Clinical and Microbiological Impact of Implementing a Decision Support Algorithm through Microbiologic Rapid Diagnosis in Critically Ill Patients: An Epidemiological Retrospective Pre-/Post-Intervention Study.

BACKGROUND: Data on the benefits of rapid microbiological testing on antimicrobial consumption (AC) and antimicrobial resistance patterns (ARPs) are scarce. We evaluated the impact of a protocol based on rapid techniques on AC and ARP in intensive care (ICU) patients. METHODS: A retrospective pre- (2018) and post-intervention (2019-2021) study was conducted in ICU patients. A rapid diagnostic algorithm was applied starting in 2019 in patients with a lower respiratory tract infection. The incidence of nosocomial infections, ARPs, and AC as DDDs (defined daily doses) were monitored. RESULTS: A total of 3635 patients were included: 987 in the pre-intervention group and 2648 in the post-intervention group. The median age was 60 years, the sample was 64% male, and the average APACHE II and SOFA scores were 19 points and 3 points. The overall ICU mortality was 17.2% without any differences between the groups. An increase in the number of infections was observed in the post-intervention group (44.5% vs. 17.9%, p < 0.01), especially due to an increase in the incidence of ventilator-associated pneumonia (44.6% vs. 25%, p < 0.001). AC decreased from 128.7 DDD in 2018 to 66.0 DDD in 2021 (rate ratio = 0.51). An increase in Pseudomonas aeruginosa susceptibility of 23% for Piperacillin/tazobactam and 31% for Meropenem was observed. CONCLUSION: The implementation of an algorithm based on rapid microbiological diagnostic techniques allowed for a significant reduction in AC and ARPs without affecting the prognosis of critically ill patients.

Timing of intubation and ICU mortality in COVID-19 patients: a retrospective analysis of 4198 critically ill patients during the first and second waves.

BACKGROUND: The optimal time to intubate patients with SARS-CoV-2 pneumonia has not been adequately determined. While the use of non-invasive respiratory support before invasive mechanical ventilation might cause patient-self-induced lung injury and worsen the prognosis, non-invasive ventilation (NIV) is frequently used to avoid intubation of patients with acute respiratory failure (ARF). We hypothesized that delayed intubation is associated with a high risk of mortality in COVID-19 patients. METHODS: This is a secondary analysis of prospectively collected data from adult patients with ARF due to COVID-19 admitted to 73 intensive care units (ICUs) between February 2020 and March 2021. Intubation was classified according to the timing of intubation. To assess the relationship between early versus late intubation and mortality, we excluded patients with ICU length of stay (LOS) < 7 days to avoid the immortal time bias and we did a propensity score and a cox regression analysis. RESULTS: We included 4,198 patients [median age, 63 (54‒71) years; 71% male; median SOFA (Sequential Organ Failure Assessment) score, 4 (3‒7); median APACHE (Acute Physiology and Chronic Health Evaluation) score, 13 (10‒18)], and median PaO2/FiO2 (arterial oxygen pressure/ inspired oxygen fraction), 131 (100‒190)]; intubation was considered very early in 2024 (48%) patients, early in 928 (22%), and late in 441 (10%). ICU mortality was 30% and median ICU stay was 14 (7‒28) days. Mortality was higher in the "late group" than in the "early group" (37 vs. 32%, p < 0.05). The implementation of an early intubation approach was found to be an independent protective risk factor for mortality (HR 0.6; 95%CI 0.5‒0.7). CONCLUSIONS: Early intubation within the first 24 h of ICU admission in patients with COVID-19 pneumonia was found to be an independent protective risk factor of mortality. TRIAL REGISTRATION: The study was registered at Clinical-Trials.gov (NCT04948242) (01/07/2021).

Soporte a la organización de las Unidades de Cuidados Intensivos durante la pandemia, a través de mapas creados a partir de los Sistemas de Información Clínica / Support to the organization of the Intensive Care Units during the pandemic through maps created from the Clinical Information Systems

No disponible

Automatic generation of minimum dataset and quality indicators from data collected routinely by the clinical information system in an intensive care unit.

BACKGROUND: Quality indicators (QIs) are being increasingly used in medicine to compare and improve the quality of care delivered. The feasibility of data collection is an important prerequisite for QIs. Information technology can improve efforts to measure processes and outcomes. In intensive care units (ICU), QIs can be automatically measured by exploiting data from clinical information systems (CIS). OBJECTIVE: To describe the development and application of a tool to automatically generate a minimum dataset (MDS) and a set of ICU quality metrics from CIS data. METHODS: We used the definitions for MDS and QIs proposed by the Spanish Society of Critical Care Medicine and Coronary Units. Our tool uses an extraction, transform, and load process implemented with Python to extract data stored in various tables in the CIS database and create a new associative database. This new database is uploaded to Qlik Sense, which constructs the MDS and calculates the QIs by applying the required metrics. The tool was tested using data from patients attended in a 30-bed polyvalent ICU during a six-year period. RESULTS: We describe the definitions and metrics, and we report the MDS and QI measurements obtained through the analysis of 4546 admissions. The results show that our ICU's performance on the QIs analyzed meets the standards proposed by our national scientific society. CONCLUSIONS: This is the first step toward using a tool to automatically obtain a set of actionable QIs to monitor and improve the quality of care in ICUs, eliminating the need for professionals to enter data manually, thus saving time and ensuring data quality.

Infección grave por Coronavirus SARS-CoV-2: Experiencia en un hospital de tercer nivel con pacientes afectados por COVID-19 durante la pandemia 2020 / Severe infection due to the SARS-CoV-2 CORONAVIRUS: Experience of a tertiary hospital with COVID-19 patients during the 2020 pandemic

No disponible

The prognostic value of muscle regional oxygen saturation index in severe community-acquired pneumonia: a prospective observational study.

BACKGROUND: Community-acquired pneumonia (CAP) mortality exceeds 20 % in critical care patients despite appropriate antibiotic therapy. Regional tissue oxygen saturation index (rSO2) measured with near-infrared spectroscopy (NIRS) might facilitate early detection for patients at risk of serious complications. Our objectives were to determine the relationship between early determination of rSO2 and mortality and to compare discrimination power for mortality of rSO2 and other resuscitation variables in critically ill CAP patients. METHODS: This is a prospective observational study. Patients with CAP were enrolled within 6 h to intensive care admission. Demographics and clinical variables were recorded. rSO2 was determined using NIRS in brachioradialis muscle. All variables were determined at baseline and 24 h after admission. RESULTS: Forty patients were enrolled. Fourteen patients (35 %) had a baseline rSO2 < 60 % and 7 of them died (50 %). Only 1 of 26 (3.8 %) patients with rSO2 ≥ 60 % died (p = 0.007). The area under ROC curve (AUROC) showed consistent mortality discrimination at baseline (0.84, p = 0.03) and at 24 h (0.86, p = 0.006) for rSO2 values. Cox regression analysis showed that "low" rSO2 at ICU admission (hazard ratio (HR) = 8.99; 95 % confidence interval (CI) 1.05-76.8; p = 0.045) and "low" rSO2 at 24 h (HR = 13.18; 95 % CI 1.52-113.6; p = 0.019) were variables independently associated with mortality. In contrast, other variables such as Acute Physiology and Chronic Health Evaluation (APACHE II) score (HR = 1.09; 95 % CI 0.99-1.19; p = 0.052) were not associated with mortality. CONCLUSIONS: Our findings suggest that forearm skeletal muscle rSO2 differs in patients with severe CAP according to outcome and might be an early prognosis tool.