Search Results (11)

Background and objectives: In older and frail patients, in-hospital cardiac arrest (IHCA) is associated with high mortality. Early warning scores such as the National Early Warning Score 2 (NEWS2) are widely used to detect clinical deterioration, but their predictive accuracy in frail populations remains uncertain. This study aimed to assess whether integrating frailty measures with NEWS2 could better describe elderly IHCA patients. Materials and Methods: We conducted a single-center, retrospective observational study in adult and frail patients (≥18 years) admitted to medical and surgical wards of the University Hospital of Siena who experienced IHCA between January 2022 and January 2024. Data on demographics, such as last NEWS2 before IHCA, Clinical Frailty Scale (CFS), Barthel Index (BI), and Charlson Comorbidity Index (CCI) were retrospectively collected and analyzed. Patients were stratified into three categories, according to NEWS2: Stable (A), Potentially Unstable or Unstable (B), and Critical (C). Results: Seventy patients were analyzed (mean age 76.9 ± 11.0 years; 56% male). The mean pre-IHCA NEWS2 score was 6.0 ± 3.5, with 41% of patients classified as NEWS2-C, 48% classified as NEWS2-B, and 11% classified as NEWS2-A. The NEWS2-A category showed higher BI and lower CFS than NEWS2-B and NEWS2-C (p < 0.01), while CCI and age did not significantly differ. Conclusions: The association of NEWS2 with frailty scores could identify some elderly patients with limited pre-arrest physiological derangements but high frailty who suffered from IHCA. These findings provide descriptive insights that may inform monitoring strategies for “at-risk” elderly patients to help prevent IHCA. Full article

Load balancing is a widely adopted strategy in modern distributed systems because it distributes workloads across servers, mitigating overload and improving overall performance. However, the rapid growth of such systems has created a need for more adaptive strategies to ensure optimal utilization and responsiveness of resources. Traditional algorithms such as Round Robin (RR) and Weighted Round Robin (WRR) assign requests without considering server states or request characteristics. We implement a machine learning (ML)–based predictive load balancer, forecasting the latency of a request based on the request itself and container parameters, specifically the average latency of the last 50 requests and the count of active requests, and evaluate it against RR and WRR. For the experiment, synthetic data were generated to replicate real-world requests by creating random URL and method combinations, attaching a task size in Million Instructions (MI), and distributing them among three containers with varying resources according to the load balancing strategies described above. Under the conditions tested, the ML approach achieved the worst performance, trailing both RR and WRR in terms of throughput and average latency, although the model accuracy was sufficiently high (R² = 0.8+). Post hoc analysis indicates that limited and occasionally stale runtime features caused the load balancer to direct all requests to a single container until the next statistics update, since that container was considered the ‘best’ during that interval. Full article

Background: Ward patients who experience clinical deterioration are at high risk of mortality. Conventional rapid response systems (RRS) using track-and-trigger protocols have not consistently demonstrated improved outcomes. This study evaluated the impact of an artificial intelligence (AI)-based cardiac arrest prediction model. Methods: This 1-year, prospective, non-randomized interventional trial assigned hospitalized patients with AI-based software as a medical device (AI-SaMD) high-risk alerts to groups based on their subsequent clinical response; those reassessed or treated within 24 h comprised the AI-SaMD-guided cohort, while the remainder formed the usual care cohort. Alerts prompted an optional but not mandatory treatment review. The primary outcome was ward-based cardiac arrest; the secondary outcome was in-hospital mortality. Multivariable regression analysis was used to adjust for potential confounders. Results: Of 35,627 general ward admissions, 2906 triggered an AI-SaMD alert. Among these, 1409 (48.4%) were allocated to the AI-SaMD-guided cohort. The incidence of cardiac arrest significantly decreased from 2.07% to 1.06% (adjusted risk ratio (RR), 0.54; 95% confidence interval (CI), 0.20–0.88; p < 0.01). In-hospital mortality also significantly declined (adjusted RR, 0.65; 95% CI, 0.32–0.98; p < 0.05). Conclusions: AI-SaMD-guided alerts were associated with reductions in cardiac arrest and in-hospital mortality without requiring additional resources, supporting their integration into current clinical workflows to improve patient safety and optimize RRS performance. Full article

The recent pandemic increased attention to the need for appropriated ventilation and good air quality as efficient measures to achieve safe and healthy indoor air. This work provides a novel methodology for continuously evaluating ventilation in public areas using modern rapid response sensors (RRS). This methodology innovatively assesses the ventilation of a space by combining a quantitative estimation of the real air exchange in the space—obtained from CO₂ experimental RRS measurements and the characteristics of and activity in the space—and indoor and outdoor RRS measurements of other pollutants, with healthy recommendations from different organisations. The methodology allows space managers to easily evaluate, in a continuous form, the appropriateness of their ventilation strategy, thanks to modern RRS measurements and direct calculations (implemented here in a web app), even in situations of full activity. The methodology improves on the existing standards, which imply the release of tracer gases and expert intervention, and could also be used to set a control system that measures continuously and adapts the ventilation to changes in indoor occupancy and activity, guaranteeing safe and healthy air in an energy-efficient way. Sample public concurrence spaces with different conditions are used to illustrate the methodology. Full article

Background: Cancer patients who are admitted to hospitals are at high risk of short-term deterioration due to treatment-related or cancer-specific complications. A rapid response system (RRS) is initiated when patients who are deteriorating or at risk of deteriorating are identified. This study was conducted to develop a deep learning-based early warning score (EWS) for cancer patients (Can-EWS) using delta values in vital signs. Methods: A retrospective cohort study was conducted on all oncology patients who were admitted to the general ward between 2016 and 2020. The data were divided into a training set (January 2016–December 2019) and a held-out test set (January 2020–December 2020). The primary outcome was clinical deterioration, defined as the composite of in-hospital cardiac arrest (IHCA) and unexpected intensive care unit (ICU) transfer. Results: During the study period, 19,739 cancer patients were admitted to the general wards and eligible for this study. Clinical deterioration occurred in 894 cases. IHCA and unexpected ICU transfer prevalence was 1.77 per 1000 admissions and 43.45 per 1000 admissions, respectively. We developed two models: Can-EWS V1, which used input vectors of the original five input variables, and Can-EWS V2, which used input vectors of 10 variables (including an additional five delta variables). The cross-validation performance of the clinical deterioration for Can-EWS V2 (AUROC, 0.946; 95% confidence interval [CI], 0.943–0.948) was higher than that for MEWS of 5 (AUROC, 0.589; 95% CI, 0.587–0.560; p < 0.001) and Can-EWS V1 (AUROC, 0.927; 95% CI, 0.924–0.931). As a virtual prognostic study, additional validation was performed on held-out test data. The AUROC and 95% CI were 0.588 (95% CI, 0.588–0.589), 0.890 (95% CI, 0.888–0.891), and 0.898 (95% CI, 0.897–0.899), for MEWS of 5, Can-EWS V1, and the deployed model Can-EWS V2, respectively. Can-EWS V2 outperformed other approaches for specificities, positive predictive values, negative predictive values, and the number of false alarms per day at the same sensitivity level on the held-out test data. Conclusions: We have developed and validated a deep learning-based EWS for cancer patients using the original values and differences between consecutive measurements of basic vital signs. The Can-EWS has acceptable discriminatory power and sensitivity, with extremely decreased false alarms compared with MEWS. Full article

Background: Anticipating and avoiding preventable intrahospital cardiac arrest and clinical deterioration are important priorities for international healthcare systems and institutions. One of the internationally followed strategies to improve this matter is the introduction of the Rapid Response Systems (RRS). Although there is vast evidence from the international community, the evidence reported in a Spanish context is scarce. Methods: A nationwide cross-sectional research consisting of a voluntary 31-question online survey was performed. The Spanish Society of Intensive, Critical and Coronary Care Medicine (SEMICYUC) supported the research. Results: We received 62 fully completed surveys distributed within 13 of the 17 regions and two autonomous cities of Spain. Thirty-two of the participants had an established Rapid Response Team (RRT). Common frequency on measuring vital signs was at least once per shift but other frequencies were contemplated (48.4%), usually based on professional criteria (69.4%), as only 12 (19.4%) centers used Early Warning Scores (EWS) or automated alarms on abnormal parameters. In the sample, doctors, nurses (55%), and other healthcare professionals (39%) could activate the RRT via telephone, but only 11.3% of the sample enacted this at early signs of deterioration. The responders on the RRT are the Intensive Care Unit (ICU), doctors, and nurses, who are available 24/7 most of the time. Concerning the education and training of general ward staff and RRT members, this varies from basic to advanced and specific-specialized level, simulating a growing educational methodology among participants. A great number of participants have emergency resuscitation equipment (drugs, airway adjuncts, and defibrillators) in their general wards. In terms of quality improvement, only half of the sample registered RRT activity indicators. In terms of the use of communication and teamwork techniques, the most used is clinical debriefing in 29 centers. Conclusions: In terms of the concept of RRS, we found in our context that we are in the early stages of the establishment process, as it is not yet a generalized concept in most of our hospitals. The centers that have it are in still in the process of maturing the system and adapting themselves to our context. Full article

There are different methods to extract and brew coffee, therefore, coffee processing is an important factor and should be studied in detail. Herein, coffee was brewed by means of a new espresso professional coffee machine, using coffee powder or portioned coffee (capsule). Four different kinds of coffees (Biologico, Dolce, Deciso, Guatemala) were investigated with and without capsules and the goal was to classify the volatiloma of each one by Small Sensor System (S3). The response of the semiconductor metal oxide sensors (MOX) of S3 where recorded, for all 288 replicates and after normalization ∆R/R0 was extracted as a feature. PCA analysis was used to compare and differentiate the same kind of coffee sample with and without a capsule. It could be concluded that the coffee capsules affect the quality, changing on the flavor profile of espresso coffee when extracted different methods confirming the use of s3 device as a rapid and user-friendly tool in the food quality control chain. Full article

In the era of rapid development of new, expensive cancer therapies, value frameworks have been developed to quantify clinical benefit (CB). We assessed the evolution of CB since the 2015 introduction of The American Society of Clinical Oncology and The European Society of Medical Oncology value frameworks. Randomized clinical trials (RCTs) assessing systemic therapies for solid malignancies from 2010 to 2020 were evaluated and CB (Δ) in 2010–2014 (pre-value frameworks (PRE)) were compared to 2015–2020 (POST) for overall survival (OS), progression-free survival (PFS), response rate (RR), and quality of life (QoL). In the 485 studies analyzed (12% PRE and 88% POST), the most common primary endpoint was PFS (49%), followed by OS (20%), RR (12%), and QoL (6%), with a significant increase in OS and decrease in RR as primary endpoints in the POST era (p = 0.011). Multivariable analyses revealed significant improvement in ΔOS POST (OR 2.86, 95% CI 0.46 to 5.26, p = 0.02) while controlling for other variables. After the development of value frameworks, median ΔOS improved minimally. The impact of value frameworks has yet to be fully realized in RCTs. Efforts to include endpoints shown to impact value, such as QoL, into clinical trials are warranted. Full article

Background and Objectives: For effective function of the rapid response system (RRS), prompt identification of patients at a high risk of cardiac arrest and RRS activation without hesitation are important. This study aimed to identify clinical factors that increase the risk of intensive care unit (ICU) transfer and cardiac arrest to identify patients who are likely to develop serious conditions requiring ICU management and appropriate RRS activation in Japan. Materials and Methods: We performed a single-center, case control study among patients requiring a rapid response team (RRT) call from 2017 to 2020. We extracted the demographic data, vital parameters, blood oxygen saturation (SpO₂) and the fraction of inspired oxygen (FiO₂) from the medical records at the time of RRT call. The patients were divided into two groups to identify clinical signs that correlated with the progression of clinical deterioration. Patient characteristics in the two groups were compared using statistical tests based on the distribution. Receiver operating characteristic (ROC) curve analysis was used to identify the appropriate cut-off values of vital parameters or FiO₂ that showed a significant difference between-group. Multivariate logistic regression analysis was used to identify patient factors that were predictive of RRS necessity. Results: We analyzed the data of 65 patients who met our hospital’s RRT call criteria. Among the clinical signs in RRT call criteria, respiratory rate (RR) (p < 0.01) and the needed FiO₂ were significantly increased (p < 0.01) in patients with severe disease course. ROC curve analysis revealed RR and needed FiO₂ cut-off values of 25.5 breaths/min and 30%. The odds ratio for the progression of clinical deterioration was 40.5 times higher with the combination of RR ≥ 26 breaths/min and needed FiO₂ ≥ 30%. Conclusions: The combined use of RR ≥ 26 breaths/min and needed FiO₂ ≥ 30% might be valid for identifying patients requiring intensive care management. Full article

Background: Hospitalized patients can develop septic shock at any time. Therefore, it is important to identify septic patients in hospital wards and rapidly perform the optimal treatment. Although the sepsis bundle has already been reported to improve survival rates, the controversy over evidence of the effect of in-hospital sepsis continues to exist. We aimed to estimate the outcomes and bundle compliance of patients with septic shock in hospital wards managed through the rapid response system (RRS). Methods: A retrospective cohort study of 976 patients with septic shock managed through the RRS at an academic, tertiary care hospital in Korea from 2008 to 2017. Results: Of the 976 enrolled patients, the compliance of each sepsis bundle was high (80.8–100.0%), but the overall success rate of the bundle was low (58.3%). The compliance rate for achieving the overall sepsis bundle increased from 26.5% to 70.0%, and the 28-day mortality continuously decreased from 50% to 32.1% over 10 years. We analyzed the two groups according to whether they completed the overall sepsis bundle or not. Of the 976 enrolled patients, 569 (58.3%) sepsis bundles were completed, whereas 407 (41.7%) were incomplete. The complete bundle group showed lower 28-day mortality than the incomplete bundle group (37.1% vs. 53.6%, p < 0.001). In the multivariate multiple logistic regression model, the 28-day mortality was significantly associated with the complete bundle (adjusted odds ratio (OR), 0.61; 95% confidence intervals (CI), 0.40–0.91; p = 0.017). The obtaining of blood cultures (adjusted OR, 0.45; 95% CI, 0.33–0.63; p < 0.001) and lactate re-measurement (adjusted OR, 0.69; 95% CI, 0.50–0.95; p = 0.024) in each component of the sepsis bundle were associated with the 28-day mortality. Conclusions: The rapid response system provides improving sepsis bundle compliances and survival in patients with septic shock in hospital wards. Full article

The major components of the cytokinin (CK) signaling pathway have been identified from the receptors to their downstream transcription factors. However, since signaling proteins are encoded by multigene families, characterizing and quantifying the contribution of each component or their combinations to the signaling cascade have been challenging. Here, we describe a transient gene expression system in rice (Oryza sativa) protoplasts suitable to reconstitute CK signaling branches using the CK reporter construct TCSn:fLUC, consisting of a synthetic CK-responsive promoter and the firefly luciferase gene, as a sensitive readout of signaling output. We used this system to systematically test the contributions of CK signaling components, either alone or in various combinations, with or without CK treatment. The type-B response regulators (RRs) OsRR16, OsRR17, OsRR18, and OsRR19 all activated TCSn:fLUC strongly, with OsRR18 and OsRR19 showing the strongest induction by CK. Cotransfecting the reporter with OsHP01, OsHP02, OsHP05, or OsHK03 alone resulted in much weaker effects relative to those of the type-B OsRRs. When we tested combinations of OsHK03, OsHPs, and OsRRs, each combination exhibited distinct CK signaling activities. This system thus allows the rapid and high-throughput exploration of CK signaling in rice. Full article