previous colonization/infection with MDR GNR (OR=2.3, 95 % CI 1.2-4.3, p=0.028). Using a cut-off value of two points, the score had a sensitivity of 66.07 % (95 % CI 58.4-73.2 %), a specificity of 77.8 % (95 % CI 71.4-82.7 %), a positive predictive value of 68 % (95 % CI 61.9-73.4 %), and a negative predictive value of 75.9 % (95 % CI 71.6-79.7 %). The overall performance of the score was satisfactory (AUROC 0.78; 95 % CI 0.73-0.82). In the cases with one or none of the risk factors identified, the negative likelihood ratio was 0.18 and the post-test probability of having MDR GNR was 11.68 %. CONCLUSIONS: With the growing incidence of MDR GNR as etiologic agents of bacteremia in cancer patients, the development of this score could be a potential tool for clinicians.

Pandemic 2009 Influenza A (H1N1) virus infection in cancer and hematopoietic stem cell transplant recipients; a multicenter observational study.

BACKGROUND: During March 2009 a novel Influenza A virus emerged in Mexico. We describe the clinical picture of the pandemic Influenza A (H1N1) Influenza in cancer patients during the 2009 influenza season. METHODS: Twelve centers participated in a multicenter retrospective observational study of cancer patients with confirmed infection with the 2009 H1N1 Influenza A virus (influenza-like illness or pneumonia plus positive PCR for the 2009 H1N1 Influenza A virus  in respiratory secretions). Clinical data were obtained by retrospective chart review and analyzed.  RESULTS: From May to August 2009, data of 65 patients were collected. Median age was 51 years, 57 % of the patients were female. Most patients (47) had onco-hematological cancers and 18 had solid tumors. Cancer treatment mainly consisted of chemotherapy (46), or stem cell transplantation (SCT) (16). Only 19 of 64 patients had received the 2009 seasonal Influenza vaccine. Clinical presentation included pneumonia (43) and upper respiratory tract infection (22). Forty five of 58 ambulatory patients were admitted. Mechanical ventilation was required in 12 patients (18%). Treatment included oseltamivir monotherapy or in combination with amantadine for a median of 7 days. The global 30-day mortality rate was 18%. All 12 deaths were among the non-vaccinated patients. No deaths were observed among the 19 vaccinated patients. Oxygen saturation <96% at presentation was a predictor of mortality (OR 19.5; 95%CI: 2.28 to 165.9). CONCLUSIONS: In our cancer patient population, the pandemic 2009 Influenza A (H1N1) virus was associated with high incidence of pneumonia (66%), and 30-day mortality (18.5%). Saturation <96% was significantly associated with death. No deaths were observed among vaccinated patients.