Procalcitonin and C-Reactive Protein As Markers of Bacteremia in Patients With Febrile Neutropenia Who Receive Chemotherapy for Acute Leukemia: A Prospective Study From Nepal

A biomarker panel of C-reactive protein, procalcitonin and serum amyloid A is a predictor of sepsis in severe trauma patients

Severe trauma could induce sepsis due to the loss of control of the infection, which may eventually lead to death. Accurate and timely diagnosis of sepsis with severe trauma remains challenging both for clinician and laboratory. Combinations of markers, as opposed to single ones, may improve diagnosis. We compared the diagnostic characteristics of routinely used biomarkers of sepsis alone and in combination, trying to define a biomarker panel to predict sepsis in severe patients. This prospective observational study included patients with severe trauma (Injury severity score, ISS = 16 or more) in the emergency intensive care unit (EICU) at a university hospital. Blood samples were collected and plasma levels of procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6) and serum amyloid A (SAA) were measured using commercial enzyme linked immunosorbent assay (ELISA) kits. A total of 100 patients were eligible for analysis. Of these, 52 were diagnosed with sepsis. CRP yielded the highest discriminative value followed by PCT. In multiple logistic regression, SAA, CRP, and PCT were found to be independent predictors of sepsis. Bioscore which was composed of SAA, CRP, and PCT was shown to be far superior to that of each individual biomarker taken individually. Therefore, compared with single markers, the biomarker panel of PCT, CRP, and SAA was more predictive of sepsis in severe polytrauma patients.

Highlights from ecancer Choosing Wisely Nepal 2022: critical appraisal skills for evidence-based practice, 24th-25th September 2022, Kathmandu, Nepal

The ecancer Kathmandu 2022 workshop on the 24th-25th September 2022 was the first ecancer conference organised in Nepal, a Southeast Asian nation sandwiched between India and China. It was focused on critical appraisal skills for evidence-based practice and was organised in partnership with the Karnali Academy of Health Sciences and the Civil Service Hospital from Nepal, and the Queen's Global Oncology Program from Canada. The workshop emphasised the need for critical thinking in understanding clinical research, and also motivated the delegates to undertake meaningful clinical research relevant to the local setting. The sessions highlighted the features of a good clinical research, identify pitfalls in the reporting of clinical trials, implementation of the research into locally relevant practice and development of local clinical guidelines. Furthermore, the faculty also discussed how to write a good scientific paper, the do's and don'ts of a systematic review and meta-analysis, the role of peer-review and how to do one properly and what do editors look for in evaluating papers submitted for publication. The audience learned the importance of finding a good mentor and fostering local and international collaboration. The local faculty also highlighted their own personal journeys and how mentorship and global collaboration played an important role in their own academic career. The enthusiastic panel discussion was a highlight of the programme where the delegates learned about several important topics from the faculties, such as work-life balance, the role of mentorship in building careers and building networks.

Clinical Epidemiology Characteristics and Etiology of Febrile Neutropenia in Children: Analysis of 421 Cases

The congenital immune system includes neutrophils, which perform a variety of functions. Congenital and acquired neutropenia are rare illnesses with an underestimated prevalence in children. The aim of this study is to examine the epidemiology and etiology of febrile neutropenia in children at Haiphong Children’s Hospital, Haiphong, Vietnam. Methods: A cross-sectional study was carried out on 421 febrile neutropenia children. Clinical and laboratory characteristics were examined. Results: The median age (IQR) was 25.0 (12.5–59.5) months. The male-to-female ratio was 1.35/1. There were twice as many children living in the suburbs (66.98%) as in urban areas (33.02%). The mean (SD) temperature at admission was 38.50 ± 0.59 °C. Diagnosed causes associated with neutropenia included acute respiratory infections 250 (59.45%), gastrointestinal infections 68 (16.1%), erythema 37 (8.79%), acute leukemia 15 (3.56%), urinary tract infection 5 (1.19%), and encephalitis/meningitis 4 (0.95%). Viral etiology accounted for 61.52% (259): influenza type A—50.19% (130), influenza type B—31.27% (81), dengue virus—14.67% (38), measles virus 1—93% (5), rotavirus—1.54% (4), and EBV—0.4% (1). Twenty-five patients (5.94%) were found to have bacteria in their cultures, with Streptococcus pneumonia being the most common (eight patients; 32%). Conclusions: Febrile neutropenia was common in children under 2 years old. Primary clinical manifestations were acute upper respiratory tract infections, and viruses most commonly caused febrile neutropenia. Further studies with larger sample sizes are needed to determine the cause of febrile neutropenia.

Machine learning-assisted prediction of pneumonia based on non-invasive measures

Background

Pneumonia is an infection of the lungs that is characterized by high morbidity and mortality. The use of machine learning systems to detect respiratory diseases via non-invasive measures such as physical and laboratory parameters is gaining momentum and has been proposed to decrease diagnostic uncertainty associated with bacterial pneumonia. Herein, this study conducted several experiments using eight machine learning models to predict pneumonia based on biomarkers, laboratory parameters, and physical features.

Methods

We perform machine-learning analysis on 535 different patients, each with 45 features. Data normalization to rescale all real-valued features was performed. Since it is a binary problem, we categorized each patient into one class at a time. We designed three experiments to evaluate the models: (1) feature selection techniques to select appropriate features for the models, (2) experiments on the imbalanced original dataset, and (3) experiments on the SMOTE data. We then compared eight machine learning models to evaluate their effectiveness in predicting pneumonia

Results

Biomarkers such as C-reactive protein and procalcitonin demonstrated the most significant discriminating power. Ensemble machine learning models such as RF (accuracy = 92.0%, precision = 91.3%, recall = 96.0%, f1-Score = 93.6%) and XGBoost (accuracy = 90.8%, precision = 92.6%, recall = 92.3%, f1-score = 92.4%) achieved the highest performance accuracy on the original dataset with AUCs of 0.96 and 0.97, respectively. On the SMOTE dataset, RF and XGBoost achieved the highest prediction results with f1-scores of 92.0 and 91.2%, respectively. Also, AUC of 0.97 was achieved for both RF and XGBoost models.

Conclusions

Our models showed that in the diagnosis of pneumonia, individual clinical history, laboratory indicators, and symptoms do not have adequate discriminatory power. We can also conclude that the ensemble ML models performed better in this study.

Understanding and Managing Sepsis in Patients With Cancer in the Era of Antimicrobial Resistance

Sepsis is a frequent complication in immunosuppressed cancer patients and hematopoietic stem cell transplant recipients that is associated with high morbidity and mortality rates. The worldwide emergence of antimicrobial resistance is of special concern in this population because any delay in starting adequate empirical antibiotic therapy can lead to poor outcomes. In this review, we aim to address: (1) the mechanisms involved in the development of sepsis and septic shock in these patients; (2) the risk factors associated with a worse prognosis; (3) the impact of adequate initial empirical antibiotic therapy given the current era of widespread antimicrobial resistance; and (4) the optimal management of sepsis, including adequate and early source control of infection, optimized antibiotic use based on the pharmacokinetic and pharmacodynamics changes in these patients, and the role of the new available antibiotics.

Olanzapine for the prophylaxis and rescue of chemotherapy-induced nausea and vomiting: a systematic review, meta-analysis, cumulative meta-analysis and fragility assessment of the literature

INTRODUCTION

The aim of this study is to rigorously review the efficacy and safety of olanzapine in defined hematology oncology settings including (1) the setting of highly emetogenic chemotherapy (HEC) and moderately emetogenic chemotherapy (MEC) settings (2) at 5 mg and 10 mg doses, and (3) for response rates for use in the acute, delayed, and overall settings post-MEC and HEC.

METHODS

Ovid MEDLINE, Embase, and Cochrane Central Register of Controlled Trials were searched through April 23, 2020. The primary efficacy endpoints were the rate of complete response, in the acute (0-24 h post-chemotherapy), delayed (24-120 h post-chemotherapy), and overall (0-120 h post-chemotherapy) phases. The secondary efficacy endpoints were the rates of no nausea and no emesis, for each phase. Safety endpoints were the rate of no serious adverse events (i.e., no grade 3 or 4 toxicities), as assessed by Common Terminology Criteria for Adverse Events (CTCAE) criteria. The Mantel-Haenszel, random-effects analysis model was used to compute risk ratios and accompanying 95% confidence intervals for each endpoint. For endpoints that statistically favored one arm, absolute risk differences were computed to assess whether there is a 10% or greater difference, used as the threshold for clinical significance by MASCC/ESMO. Fragility indices were also calculated for each statistically significant endpoint, to quantitatively assess the robustness of the summary estimate. A cumulative meta-analysis was conducted for each efficacy meta-analysis with more than 5 studies, also using the Mantel-Haenszel random-effects analysis model.

RESULTS

Three studies reported on olanzapine for the rescue of breakthrough chemotherapy-induced nausea and vomiting (CINV); 22 studies reported on olanzapine in the prophylactic setting. For studies reporting on HEC patients, olanzapine-containing regimens were statistically and clinically superior in seven of nine efficacy endpoints in the prophylaxis setting. When olanzapine is administered at a 10-mg dose, it is statistically and clinically superior to control patients in eight of nine endpoints among adults. Olanzapine may be effective in the MEC setting and when administered at 5-mg doses, but the paucity of data leads to notable uncertainty.

CONCLUSION

Further RCTs are needed in the setting of MEC patients and administration of olanzapine at a lower 5-mg dose, which may be given to reduce the sedative effect of olanzapine at 10 mg.

Mitigating Effect of 1-Palmitoyl-2-Linoleoyl-3-Acetyl-Rac-Glycerol (PLAG) on a Murine Model of 5-Fluorouracil-Induced Hematological Toxicity

5-Fluorouracil (5-FU) is an antimetabolite chemotherapy widely used for the treatment of various cancers. However, many cancer patients experience hematological side effects following 5-FU treatment. Here, we investigated the protective effects of 1-palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol (PLAG) as a mitigator against 5-FU-induced hematologic toxicity, including neutropenia, monocytopenia, thrombocytopenia, and thrombocytosis, in Balb/c mice injected with 5-FU (100 mg/kg, i.p.). Administration of PLAG significantly and dose-dependently reduced the duration of neutropenia and improved the nadirs of absolute neutrophil counts (ANCs). Moreover, while the ANCs of all mice in the control fell to the severely neutropenic range, none of the mice in the PLAG 200 and 400 mg/kg-treated groups experienced severe neutropenia. Administration of PLAG significantly delayed the mean first day of monocytopenia and reduced the duration of monocytopenia. PLAG also effectively reduced extreme changes in platelet counts induced by 5-FU treatment, thus preventing 5-FU-induced thrombocytopenia and thrombocytosis. PLAG significantly decreased plasma levels of the chemokine (C–X–C motif) ligand 1 (CXCL1), CXCL2, interleukin (IL)-6, and C-reactive protein (CRP), which were elevated consistently with the occurrence time of neutropenia, monocytopenia, and thrombocytopenia. When compared with olive oil and palmitic linoleic hydroxyl glycerol (PLH), only PLAG effectively mitigated 5-FU-induced hematological toxicity, indicating that it has a distinctive mechanism of action. In conclusion, PLAG may have therapeutic potential as a mitigator for 5-FU-induced neutropenia and other hematological disorders.