Prolonged vs Intermittent Infusions of ß-Lactam Antibiotics in Adults With Sepsis or Septic Shock: A Systematic Review and Meta-Analysis.

Importance: There is uncertainty about whether prolonged infusions of ß-lactam antibiotics improve clinically important outcomes in critically ill adults with sepsis or septic shock. Objective: To determine whether prolonged ß-lactam antibiotic infusions are associated with a reduced risk of death in critically ill adults with sepsis or septic shock compared with intermittent infusions. Data Sources: The primary search was conducted with MEDLINE (via PubMed), CINAHL, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), and ClinicalTrials.gov from inception to May 2, 2024. Study Selection: Randomized clinical trials comparing prolonged (continuous or extended) and intermittent infusions of ß-lactam antibiotics in critically ill adults with sepsis or septic shock. Data Extraction and Synthesis: Data extraction and risk of bias were assessed independently by 2 reviewers. Certainty of evidence was evaluated with the Grading of Recommendations Assessment, Development and Evaluation approach. A bayesian framework was used as the primary analysis approach and a frequentist framework as the secondary approach. Main Outcomes and Measures: The primary outcome was all-cause 90-day mortality. Secondary outcomes included intensive care unit (ICU) mortality and clinical cure. Results: From 18 eligible randomized clinical trials that included 9108 critically ill adults with sepsis or septic shock (median age, 54 years; IQR, 48-57; 5961 men [65%]), 17 trials (9014 participants) contributed data to the primary outcome. The pooled estimated risk ratio for all-cause 90-day mortality for prolonged infusions of ß-lactam antibiotics compared with intermittent infusions was 0.86 (95% credible interval, 0.72-0.98; I2 = 21.5%; high certainty), with a 99.1% posterior probability that prolonged infusions were associated with lower 90-day mortality. Prolonged infusion of ß-lactam antibiotics was associated with a reduced risk of intensive care unit mortality (risk ratio, 0.84; 95% credible interval, 0.70-0.97; high certainty) and an increase in clinical cure (risk ratio, 1.16; 95% credible interval, 1.07-1.31; moderate certainty). Conclusions and Relevance: Among adults in the intensive care unit who had sepsis or septic shock, the use of prolonged ß-lactam antibiotic infusions was associated with a reduced risk of 90-day mortality compared with intermittent infusions. The current evidence presents a high degree of certainty for clinicians to consider prolonged infusions as a standard of care in the management of sepsis and septic shock. Trial Registration: PROSPERO Identifier: CRD42023399434.

A Patient-Level Meta-Analysis of Intensive Glucose Control in Critically Ill Adults.

BACKGROUND: Whether intensive glucose control reduces mortality in critically ill patients remains uncertain. Patient-level meta-analyses can provide more precise estimates of treatment effects than are currently available. METHODS: We pooled individual patient data from randomized trials investigating intensive glucose control in critically ill adults. The primary outcome was in-hospital mortality. Secondary outcomes included survival to 90 days and time to live cessation of treatment with vasopressors or inotropes, mechanical ventilation, and newly commenced renal replacement. Severe hypoglycemia was a safety outcome. RESULTS: Of 38 eligible trials (n=29,537 participants), 20 (n=14,171 participants) provided individual patient data including in-hospital mortality status for 7059 and 7049 participants allocated to intensive and conventional glucose control, respectively. Of these 1930 (27.3%) and 1891 (26.8%) individuals assigned to intensive and conventional control, respectively, died (risk ratio, 1.02; 95% confidence interval [CI], 0.96 to 1.07; P=0.52; moderate certainty). There was no apparent heterogeneity of treatment effect on in-hospital mortality in any examined subgroups. Intensive glucose control increased the risk of severe hypoglycemia (risk ratio, 3.38; 95% CI, 2.99 to 3.83; P<0.0001). CONCLUSIONS: Intensive glucose control was not associated with reduced mortality risk but increased the risk of severe hypoglycemia. We did not identify a subgroup of patients in whom intensive glucose control was beneficial. (Funded by the Australian National Health and Medical Research Council and others; PROSPERO number CRD42021278869.).

Prediction of dementia risk from multimodal repeated measures: The added value of brain MRI biomarkers.

Abstract: The utility of brain magnetic resonance imaging (MRI) for predicting dementia is debated. We evaluated the added value of repeated brain MRI, including atrophy and cerebral small vessel disease markers, for dementia prediction. We conducted a landmark competing risk analysis in 1716 participants of the French population-based Three-City Study to predict the 5-year risk of dementia using repeated measures of 41 predictors till year 4 of follow-up. Brain MRI markers improved significantly the individual prediction of dementia after accounting for demographics, health measures, and repeated measures of cognition and functional dependency (area under the ROC curve [95% CI] improved from 0.80 [0.79 to 0.82] to 0.83 [0.81 to 0.84]). Nonetheless, accounting for the change over time through repeated MRIs had little impact on predictive abilities. These results highlight the importance of multimodal analysis to evaluate the added predictive abilities of repeated brain MRI for dementia and offer new insights into the predictive performances of various MRI markers. Highlights: We evaluated whether repeated brain volumes and cSVD markers improve dementia prediction.The 5-year prediction of dementia is slightly improved when considering brain MRI markers.Measures of hippocampus volume are the main MRI predictors of dementia.Adjusted on cognition, repeated MRI has poor added value over single MRI for dementia prediction.We utilized a longitudinal analysis that considers error-and-missing-prone predictors, and competing death.

Selective digestive tract decontamination in critically ill adults with acute brain injuries: a post hoc analysis of a randomized clinical trial.

PURPOSE: The aim of this study was to determine whether selective decontamination of the digestive tract (SDD) reduces in-hospital mortality in mechanically ventilated critically ill adults admitted to the intensive care unit (ICU) with acute brain injuries or conditions. METHODS: We carried out a post hoc analysis from a crossover, cluster randomized clinical trial. ICUs were randomly assigned to adopt or not to adopt a SDD strategy for two alternating 12-month periods, separated by a 3-month inter-period gap. Patients in the SDD group (n = 2791; 968 admitted to the ICU with an acute brain injury) received a 6-hourly application of an oral paste and administration of a gastric suspension containing colistin, tobramycin, and nystatin for the duration of mechanical ventilation, plus a 4-day course of an intravenous antibiotic with a suitable antimicrobial spectrum. Patients in the control group (n = 3191; 1093 admitted to the ICU with an acute brain injury) received standard care. The primary outcome was in-hospital mortality within 90 days. There were four secondary clinical outcomes: death in ICU, ventilator-, ICU- and hospital-free days to day 90. RESULTS: Of 2061 patients with acute brain injuries (mean age, 55.8 years; 36.4% women), all completed the trial. In patients with acute brain injuries, there were 313/968 (32.3%) and 415/1093 (38%) in-hospital deaths in the SDD and standard care groups (unadjusted odds ratio [OR], 0.76, 95% confidence interval [CI] 0.63-0.92; p = 0.004). The use of SDD was associated with statistically significant improvements in the four clinical secondary outcomes compared to standard care. There was no significant heterogeneity of treatment effect between patients with and without acute brain injuries (interaction p = 0.22). CONCLUSIONS: In this post hoc analysis of a randomized clinical trial in critically ill patients with acute brain injuries receiving mechanical ventilation, the use of SDD significantly reduced in-hospital mortality in patients compared to standard care without SDD. These findings require confirmation.

Random survival forests with multivariate longitudinal endogenous covariates.

Predicting the individual risk of clinical events using the complete patient history is a major challenge in personalized medicine. Analytical methods have to account for a possibly large number of time-dependent predictors, which are often characterized by irregular and error-prone measurements, and are truncated early by the event. In this work, we extended the competing-risk random survival forests to handle such endogenous longitudinal predictors when predicting event probabilities. The method, implemented in the R package DynForest, internally transforms the time-dependent predictors at each node of each tree into time-fixed features (using mixed models) that can then be used as splitting candidates. The final individual event probability is computed as the average of leaf-specific Aalen-Johansen estimators over the trees. Using simulations, we compared the performances of DynForest to accurately predict an event with (i) a joint modeling alternative when considering two longitudinal predictors only, and with (ii) a regression calibration method that ignores the informative truncation by the event when dealing with a large number of longitudinal predictors. Through an application in dementia research, we also illustrated how DynForest can be used to develop a dynamic prediction tool for dementia from multimodal repeated markers, and quantify the importance of each marker.

Individual dynamic prediction of clinical endpoint from large dimensional longitudinal biomarker history: a landmark approach.

BACKGROUND: The individual data collected throughout patient follow-up constitute crucial information for assessing the risk of a clinical event, and eventually for adapting a therapeutic strategy. Joint models and landmark models have been proposed to compute individual dynamic predictions from repeated measures to one or two markers. However, they hardly extend to the case where the patient history includes much more repeated markers. Our objective was thus to propose a solution for the dynamic prediction of a health event that may exploit repeated measures of a possibly large number of markers. METHODS: We combined a landmark approach extended to endogenous markers history with machine learning methods adapted to survival data. Each marker trajectory is modeled using the information collected up to the landmark time, and summary variables that best capture the individual trajectories are derived. These summaries and additional covariates are then included in different prediction methods adapted to survival data, namely regularized regressions and random survival forests, to predict the event from the landmark time. We also show how predictive tools can be combined into a superlearner. The performances are evaluated by cross-validation using estimators of Brier Score and the area under the Receiver Operating Characteristic curve adapted to censored data. RESULTS: We demonstrate in a simulation study the benefits of machine learning survival methods over standard survival models, especially in the case of numerous and/or nonlinear relationships between the predictors and the event. We then applied the methodology in two prediction contexts: a clinical context with the prediction of death in primary biliary cholangitis, and a public health context with age-specific prediction of death in the general elderly population. CONCLUSIONS: Our methodology, implemented in R, enables the prediction of an event using the entire longitudinal patient history, even when the number of repeated markers is large. Although introduced with mixed models for the repeated markers and methods for a single right censored time-to-event, the technique can be used with any other appropriate modeling technique for the markers and can be easily extended to competing risks setting.

Human Campylobacteriosis in Luxembourg, 2010-2013: A Case-Control Study Combined with Multilocus Sequence Typing for Source Attribution and Risk Factor Analysis.

Campylobacteriosis has increased markedly in Luxembourg during recent years. We sought to determine which Campylobacter genotypes infect humans, where they may originate from, and how they may infect humans. Multilocus sequence typing was performed on 1153 Campylobacter jejuni and 136 C. coli human strains to be attributed to three putative animal reservoirs (poultry, ruminants, pigs) and to environmental water using the asymmetric island model. A nationwide case-control study (2010-2013) for domestic campylobacteriosis was also conducted, including 367 C. jejuni and 48 C. coli cases, and 624 controls. Risk factors were investigated by Campylobacter species, and for strains attributed to different sources using a combined case-control and source attribution analysis. 282 sequence types (STs) were identified: ST-21, ST-48, ST-572, ST-50 and ST-257 were prevailing. Most cases were attributed to poultry (61.2%) and ruminants (33.3%). Consuming chicken outside the home was the dominant risk factor for both Campylobacter species. Newly identified risk factors included contact with garden soil for either species, and consuming beef specifically for C. coli. Poultry-associated campylobacteriosis was linked to poultry consumption in wintertime, and ruminant-associated campylobacteriosis to tap-water provider type. Besides confirming chicken as campylobacteriosis primary source, additional evidence was found for other reservoirs and transmission routes.

Investigating the host specificity of Campylobacter jejuni and Campylobacter coli by sequencing gyrase subunit A.

BACKGROUND: Surveillance and field investigations of Campylobacter infections require molecular tools with genetic markers appropriate for tracing purposes, i.e. based on the principle that some Campylobacter lineages acquire a host signature under adaptive selection pressure. We developed a sequence-based method targeting the quinolone resistance determining region within the subunit A of DNA gyrase (gyrA). Host specificity was evaluated by characterizing two collections of Campylobacter jejuni (N = 430) and Campylobacter coli (N = 302) originating from surface waters, domestic mammals and poultry. RESULTS: Based on nucleotide identity, a total of 80 gyrA alleles were observed. Thirty nine alleles assigned to C. coli encoding two peptides fell into three clades: two associated with surface waters and one associated with domestic mammals and poultry. The variability in GC content generated by synonymous mutations suggested that surface waters isolates originated from two distinct ecological niches. A total of 42 alleles were recorded from C. jejuni strains and encoded 8 peptides including one lying in a distinct lineage associated with wildlife. Seven of the 23 alleles encoding peptide #1 displayed the synonymous mutation G408A not identified in poultry isolates. By contrast, the substitution Ser22Gly observed in 4 different peptide groups was significantly associated with domestic birds (P = 0.001). The change in amino acid sequences Thr86Ile conferring resistance to quinolones was significantly associated with poultry (P < 0.001) in both C. jejuni and C. coli with 38.7% and 67.9% of quinolone-resistant strains, respectively. CONCLUSIONS: The gyrA typing method presented here is an informative tool as sequences appear to be predictive of particular ecological niches. Combined with multi-locus sequence typing, it could increase the resolution of source attribution, and combined with porA/flaA typing it could be suitable for detecting temporal clusters of human cases. All gyrA alleles identified were deposited in the freely accessible online database http://pubmlst.org/campylobacter.