Although early antimicrobial discontinuation guided by procalcitonin (PCT) has shown decreased antibiotic consumption in lower respiratory tract infections, the outcomes in long-term sepsis sequelae ...remain unclear.
To investigate if PCT guidance may reduce the incidence of long-term infection-associated adverse events in sepsis.
In this multicenter trial, 266 patients with sepsis (by Sepsis-3 definitions) with lower respiratory tract infections, acute pyelonephritis, or primary bloodstream infection were randomized (1:1) to receive either PCT-guided discontinuation of antimicrobials or standard of care. The discontinuation criterion was ≥80% reduction in PCT levels or any PCT ≤0.5 μg/L at Day 5 or later. The primary outcome was the rate of infection-associated adverse events at Day 180, a composite of the incidence of any new infection by
or multidrug-resistant organisms, or any death attributed to baseline
or multidrug-resistant organism infection. Secondary outcomes included 28-day mortality, length of antibiotic therapy, and cost of hospitalization.
The rate of infection-associated adverse events was 7.2% (95% confidence interval CI, 3.8-13.1%; 9/125) versus 15.3% (95% CI, 10.1-22.4%; 20/131) (hazard ratio, 0.45; 95% CI, 0.20-0.98;
= 0.045); 28-day mortality 15.2% (95% CI, 10-22.5%; 19/125) versus 28.2% (95% CI, 21.2-36.5%; 37/131) (hazard ratio, 0.51; 95% CI, 0.29-0.89;
= 0.02); and median length of antibiotic therapy 5 (range, 5-7) versus 10 (range, 7-15) days (
< 0.001) in the PCT and standard-of-care arms, respectively. The cost of hospitalization was also reduced in the PCT arm.
In sepsis, PCT guidance was effective in reducing infection-associated adverse events, 28-day mortality, and cost of hospitalization.Clinical trial registered with www.clinicaltrials.gov (NCT03333304).
Recent publications on the probable role of heparin-binding protein (HBP) as a biomarker in sepsis prompted us to investigate its diagnostic and prognostic performance in severe COVID-19. HBP and ...IL-6 were measured by immunoassays at admission and on day 7 in 178 patients with pneumonia by SARS-CoV-2. Patients were classified into non-sepsis and sepsis as per the Sepsis-3 definitions and were followed up for the development of severe respiratory failure (SRF) and for outcome. Results were confirmed by multivariate analyses. HBP was significantly higher in patients classified as having sepsis and was negatively associated with the oxygenation ratio and positively associated with creatinine and lactate. Logistic regression analysis evidenced admission HBP more than 18 ng/ml and IL-6 more than 30 pg/ml as independent risk factors for the development of SRP. Their integration prognosticated SRF with respective sensitivity, specificity, positive predictive value, and negative predictive 59.1%, 96.3%, 83.9%, and 87.8%. Cox regression analysis evidenced admission HBP more than 35 ng/ml and IL-6 more than 30 pg/ml as independent risk factors for 28-day mortality. Their integration prognosticated 28-day mortality with respective sensitivity, specificity, positive predictive value, and negative predictive value 69.2%, 92.7%, 42.9%, and 97.5%. HBP remained unchanged over-time course. A prediction score of the disposition of patients with COVID-19 is proposed taking into consideration admission levels of IL-6 and HBP. Using different cut-offs, the score may predict the likelihood for SRF and for 28-day outcome.
Abstract
Background
Clarithromycin may act as immune-regulating treatment in sepsis and acute respiratory dysfunction syndrome. However, clinical evidence remains inconclusive. We aimed to evaluate ...whether clarithromycin improves 28-day mortality among patients with sepsis, respiratory and multiple organ dysfunction syndrome.
Methods
We conducted a multicenter, randomized, clinical trial in patients with sepsis. Participants with ratio of partial oxygen pressure to fraction of inspired oxygen less than 200 and more than 3 SOFA points from systems other than the respiratory function were enrolled between December 2017 and September 2019. Patients were randomized to receive 1 gr of clarithromycin or placebo intravenously once daily for 4 consecutive days. The primary endpoint was 28-day all-cause mortality. Secondary outcomes were 90-day mortality; sepsis response (defined as at least 25% decrease in SOFA score by day 7); sepsis recurrence; and differences in peripheral blood cell populations and leukocyte transcriptomics.
Results
Fifty-five patients were allocated to each arm. By day 28, 27 (49.1%) patients in the clarithromycin and 25 (45.5%) in the placebo group died (risk difference 3.6% 95% confidence interval (CI) − 15.7 to 22.7;
P
= 0.703, adjusted OR 1.03 95%CI 0.35–3.06;
P
= 0.959). There were no statistical differences in 90-day mortality and sepsis response. Clarithromycin was associated with lower incidence of sepsis recurrence (OR 0.21 95%CI 0.06–0.68;
P
= 0.012); significant increase in monocyte HLA-DR expression; expansion of non-classical monocytes; and upregulation of genes involved in cholesterol homeostasis. Serious and non-serious adverse events were equally distributed.
Conclusions
Clarithromycin did not reduce mortality among patients with sepsis with respiratory and multiple organ dysfunction. Clarithromycin was associated with lower sepsis recurrence, possibly through a mechanism of immune restoration.
Clinical trial registration
clinicaltrials.gov identifier
NCT03345992
registered 17 November 2017; EudraCT 2017-001056-55.
In the era of increasing antimicrobial resistance, the need for early identification and prompt treatment of multi-drug-resistant infections is crucial for achieving favorable outcomes in critically ...ill patients. As traditional microbiological susceptibility testing requires at least 24 hours, automated machine learning (AutoML) techniques could be used as clinical decision support tools to predict antimicrobial resistance and select appropriate empirical antibiotic treatment.
An antimicrobial susceptibility dataset of 11,496 instances from 499 patients admitted to the internal medicine wards of a public hospital in Greece was processed by using Microsoft Azure AutoML to evaluate antibiotic susceptibility predictions using patients' simple demographic characteristics, as well as previous antibiotic susceptibility testing, without any concomitant clinical data. Furthermore, the balanced dataset was also processed using the same procedure. The datasets contained the attributes of sex, age, sample type, Gram stain, 44 antimicrobial substances, and the antibiotic susceptibility results.
The stack ensemble technique achieved the best results in the original and balanced dataset with an area under the curve-weighted metric of 0.822 and 0.850, respectively.
Implementation of AutoML for antimicrobial susceptibility data can provide clinicians useful information regarding possible antibiotic resistance and aid them in selecting appropriate empirical antibiotic therapy by taking into consideration the local antimicrobial resistance ecosystem.
Hospital-acquired infections, particularly in the critical care setting, have become increasingly common during the last decade, with Gram-negative bacterial infections presenting the highest ...incidence among them. Multi-drug-resistant (MDR) Gram-negative infections are associated with high morbidity and mortality with significant direct and indirect costs resulting from long hospitalization due to antibiotic failure. Time is critical to identifying bacteria and their resistance to antibiotics due to the critical health status of patients in the intensive care unit (ICU). As common antibiotic resistance tests require more than 24 h after the sample is collected to determine sensitivity in specific antibiotics, we suggest applying machine learning (ML) techniques to assist the clinician in determining whether bacteria are resistant to individual antimicrobials by knowing only a sample's Gram stain, site of infection, and patient demographics. In our single center study, we compared the performance of eight machine learning algorithms to assess antibiotic susceptibility predictions. The demographic characteristics of the patients are considered for this study, as well as data from cultures and susceptibility testing. Applying machine learning algorithms to patient antimicrobial susceptibility data, readily available, solely from the Microbiology Laboratory without any of the patient's clinical data, even in resource-limited hospital settings, can provide informative antibiotic susceptibility predictions to aid clinicians in selecting appropriate empirical antibiotic therapy. These strategies, when used as a decision support tool, have the potential to improve empiric therapy selection and reduce the antimicrobial resistance burden.
BACKGROUNDEvidence on the changes in the absolute counts of monocyte subpopulations in sepsis is missing.METHODSFirstly, absolute counts of circulating CD14pos/HLA-DRpos/CD45pos monocytes were ...measured by flow cytometry in 70 patients with Gram-negative sepsis and in 10 healthy volunteers. In the second phase, immunophenotyping was performed and the absolute count of circulating inflammatory monocytes and of circulating CD14dim/CD16pos/CD45pos patrolling monocytes were measured in another 55 patients and 10 healthy volunteers. Measurements were repeated on days 3, 7, and 10. Results were correlated with survival after 28 days.RESULTSGreater numbers of CD14pos/HLA-DRpos/CD45pos monocytes were found on day 1 in survivors compared to nonsurvivors (p = 0.030). Receiver operating characteristic (ROC) analysis showed that a cutoff higher than 337 cells/mm3 on day 1 could discriminate between survivors and nonsurvivors with a positive predictive value (PPV) of 91.1%. Logistic regression including Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation (APACHE) II score showed that an absolute count greater than 337 cells/mm3 was independently associated with unfavorable outcome (odds ratio (OR) 0.19, p = 0.050). The absolute counts of inflammatory and of CD14dim/CD16pos/CD45pos monocytes were greater in patients than healthy controls during the entire 10 days of follow-up. The absolute counts on day 3 of CD14dim/CD16pos/CD45pos monocytes were greater in survivors than nonsurvivors (p = 0.027). ROC analysis revealed that the cutoff at 27 cells/mm3 could discriminate between survivors and nonsurvivors with PPV of 94.1%. Logistic regression including age, SOFA score, and APACHE II score showed that an absolute count greater than 27 cells/mm3 was independently associated with unfavorable outcome (OR 0.06, p = 0.033). Logistic regression analysis showed that intra-abdominal infection on day 1 was predictive of low CD14dim/ CD16pos/CD45pos count on day 3.CONCLUSIONCirculating counts of inflammatory and patrolling monocytes are greatly increased in Gram-negative sepsis. Absolute counts of CD14pos/HLA-DRpos/CD45pos monocytes on day 1 and CD14dim/CD16pos/CD45pos monocytes on day 3 are independently associated with final outcome.TRIAL REGISTRATIONClinicalTrials.gov, NCT01223690 . Registered retrospectively on 18 October 2010.
In light of the accumulating evidence on the negative predictive value of soluble urokinase plasminogen activator receptor (suPAR), a group of experts from the fields of intensive care medicine, ...emergency medicine, internal medicine and infectious diseases frame a position statement on the role of suPAR in the screening of patients admitted to the emergency department. The statement is framed taking into consideration existing publications and our own research experience. The main content of this statement is that sUPAR is a non-specific marker associated with a high negative predictive value for unfavourable outcomes; levels < 4 ng/ml indicate that it is safe to discharge the patient, whereas levels > 6 ng/ml are an alarming sign of risk for unfavourable outcomes. However, the suPAR levels should always be interpreted in light of the patient's history.
The correlation of Clostridium difficile infection (CDI) with in-hospital morbidity is important in hospital settings where broad-spectrum antimicrobial agents are routinely used, such as in Greece. ...The C. DEFINE study aimed to assess point-prevalence of CDI in Greece during two study periods in 2013.
There were two study periods consisting of a single day in March and another in October 2013. Stool samples from all patients hospitalized outside the ICU aged ≥18 years old with diarrhea on each day in 21 and 25 hospitals, respectively, were tested for CDI. Samples were tested for the presence of glutamate dehydrogenase antigen (GDH) and toxins A/B of C. difficile; samples positive for GDH and negative for toxins were further tested by culture and PCR for the presence of toxin genes. An analysis was performed to identify potential risk factors for CDI among patients with diarrhea.
5,536 and 6,523 patients were screened during the first and second study periods, respectively. The respective point-prevalence of CDI in all patients was 5.6 and 3.9 per 10,000 patient bed-days whereas the proportion of CDI among patients with diarrhea was 17% and 14.3%. Logistic regression analysis revealed that solid tumor malignancy odds ratio (OR) 2.69, 95% confidence interval (CI): 1.18-6.15, p = 0.019 and antimicrobial administration (OR 3.61, 95% CI: 1.03-12.76, p = 0.045) were independent risk factors for CDI development. Charlson's Comorbidity Index (CCI) >6 was also found as a risk factor of marginal statistical significance (OR 2.24, 95% CI: 0.98-5.10). Median time to CDI from hospital admission was shorter with the presence of solid tumor malignancy (3 vs 5 days; p = 0.002) and of CCI >6 (4 vs 6 days, p = 0.009).
The point-prevalence of CDI in Greek hospitals was consistent among cases of diarrhea over a 6-month period. Major risk factors were antimicrobial use, solid tumor malignancy and a CCI score >6.
The presence of human immunodeficiency virus type 1 (HIV-1) drug resistance among drug-naïve patients remains stable, although the proportion of patients with virological failure to therapy is ...decreasing. The dynamics of transmitted resistance among drug-naïve patients remains largely unknown. The prevalence of non-nucleoside reverse transcriptase inhibitors (NNRTI) resistance was 16.9% among treatment-naïve individuals in Greece. We aimed to investigate the transmission dynamics and the effective reproductive number (
) of the locally transmitted NNRTI resistance. We analyzed sequences with dominant NNRTI resistance mutations (E138A and K103N) found within monophyletic clusters (local transmission networks (LTNs)) from patients in Greece. For the K103N LTN, the
was >1 between 2008 and the first half of 2013. For all E138A LTNs, the
was >1 between 1998 and 2015, except the most recent one (E138A_4), where the
was >1 between 2006 and 2011 and approximately equal to 1 thereafter. K103N and E138A_4 showed similar characteristics with a more recent origin, higher
during the first years of the sub-epidemics, and a declining trend in the number of transmissions during the last two years. In the remaining LTNs the epidemic was still expanding. Our study highlights the added value of molecular epidemiology to public health.
The pneumonia of COVID-19 illness has often a subtle initial presentation making mandatory the use of biomarkers for evaluation of severity and prediction of final patient disposition. We evaluated ...the use of hydrogen sulfide (H2S) for the outcome of COVID-19 pneumonia.
We studied 74 patients with COVID-19. Clinical data were collected, and survival predictors were calculated. Blood was collected within 24 h after admission (day 1) and on day 7. H2S was measured in sera by monobromobimane derivation followed by high-performance liquid chromatography and correlated to other markers like procalcitonin and C-reactive protein (CRP). Tumor necrosis factor alpha and interleukin (IL)-6 were also measured in serum.
Survivors had significantly higher H2S levels on days 1 and 7 after admission. A cut-off point of 150.44 μM could discriminate survivors from non-survivors with 80% sensitivity, 73.4% specificity, and negative predictive value 95.9%. Mortality after 28 days was 32% with admission levels lower than or equal to 150.44 μM and 4.1% with levels above 150.44 μM (P: 0.0008). Mortality was significantly greater among patients with a decrease of H2S levels from day 1 to day 7 greater than or equal to 36% (p: 0.0005). Serum H2S on day 1 was negatively correlated with IL-6 and CRP and positively correlated with the absolute lymphocyte count in peripheral blood.
It is concluded that H2S is a potential marker for severity and final outcome of pneumonia by the SARS-CoV-2 coronavirus. Its correlation with IL-6 suggests anti-inflammatory properties.
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