National ICU Registries as Enablers of Clinical Research and Quality Improvement.

OBJECTIVES: Clinical quality registries (CQRs) have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. This narrative review describes the challenges, proposed solutions, and evidence generated by National ICU registries as facilitators for research and quality improvement. DATA SOURCES: English language articles were identified in PubMed using phrases related to ICU registries, CQRs, outcomes, and case-mix. STUDY SELECTION: Original research, review articles, letters, and commentaries, were considered. DATA EXTRACTION: Data from relevant literature were identified, reviewed, and integrated into a concise narrative review. DATA SYNTHESIS: CQRs have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. The initial experience in European countries and in Oceania ensured that through locally generated data, ICUs could assess their performances by using risk-adjusted measures and compare their results through fair and validated benchmarking metrics with other ICUs contributing to the CQR. The accomplishment of these initiatives, coupled with the increasing adoption of information technology, resulted in a broad geographic expansion of CQRs as well as their use in quality improvement studies, clinical trials as well as international comparisons, and benchmarking for ICUs. CONCLUSIONS: ICU registries have provided increased knowledge of case-mix and outcomes of ICU patients based on real-world data and contributed to improve care delivery through quality improvement initiatives and trials. Recent increases in adoption of new technologies (i.e., cloud-based structures, artificial intelligence, machine learning) will ensure a broader and better use of data for epidemiology, healthcare policies, quality improvement, and clinical trials.

Development and external validation of a machine learning model for the prediction of persistent acute kidney injury stage 3 in multi-centric, multi-national intensive care cohorts.

BACKGROUND: The aim of this retrospective cohort study was to develop and validate on multiple international datasets a real-time machine learning model able to accurately predict persistent acute kidney injury (AKI) in the intensive care unit (ICU). METHODS: We selected adult patients admitted to ICU classified as AKI stage 2 or 3 as defined by the "Kidney Disease: Improving Global Outcomes" criteria. The primary endpoint was the ability to predict AKI stage 3 lasting for at least 72 h while in the ICU. An explainable tree regressor was trained and calibrated on two tertiary, urban, academic, single-center databases and externally validated on two multi-centers databases. RESULTS: A total of 7759 ICU patients were enrolled for analysis. The incidence of persistent stage 3 AKI varied from 11 to 6% in the development and internal validation cohorts, respectively and 19% in external validation cohorts. The model achieved area under the receiver operating characteristic curve of 0.94 (95% CI 0.92-0.95) in the US external validation cohort and 0.85 (95% CI 0.83-0.88) in the Italian external validation cohort. CONCLUSIONS: A machine learning approach fed with the proper data pipeline can accurately predict onset of Persistent AKI Stage 3 during ICU patient stay in retrospective, multi-centric and international datasets. This model has the potential to improve management of AKI episodes in ICU if implemented in clinical practice.

Parental practices that influence children's development: how often are they implemented and by whom-results from the NASCITA birth cohort study.

This study aims to assess how commonly 15 parental practices, known to have positive effects on child and adult health, are carried out by families in Italy, if they are related, and which characteristics are associated with implementation. Children participating in the NASCITA Cohort, a prospective study in which family pediatricians in Italy collect data on children and their families, were included if they had sufficient data. Data on practice implementation, socio-demographic characteristics, and interrelatedness between practices were analyzed. In all, 3337 children were included. Their mothers had an average age at birth of 33 years (range 17-52) and medium-high levels of education (86% of mothers) and employment (72%). No smoking or alcohol in pregnancy, supine infant sleeping position, and tummy time were the most commonly implemented practices (by over 85% of mothers, each), while the least common was exclusive breastfeeding at 6 months (28%). Parental practices are related and several socio-demographic characteristics influence their implementation, with mother's educational level and geographic area of residence influencing most of the practices (each influencing 12 of 15 practices). Low educational level (OR 0.34; 95% CI 0.26-0.44), being born abroad (OR 0.43; 95% CI 0.34-0.56), and residing in the South (OR 0.49; 95% CI 0.41-0.58) most reduce the probability of implementing numerous supportive practices (all three P < 0.001).    Conclusion: Socio-demographic factors contribute significantly to carrying out supportive practices. Future interventions should address the identified inequalities, prioritizing families most in need. Direct involvement of pediatricians is warranted given their favorable position for promoting positive behaviors. What is Known: • Several parental actions in the early life of a child are known to have positive effects on later child health and development. • While folic acid supplementation and exclusive breastfeeding have been promoted for years, other supporting actions are less well-known. What is New: • Rates of parental adherence to the different supportive actions varied greatly and actions were often scantly adopted. • Socio-demographic characteristics influenced adherence, with young, unemployed mothers with low educational levels, living in the South, or who were born abroad adhering significantly less.

Management and outcomes in critically ill nonagenarian versus octogenarian patients.

BACKGROUND: Intensive care unit (ICU) patients age 90 years or older represent a growing subgroup and place a huge financial burden on health care resources despite the benefit being unclear. This leads to ethical problems. The present investigation assessed the differences in outcome between nonagenarian and octogenarian ICU patients. METHODS: We included 7900 acutely admitted older critically ill patients from two large, multinational studies. The primary outcome was 30-day-mortality, and the secondary outcome was ICU-mortality. Baseline characteristics consisted of frailty assessed by the Clinical Frailty Scale (CFS), ICU-management, and outcomes were compared between octogenarian (80-89.9 years) and nonagenarian (> 90 years) patients. We used multilevel logistic regression to evaluate differences between octogenarians and nonagenarians. RESULTS: The nonagenarians were 10% of the entire cohort. They experienced a higher percentage of frailty (58% vs 42%; p < 0.001), but lower SOFA scores at admission (6 + 5 vs. 7 + 6; p < 0.001). ICU-management strategies were different. Octogenarians required higher rates of organ support and nonagenarians received higher rates of life-sustaining treatment limitations (40% vs. 33%; p < 0.001). ICU mortality was comparable (27% vs. 27%; p = 0.973) but a higher 30-day-mortality (45% vs. 40%; p = 0.029) was seen in the nonagenarians. After multivariable adjustment nonagenarians had no significantly increased risk for 30-day-mortality (aOR 1.25 (95% CI 0.90-1.74; p = 0.19)). CONCLUSION: After adjustment for confounders, nonagenarians demonstrated no higher 30-day mortality than octogenarian patients. In this study, being age 90 years or more is no particular risk factor for an adverse outcome. This should be considered- together with illness severity and pre-existing functional capacity - to effectively guide triage decisions. TRIAL REGISTRATION: NCT03134807 and NCT03370692 .

The Hematocrit Affects the Volume of Plasma Treated With Coupled Plasma Filtration and Adsorption With Predilution.

Coupled plasma filtration and adsorption (CPFA) is an extracorporeal blood purification technique proposed for the treatment of septic-shock. By removing pro- and anti-inflammatory mediators from plasma, CPFA is supposed to have a therapeutic effect on the abnormal inflammatory response seen in this condition. Recently, blood predilution with citrate solution has been adopted to prevent clotting in the CPFA circuit-one of the main problems of the technique. Taking into account the patient's hematocrit, we worked out a formula for the volume of plasma effectively treated by CPFA after predilution. Neglecting this effect, as is commonly done, introduces significant distortions in the estimation of the volume, possibly causing under-treatment. The distortion is stronger when the hematocrit and the predilution fraction are large and weaker when both values shrink. By correctly indicating the daily dose of plasma adsorption received by patients, this formula is essential for assessing the therapeutic efficacy of CPFA and, subsequently, establishing its optimal doses.

A new test and graphical tool to assess the goodness of fit of logistic regression models.

A prognostic model is well calibrated when it accurately predicts event rates. This is first determined by testing for goodness of fit with the development dataset. All existing tests and graphic tools designed for the purpose suffer several drawbacks, related mainly to the subgrouping of observations or to heavy dependence on arbitrary parameters. We propose a statistical test and a graphical method to assess the goodness of fit of logistic regression models, obtained through an extension of similar techniques developed for external validation. We analytically computed and numerically verified the distribution of the underlying statistic. Simulations on a set of realistic scenarios show that this test and the well-known Hosmer-Lemeshow approach have similar type I error rates. The main advantage of this new approach is that the relationship between model predictions and outcome rates across the range of probabilities can be represented in the calibration belt plot, together with its statistical confidence. By readily spotting any deviations from the perfect fit, this new graphical tool is designed to identify, during the process of model development, poorly modeled variables that call for further investigation. This is illustrated through an example based on real data.

A new calibration test and a reappraisal of the calibration belt for the assessment of prediction models based on dichotomous outcomes.

Calibration is one of the main properties that must be accomplished by any predictive model. Overcoming the limitations of many approaches developed so far, a study has recently proposed the calibration belt as a graphical tool to identify ranges of probability where a model based on dichotomous outcomes miscalibrates. In this new approach, the relation between the logits of the probability predicted by a model and of the event rates observed in a sample is represented by a polynomial function, whose coefficients are fitted and its degree is fixed by a series of likelihood-ratio tests. We propose here a test associated with the calibration belt and show how the algorithm to select the polynomial degree affects the distribution of the test statistic. We calculate its exact distribution and confirm its validity via a numerical simulation. Starting from this distribution, we finally reappraise the procedure to construct the calibration belt and illustrate an application in the medical context.

Cardiogenic shock in general intensive care unit: a Nationwide prospective analysis of epidemiology and outcome.

BACKGROUND: Cardiogenic shock (CS) is a life-threatening disease burdened by a mortality up to 50%. The epidemiology has changed with non-ischemic aetiologies being predominant although data was mainly derived from patients admitted to dedicated acute cardiac care. We report the epidemiology and outcome of patients with CS admitted to general intensive care unit (ICU). METHODS: Prospective multicentric epidemiological study including 314 general ICU adhering to the GiViTI Nationwide registry from 2011 to 2018, excluding cardiac arrest. The primary endpoint of the study was mortality. The association between clinical factors and mortality was evaluated using a logistic regression model. The Odds Ratios of the covariates quantify their association with mortality during hospitalization. RESULTS: 11052 patients admitted to general ICU (incidence 2.17%; median age 72 (IQR [66-81]), 38.7% were women) with CS were included. Fourthy-seven percent of patients had more than 3 organ insufficiency at the time of admission. The most common CS aetiologies were: left heart failure LHF- 5247-47.5%), acute myocardial infarction (AMI - 3612-32.6%); right heart failure (RHF- 515-4.6%) and biventricular failure (532- 4.8%). 85.5% were mechanically ventilated during the ICU hospitalization. The overall ICU mortality was 44.8%, increasing to 53.4% during the hospitalization in the index hospital and to 54.3% at the latest hospital. RHF-CS patients exhibited the highest mortality risk (OR: 1.19 95% CI [0.94 - 1.50]; p < 0.001), followed by biventricular-CS OR 1.04 95% CI [0.82-1.32]. Respiratory failure (OR 1.13 [95%CI 1.08-1.19]), coagulation disorder (1.17 (95% CI 1.1-1.24), renal dysfunction (OR 1.55 [95% CI 1.50-1.61] and neurological alteration (OR 1.45 [95% CI 1.39-1.50]) were associated with worsen outcome along with severe hypotension (systolic blood pressure < 70 mmHg- OR 2.35 95% CI [2.06-2.67]), increasing age (OR 2.21 95% CI [2.01-2.42] and longer ICU stay prior to admission (2-fold increase for each 4.7 days). CONCLUSIONS: In the general ICU the aetiology of CS, excluding cardiac arrest, remains characterized mostly by LHF with RHF-CS burdened by higher mortality. Multiorgan failure at admission and longer hospital stay before ICU admission predispose to worsen outcome.

Cardiogenic shock diagnosis and management in general intensive care: a nationwide survey.

BACKGROUND: the epidemiology of cardiogenic shock has evolved over the years: in the last decades an increasing prevalence of cardiogenic shock related to acute decompensated heart failure was observed. Therefore, treatment bundles should be updated according to the underlying pathophysiology. No data exist regarding the diagnostic/therapeutic strategies in general intensive care units. METHODS: A 27-questions survey was spread through the GiViTi (Italian Group for the Evaluation of Interventions in Intensive Care Medicine). The results were then divided according to level of hospitals (1st-2nd versus 3rd). RESULTS: Sixty-nine general intensive care units replied to the survey. The shock team is present in 13% of institutions; Society for Cardiovascular Angiography and Interventions shock classification is applied only in 18.8%. Among the ICUs, 94.2% routinely use a cardiac output monitoring device (pulmonary artery catheter more frequently in 3rd level centers). The first-line adrenergic drug are vasopressors in 27.5%, inotrope in 21.7% or their combination in 50.7%; 79.7% applies fluid challenge. The first vasopressor of choice is norepinephrine (95.7%) (maximum dosage tolerated higher than 0.5 mcg/kg/min in 29%); the first line inotrope is dobutamine (52.2%), followed by epinephrine in 36.2%. The most frequently used mechanical circulatory supports are intra-aortic balloon pump (71%), Impella (34.8%) and VA-ECMO (33.3%); VA-ECMO is the first line strategy in refractory cardiogenic shock (60.8%). CONCLUSIONS: According to this survey, there is no standardized approach to cardiogenic shock amongst Italian general intensive care units. The application of shock severity stratification and the treatment bundles may play a key role in improving the outcome.

Understanding the burden of antibiotic resistance: a decade of carbapenem-resistant Gram-negative bacterial infections in Italian intensive care units.

Introduction: In patients admitted to intensive care units (ICUs), Gram-negative bacteria (GNB) infections pose significant challenges due to their contribution to morbidity, mortality, and healthcare costs. During the SARS-CoV-2 pandemic, Italy witnessed a rise in healthcare-associated infections (HAIs), with GNBs involved in a substantial proportion of cases. Concerningly, carbapenem-resistant GNBs (CR-GNBs) have increased worldwide, posing therapeutic challenges. Methods: Retrospective multicentre study analysing data from over 299,000 patients admitted to Italian ICUs from 2013 to 2022. Results: The study revealed an average of 1.5 infections per patient, with HAIs peaking during the pandemic years. Ventilator associated pneumonia (VAP) emerged as the most common HAI, with Klebsiella spp. and Pseudomonas aeruginosa predominating. Alarmingly, CR-GNBs accounted for a significant proportion of infections, particularly in VAP, bloodstream infections, and intra-abdominal infections. Discussion: Our findings underscore the pressing need for enhanced infection control measures, particularly in the ICU setting, to mitigate the rising prevalence of CR-GNBs and their impact on patient outcomes. The study provides valuable insights into the epidemiology of HAIs in Italian ICUs and highlights the challenges posed by CR-GNBs, especially in the context of the SARS-CoV-2 pandemic, which exacerbated the issue and may serve as a crucial example for the management of future viral pandemics.

Differences between centers in functional outcome of patients with ADHD after 1 year from the time of diagnosis.

Although the pharmacological therapy of ADHD has been widely studied, little has been done to compare the different therapeutic approaches (e.g., drug therapy vs. psychological treatments) and even less has been done to compare the outcome of the therapy between centers. This multicenter observational study aims to assess between-center variation in functional outcome of ADHD patients one year after the diagnosis, according to the treatment received. We used the Regional ADHD Registry data on 1429 patients enrolled in 16 ADHD centers in the 2011-2022 period. To evaluate the effectiveness of the therapy we used a generalized linear mixed model with the center as the random effect, including patient condition at diagnosis and center characteristics, weighting by the inverse of the propensity score of the treatment received by the patient. Between-center variation was expressed as the relative difference in odds-ratios between the observed and the expected number of patients whose condition improved, using the Clinical Global Impressions-Improvement Scale (CGI-I), and the relative 95% CI. Patients who received combined treatment were significantly more likely to improve compared to other treatment groups (65.5% vs 54.4% for methylphenidate alone, 53.4% for psychological treatment alone, or 40.5% for no therapy). Adjusted for patients and center characteristics, the log-odds ratio ranged from 0.85 (0.29-1.55 95% CI) to - 0.64 (- 1.17-- 0.18 95% CI). The mean expected probability of improvement after one year of therapy for an average patient with ADHD for each center was 47.7% in a center at the 25th percentile and 61.2% in a center at the 75th percentile of the outcome distribution after adjustments. The wide between-center variation in patient functional improvement one year after the diagnosis of ADHD could be largely explained by center-specific therapeutic approaches or attitudes. More careful and stringent work is needed to reduce differences in responses between centers, as could formal and periodic audit programs within and between centers.

Continuous and early prediction of future moderate and severe Acute Kidney Injury in critically ill patients: Development and multi-centric, multi-national external validation of a machine-learning model.

BACKGROUND: Acute Kidney Injury (AKI) is a major complication in patients admitted to Intensive Care Units (ICU), causing both clinical and economic burden on the healthcare system. This study develops a novel machine-learning (ML) model to predict, with several hours in advance, the AKI episodes of stage 2 and 3 (according to KDIGO definition) acquired in ICU. METHODS: A total of 16'760 ICU adult patients from 145 different ICU centers and 3 different countries (US, Netherland, Italy) are retrospectively enrolled for the study. Every hour the model continuously analyzes the routinely-collected clinical data to generate a new probability of developing AKI stage 2 and 3, according to KDIGO definition, during the ICU stay. RESULTS: The predictive model obtains an auROC of 0.884 for AKI (stage 2/3 KDIGO) prediction, when evaluated on the internal test set composed by 1'749 ICU stays from US and EU centers. When externally tested on a multi-centric US dataset of 6'985 ICU stays and multi-centric Italian dataset of 1'025 ICU stays, the model achieves an auROC of 0.877 and of 0.911, respectively. In all datasets, the time between model prediction and AKI (stage 2/3 KDIGO) onset is at least of 14 hours after the first day of ICU hospitalization. CONCLUSIONS: In this study, a novel ML model for continuous and early AKI (stage 2/3 KDIGO) prediction is successfully developed, leveraging only routinely-available data. It continuously predicts AKI episodes during ICU stay, at least 14 hours in advance when the AKI episode happens after the first 24 hours of ICU admission. Its performances are validated in an extensive, multi-national and multi-centric cohort of ICU adult patients. This ML model overcomes the main limitations of currently available predictive models. The benefits of its real-world implementation enable an early proactive clinical management and the prevention of AKI episodes in ICU patients. Furthermore, the software could be directly integrated with IT system of the ICU.

Organizational Learning in Healthcare Contexts after COVID-19: A Study of 10 Intensive Care Units in Central and Northern Italy through Framework Analysis.

The rapid spread of the SARS-CoV-2 virus has forced healthcare organizations to change their organization, introducing new ways of working, relating, communicating, and managing to cope with the growing number of hospitalized patients. Starting from the analysis of the narratives of healthcare workers who served in the intensive care units of 10 hospitals in Central and Northern Italy, this contribution intends to highlight elements present during the pandemic period within the investigated structures, which are considered factors that can influence the birth of organizational learning. Specifically, the data collected through interviews and focus groups were analyzed using the framework analysis method of Ritchie and Spencer. The conducted study made it possible to identify and highlight factors related to aspects of communication, relationships, context, and organization that positively influenced the management of the health emergency, favoring the improvement of the structure. It is believed that the identification of these factors by healthcare organizations can represent a valuable opportunity to rethink themselves, thus becoming a source of learning.

Thoracic UltrasONOgraphy Reporting: The TUONO Consensus.

The widespread use of the lung ultrasound (LUS) has not been followed by the development of a comprehensive standardized tool for its reporting in the intensive care unit (ICU) which could be useful to promote consistency and reproducibility during clinical examination. This work aims to define the essential features to be included in a standardized reporting tool and provides a structured model form to fully express the diagnostic potential of LUS and facilitate intensivists in the use of a LUS in everyday clinical ICU examination. We conducted a modified Delphi process to build consensus on the items to be integrated in a standardized report form and on its structure. A committee of 19 critical care physicians from 19 participating ICUs in Italy was formed, including intensivists experienced in ultrasound from both teaching hospitals and referral hospitals, and internationally renowned experts on the LUS. The consensus for 31 statements out of 33 was reached at the third Delphi round. A structured model form was developed based on the approved statements. The development of a standardized model as a backbone to report a LUS may facilitate the guidelines' application in clinical practice and increase inter-operator agreement. Further studies are needed to evaluate the effects of standardized reports in critically ill patients.

Physiologic dead space is independently associated with mortality and discharge of mechanically ventilated patients with COVID-19 ARDS: a retrospective study.

Physiologic dead space is a well-established independent predictor of death in patients with acute respiratory distress syndrome (ARDS). Here, we explore the association between a surrogate measure of dead space (DS) and early outcomes of mechanically ventilated patients admitted to Intensive Care Unit (ICU) because of COVID-19-associated ARDS. Retrospective cohort study on data derived from Italian ICUs during the first year of the COVID-19 epidemic. A competing risk Cox proportional hazard model was applied to test for the association of DS with two competing outcomes (death or discharge from the ICU) while adjusting for confounders. The final population consisted of 401 patients from seven ICUs. A significant association of DS with both death (HR 1.204; CI 1.019-1.423; p = 0.029) and discharge (HR 0.434; CI 0.414-0.456; p [Formula: see text]) was noticed even when correcting for confounding factors (age, sex, chronic obstructive pulmonary disease, diabetes, PaO[Formula: see text]/FiO[Formula: see text], tidal volume, positive end-expiratory pressure, and systolic blood pressure). These results confirm the important association between DS and death or ICU discharge in mechanically ventilated patients with COVID-19-associated ARDS. Further work is needed to identify the optimal role of DS monitoring in this setting and to understand the physiological mechanisms underlying these associations.

Cosmological constant: a lesson from Bose-Einstein condensates.

The cosmological constant is one of the most pressing problems in modern physics. We address this issue from an emergent gravity standpoint, by using an analogue gravity model. Indeed, the dynamics of the emergent metric in a Bose-Einstein condensate can be described by a Poisson-like equation with a vacuum source term reminiscent of a cosmological constant. The direct computation of this term shows that in emergent gravity scenarios this constant may be naturally much smaller than the naive ground-state energy of the emergent effective field theory. This suggests that a proper computation of the cosmological constant would require a detailed understanding about how Einstein equations emerge from the full microscopic quantum theory. In this light, the cosmological constant appears as a decisive test bench for any quantum or emergent gravity scenario.

Thoracic UltrasONOgraphy Reporting: The TUONO Study.

Lung ultrasound (LUS) is a validated technique for the prompt diagnosis and bedside monitoring of critically ill patients due to its availability, safety profile, and cost-effectiveness. The aim of this work is to detect similarities and differences among LUS reports performed in ICUs and to provide a common ground for an integrated report form. We collected all LUS reports during an index week in 21 ICUs from the GiViTI network. First, we considered signs, chest areas, and terminology reported. Then, we compared different report structures and categorized them as structured reports (SRs), provided with a predefined model form, and free unstructured text reports (FTRs) that had no predetermined structure. We analyzed 171 reports from 21 ICUs, and 59 reports from 5 ICUs were structured. All the reports presented a qualitative description that mainly focused on the presence of B-lines, consolidations, and pleural effusion. Zones were defined in 66 reports (39%). In SRs, a complete examination of all the regions was more frequently achieved (96% vs. 74%), and a higher impact on therapeutic strategies was observed (17% vs. 6%). LUS reports vary significantly among different centers. Adopting an integrated SR seems to promote a systematic approach in scanning and reporting, with a potential impact on LUS clinical applications.

Tissue Penetration of Antimicrobials in Intensive Care Unit Patients: A Systematic Review-Part I.

The challenging severity of some infections, especially in critically ill patients, makes the diffusion of antimicrobial drugs within tissues one of the cornerstones of chemotherapy. The knowledge of how antibacterial agents penetrate tissues may come from different sources: preclinical studies in animal models, phase I-III clinical trials and post-registration studies. However, the particular physiopathology of critically ill patients may significantly alter drug pharmacokinetics. Indeed, changes in interstitial volumes (the third space) and/or in glomerular filtration ratio may influence the achievement of bactericidal concentrations in peripheral compartments, while inflammation can alter the systemic distribution of some drugs. On the contrary, other antibacterial agents may reach high and effective concentrations thanks to the increased tissue accumulation of macrophages and neutrophils. Therefore, the present review explores the tissue distribution of beta-lactams and other antimicrobials acting on the cell wall and cytoplasmic membrane of bacteria in critically ill patients. A systematic search of articles was performed according to PRISMA guidelines, and tissue/plasma penetration ratios were collected. Results showed a highly variable passage of drugs within tissues, while large interindividual variability may represent a hurdle which must be overcome to achieve therapeutic concentrations in some compartments. To solve that issue, off-label dosing regimens could represent an effective solution in particular conditions.

Tissue Penetration of Antimicrobials in Intensive Care Unit Patients: A Systematic Review-Part II.

In patients that are admitted to intensive care units (ICUs), the clinical outcome of severe infections depends on several factors, as well as the early administration of chemotherapies and comorbidities. Antimicrobials may be used in off-label regimens to maximize the probability of therapeutic concentrations within infected tissues and to prevent the selection of resistant clones. Interestingly, the literature clearly shows that the rate of tissue penetration is variable among antibacterial drugs, and the correlation between plasma and tissue concentrations may be inconstant. The present review harvests data about tissue penetration of antibacterial drugs in ICU patients, limiting the search to those drugs that mainly act as protein synthesis inhibitors and disrupting DNA structure and function. As expected, fluoroquinolones, macrolides, linezolid, and tigecycline have an excellent diffusion into epithelial lining fluid. That high penetration is fundamental for the therapy of ventilator and healthcare-associated pneumonia. Some drugs also display a high penetration rate within cerebrospinal fluid, while other agents diffuse into the skin and soft tissues. Further studies are needed to improve our knowledge about drug tissue penetration, especially in the presence of factors that may affect drug pharmacokinetics.