The critically ill polytrauma patient presents with a series of associated pathophysiologies secondary to the traumatic injuries. The most important include systemic inflammatory response syndrome (SIRS), sepsis, oxidative stress (OS), metabolic disorders, and finally multiple organ dysfunction syndrome (MODS) and death. The poor outcome of these patients is related to the association of the aforementioned pathologies. The nutrition of the critically ill polytrauma patient is a distinct challenge because of the rapid changes in terms of energetic needs associated with hypermetabolism, sepsis, SIRS, and OS. Moreover, it has been proven that inadequate nutrition can prolong the time spent on a mechanical ventilator and the length of stay in an intensive care unit (ICU). A series of mathematical equations can predict the energy expenditure (EE), but they have disadvantages, such as the fact that they cannot predict the EE accurately in the case of patients with hypermetabolism. Indirect calorimetry (IC) is another method used for evaluating and monitoring the energy status of critically ill patients. In this update paper, we present a series of pathophysiological aspects associated with the metabolic disaster affecting the critically ill polytrauma patient. Furthermore, we present different non-invasive monitoring methods that could help the intensive care physician in the adequate management of this type of patient.

Over recent decades, a dramatic increase in infections caused by multidrug-resistant pathogens has been observed worldwide. The aim of the present study was to investigate the relationship between local resistance bacterial patterns and antibiotic consumption in an intensive care unit in a Romanian university hospital. A prospective study was conducted between 1st January 2012 and 31st December 2013. Data covering the consumption of antibacterial drugs and the incidence density for the main resistance phenotypes was collected on a monthly basis, and this data was aggregated quarterly. The relationship between the antibiotic consumption and resistance was investigated using cross-correlation, and four regression models were constructed, using the SPSS version 20.0 (IBM, Chicago, IL) and the R version 3.2.3 packages. During the period studied, the incidence of combined-resistant and carbapenem-resistant P. aeruginosa strains increased significantly [(gradient = 0.78, R2 = 0.707, p = 0.009) (gradient = 0.74, R2 = 0.666, p = 0.013) respectively], mirroring the increase in consumption of β-lactam antibiotics with β-lactamase inhibitors (piperacillin/tazobactam) and carbapenems (meropenem) [(gradient = 10.91, R2 = 0.698, p = 0.010) and (gradient = 14.63, R2 = 0.753, p = 0.005) respectively]. The highest cross-correlation coefficients for zero time lags were found between combined-resistant vs. penicillins consumption and carbapenem-resistant P. aeruginosa strains vs. carbapenems consumption (0.876 and 0.928, respectively). The best model describing the relation between combined-resistant P. aeruginosa strains and penicillins consumption during a given quarter incorporates both the consumption and the incidence of combined-resistant strains in the hospital department during the previous quarter (multiple R2 = 0.953, p = 0.017). The best model for explaining the carbapenem resistance of P. aeruginosa strains based on meropenem consumption during a given quarter proved to be the adjusted model which takes into consideration both previous consumption and incidence density of strains during the previous quarter (Multiple R2 = 0.921, p = 0.037). The cross-correlation coefficients and the fitted regression models provide additional evidence that resistance during the a given quarter depends not only on the consumption of antibacterial chemotherapeutic drugs in both that quarter and the previous one, but also on the incidence of resistant strains circulating during the previous quarter.

Due to the vulnerable nature of its patients, the wide use of invasive devices and broad-spectrum antimicrobials used, the intensive care unit (ICU) is often called the epicentre of infections. In the present study, we quantified the burden of hospital acquired pathology in a Romanian university hospital ICU, represented by antimicrobial agents consumption, costs and local resistance patterns, in order to identify multimodal interventional strategies. Between 1st January 2012 and 31st December 2013, a prospective study was conducted in the largest ICU of Western Romania. The study group was divided into four sub-samples: patients who only received prophylactic antibiotherapy, those with community-acquired infections, patients who developed hospital acquired infections and patients with community acquired infections complicated by hospital-acquired infections. The statistical analysis was performed using the EpiInfo version 3.5.4 and SPSS version 20. A total of 1596 subjects were enrolled in the study and the recorded consumption of antimicrobial agents was 1172.40 DDD/ 1000 patient-days. The presence of hospital acquired infections doubled the length of stay (6.70 days for patients with community-acquired infections versus 16.06/14.08 days for those with hospital-acquired infections), the number of antimicrobial treatment days (5.47 in sub-sample II versus 11.18/12.13 in sub-samples III/IV) and they increased by 4 times compared to uninfected patients. The perioperative prophylactic antibiotic treatment had an average length duration of 2.78 while the empirical antimicrobial therapy was 3.96 days in sample II and 4.75/4.85 days for the patients with hospital-acquired infections. The incidence density of resistant strains was 8.27/1000 patient-days for methicilin resistant Staphylococcus aureus, 7.88 for extended spectrum β-lactamase producing Klebsiella pneumoniae and 4.68/1000 patient-days for multidrug resistant Acinetobacter baumannii. Some of the most important circumstances collectively contributing to increasing the consumption of antimicrobials and high incidence densities of multidrug-resistant bacteria in the studied ICU, are represented by prolonged chemoprophylaxis and empirical treatment and also by not applying the definitive antimicrobial therapy, especially in patients with favourable evolution under empirical antibiotic treatment. The present data should represent convincing evidence for policy changes in the antibiotic therapy.

Background: Heart failure (HF), chronic kidney disease (CKD), and atrial fibrillation (AF) frequently coexist, forming a high-risk triad that amplifies morbidity and mortality through shared pathophysiological mechanisms such as neurohormonal activation, fluid overload, and inflammation. Current risk stratification tools, including CHA₂DS₂-VASc and HAS-BLED, inadequately capture the complexity of these multimorbid patients. This study aims to explore the influence of comorbidities, hypertension severity, anticoagulation strategy, and risk scores on hospitalization outcomes in patients with coexisting HF, CKD, and AF. Materials and Methods: A retrospective case study was conducted on 174 hospitalized patients with HF, CKD, and AF. Clinical data included hypertension grade, HF phenotype (HFpEF vs. HFrEF), NYHA classification, renal function (KDIGO stage), stroke and bleeding risk scores (CHA₂DS₂-VASc: congestive heart failure, hypertension, age ≥ 75, diabetes, and stroke/TIA; HAS-BLED: hypertension, abnormal renal/liver function, stroke, bleeding, labile INR, elderly, and drugs/alcohol), comorbidities (neurological, psychiatric, COPD, and diabetes), anticoagulation type (DOACs vs. VKAs), and length of hospital stay. Statistical analysis included Spearman correlation, independent t-tests, and multivariate regression to evaluate associations between variables and clinical outcomes. Results: Most patients were elderly (mean age 75 ± 12), with advanced CKD (stage 3b) and systolic HF (77% HFrEF). Mean CHA₂DS₂-VASc was 5.67, HAS-BLED was 4.40, and ATRIA was 4.74, indicating high stroke and bleeding risk. Anticoagulation was predominantly via DOACs (69.5%). Hypertension severity did not significantly correlate with NYHA class (ρ = −0.14, p = 0.068). Neurological, psychiatric, and metabolic comorbidities showed no significant associations with HF severity. COPD and diabetes correlated inversely with CHA₂DS₂-VASc scores (ρ = −0.83, p = 0.014). No significant differences were observed in hospital stay between HF phenotypes or prior stroke history. In-hospital mortality was low (2.3%). Conclusions: Traditional risk scores do not fully capture the complexity of multimorbid patients. Metabolic comorbidities showed an inverse correlation with stroke risk scores, and no significant correlation was observed between hypertension severity and HF symptom burden. Hypertension and common comorbidities did not correlate with HF symptom burden, and metabolic diseases may paradoxically associate with lower stroke risk scores. These findings highlight the need for improved multimodal risk assessment strategies that consider the heterogeneity of multimorbid populations. Personalized, integrated approaches are essential to optimize anticoagulation, reduce hospitalization, and improve prognosis.

The development of general anesthesia techniques and anesthetic substances has opened new horizons for the expansion and improvement of surgical techniques. Nevertheless, more complex surgical procedures have brought a higher complexity and longer duration for general anesthesia, which has led to a series of adverse events such as hemodynamic instability, under- or overdosage of anesthetic drugs, and an increased number of post-anesthetic events. In order to adapt the anesthesia according to the particularities of each patient, the multimodal monitoring of these patients is highly recommended. Classically, general anesthesia monitoring consists of the analysis of vital functions and gas exchange. Multimodal monitoring refers to the concomitant monitoring of the degree of hypnosis and the nociceptive-antinociceptive balance. By titrating anesthetic drugs according to these parameters, clinical benefits can be obtained, such as hemodynamic stabilization, the reduction of awakening times, and the reduction of postoperative complications. Another important aspect is the impact on the status of inflammation and the redox balance. By minimizing inflammatory and oxidative impact, a faster recovery can be achieved that increases patient safety. The purpose of this literature review is to present the most modern multimodal monitoring techniques to discuss the particularities of each technique.

A critically ill polytrauma patient is one of the most complex cases to be admitted to the intensive care unit, due to both the primary traumatic complications and the secondary post-traumatic interactions. From a molecular, genetic, and epigenetic point of view, numerous biochemical interactions are responsible for the deterioration of the clinical status of a patient, and increased mortality rates. From a molecular viewpoint, microRNAs are one of the most complex macromolecular systems due to the numerous modular reactions and interactions that they are involved in. Regarding the expression and activity of microRNAs in sepsis, their usefulness has reached new levels of significance. MicroRNAs can be used both as an early biomarker for sepsis, and as a therapeutic target because of their ability to block the complex reactions involved in the initiation, maintenance, and augmentation of the clinical status.