Rapid Response System Research Articles

Sepsis Bundle Compliance and Mortality according to Body Temperature of Patients with Sepsis in General Wards Identified Using the Rapid Response System

Purpose : This study aimed to investigate the difference in compliance with the sepsis bundle and mortality rates according to the body temperature of patients with sepsis in general wards identified using a rapid response system (RRS). Methods : A retrospective observational study of 1,083 patients with sepsis in general wards identified using the RRS from July 2018 to December 2022 was performed at a tertiary care hospital in South Korea. The patients were classified into hypothermia (＜36℃), normothermia (36-38℃), and hyperthermia (＞38℃) groups according to their body temperature at the time of RRS activation. Results : A total of 1,083 sepsis patients were analyzed, comprising 17 cases of hypothermia, 624 cases of normothermia, and 442 cases of hyperthermia. There were statistically significant differences among the body temperature groups in the rate of compliance with the sepsis bundle within 1 h (hypothermia: 64.7% vs. normothermia: 49.5% vs. hyperthermia: 60.4%, <i>p</i> =.010), the rate of compliance with the overall sepsis bundle, including lactate re-measurement (64.7% vs. 49.5% vs. 60.4%, <i>p</i> =.001), and the rate of blood culture testing (94.1% vs. 85.9% vs. 92.8%, <i>p</i> =.002). The 28-day mortality rates in the hypothermia, normothermia, and hyperthermia groups were 29.4%, 32.4%, and 16.5%, respectively (<i>p</i> ＜.001). Conclusion : There were statistically significant differences in compliance with the sepsis bundle and mortality rates according to body temperature. Patients with sepsis and normothermia showed lower compliance with the sepsis bundle and higher mortality rates. Therefore, it is recommended to develop strategies for the early recognition of patients with sepsis and normothermia and to improve compliance with the sepsis bundle.

The Early Radio Afterglow of Short GRB 230217A

We present the radio afterglow of short gamma-ray burst (GRB) 230217A, which was detected less than 1 day after the gamma-ray prompt emission with the Australia Telescope Compact Array (ATCA) and the Karl G. Jansky Very Large Array. The ATCA rapid-response system automatically triggered an observation of GRB 230217A following its detection by the Neil Gehrels Swift Observatory and began observing the event just 32 minutes postburst at 5.5 and 9 GHz for 7 hr. Dividing the 7 hr observation into three time-binned images allowed us to obtain radio detections with logarithmic central times of 1, 2.8, and 5.2 hr postburst, the first of which represents the earliest radio detection of any GRB to date. The decline of the light curve is consistent with reverse shock emission if the observing bands are below the spectral peak and not affected by synchrotron self-absorption. This makes GRB 230217A the fifth short GRB (SGRB) with radio detections attributed to a reverse shock at early times (<1 day postburst). Following brightness temperature arguments, we have used our early radio detections to place the highest minimum Lorentz factor ( Γmin>50 at ∼1 hr) constraints on a GRB in the radio band. Our results demonstrate the importance of rapid radio follow-up observations with long integrations and good sensitivity for detecting the fast-evolving radio emission from SGRBs and probing their reverse shocks.

Characteristics and outcomes of patients screened by the rapid response team and transferred to intensive care unit in South Korea

The rapid response system (RRS) is associated with a reduction in in-hospital mortality. This study aimed to determine the characteristics and outcomes of patients transferred to the intensive care unit (ICU) by a rapid response team (RRT). This retrospective, multicenter cohort study included patients from nine hospitals in South Korea. Adult patients who were admitted to the general ward (GW) and required RRS activation were included. Patients with do-not-resuscitate orders and without lactate level or Sequential Organ Failure Assessment score were excluded. A total of 8228 patients were enrolled, 3379 were transferred to the ICU. The most common reasons for RRT activation were respiratory distress, sepsis and septic shock. The number of patients who underwent interventions, the length of hospital stays, 28-day mortality, and in-hospital mortality were higher in the ICU group than in the GW group. Factors that could affect both 28-day and in-hospital mortality included the severity score, low PaO2/FiO2 ratio, higher lactate and C-reactive protein levels, and hospitalization time prior to RRT activation. Patients admitted to the ICU after RRT activation generally face more challenging clinical situations, which may affect their survival outcomes.

Acute Care Nurses' Partnership With Patients to Recognise and Respond to Changes in Patients' Clinical States: AQualitative Study.

To explore and describe acute care nurses' partnership with patients to recognise and respond to changes in patients' clinical states. Acute care nurses' decisions to partner with patients to recognise deterioration in clinical states and to respond by activating a rapid response system improves patient outcomes. Acutely unwell patients can also experience clinical changes that include improvement and deterioration that does not trigger rapid response system activation over the course of hospitalisation from illness and treatment. How acute care nurses partner with patients in response to improvement and deterioration not triggering a rapid response system is not well-understood. An exploratory, descriptive study underpinned by Tanner's Clinical Judgement Model. Using purposive and quota sampling, 20 nurses with direct patient care responsibilities on one medical and one surgical ward in a large Australian hospital were recruited. Nonparticipant observations followed by semistructured interviews were conducted between January and May of 2021. Nurse-patient interactions were observed for 4 h, and verbally described and recorded. Semistructured interviews were recorded and explored nurses' reasoning behind decisions observed. Reflexive thematic analysis was used to analyse the data. Three themes were identified from the data: nurses checking in for changes; nurses forming judgements; and nurses partnering with patients to respond. Acute care nurses promoted subjective assessment based on patients' safety risks. Patients' participation in response to changes was prioritised based on acute care nurses' judgement of safety. Patients receive significant safety benefits when acute care nurses partner with patients in response to their experience of improvement and deterioration during acute illness. Further research should evaluate the sensitivity of subjective cues in patient assessment. Partnership with patients in assessment and management of improvement and deterioration improves the quality and safety of patient care. Assessment frameworks should equally prioritise the use of objective and subjective cues. Nursing education should promote the safety benefits of patient partnerships in responding to patient changes. Equator checklist COREQ. Data collected included description of patients' interactions with study participants.

Paediatric family activation rapid response (FARR) in acute care: a qualitative study for developing a multilingual application (app) intervention

BackgroundDelayed recognition of clinical deterioration can result in harm to patients. Parents/carers can often recognise changes in the child’s condition before healthcare professionals (HCPs). To mitigate the risk of failure...

Impact of rapid response system in mortality and complications post-orthopedic surgery: a retrospective cohort study

BackgroundRapid response systems (RRSs) are used in hospitals to identify and treat deteriorating patients. However, RRS implementation and outcomes in orthopedic and surgical patients remain controversial. We aimed to investigate whether the RRS affects mortality and complications after orthopedic surgery.MethodsThe National Health Insurance Service of South Korea provided the data for this population-based cohort study. Individuals who were admitted to the hospital that implemented RRS were categorized into the RRS group and those admitted to a hospital that did not implement the RRS were categorized into the non-RRS group. In-hospital mortality and postoperative complications were the endpoints.ResultsA total of 931,774 adult patients were included. Among them, 93,293 patients underwent orthopedic surgery in a hospital that implemented RRS and were assigned to the RRS group, whereas 838,481 patients were assigned to the non-RRS group. In multivariable logistic regression analysis, the RRS group was not associated with in-hospital mortality after orthopedic surgery compared with the non-RRS group (odds ratio [OR] 0.93, 95% confidence interval [CI] 0.80, 1.08; P = 0.350). However, the RRS group was associated with a 14% lower postoperative complication rate after orthopedic surgery than the non-RRS group (OR 0.86, 95% CI 0.84, 0.86; P < 0.001).ConclusionsThe RRS was not associated with in-hospital mortality following orthopedic surgery in South Korea. However, RRS deployment was related to a decreased risk of postoperative complications in patients undergoing orthopedic surgery.

Rapid response system and outcomes in patients who underwent cranial neurosurgery: a nationwide cohort study.

Hospitals use rapid response systems (RRSs) to identify and treat patients whose conditions rapidly worsen after admission. However, no study has examined the effects of RRS deployment on the clinical outcomes of patients undergoing cranial neurosurgery. Thus, the authors investigated whether use of RRS affects clinical outcomes in these patients. This nationwide, retrospective, population-based cohort study included adult patients who underwent cranial neurosurgery in South Korea between January 1, 2019, and December 31, 2021. The authors classified patients admitted to hospitals that operated RRS into the RRS group and those admitted to hospitals that did not operate RRS into the non-RRS group. Overall, 73,600 hospitalized patients who underwent cranial neurosurgery were included in this study. These patients were divided into 2 groups: 38,544 (52.4%) were included in the RRS group and 35,066 (47.6%) in the non-RRS group. After propensity score matching, 40,058 patients (20,029 in each group) remained. The in-hospital mortality rate was 10.1% (2022/20,029) for the non-RRS group and 8.9% (1792/20,029) for the RRS group. In the logistic regression analysis, the in-hospital mortality rate of the RRS group was 12% (OR 0.88, 95% CI 0.82-0.94, p < 0.001) lower than that of the non-RRS group. The 1-year all-cause mortality rate was 26.5% (5300/20,029) in the non-RRS group and 24.6% (4921/20,029) in the RRS group. In the Cox regression analysis, the 1-year all-cause mortality rate of the RRS group was 9% (HR 0.91, 95% CI 0.88-0.95; p < 0.001) lower than that of the non-RRS group. This population-based cohort study revealed that implementing RRS was associated with enhanced short- and long-term survival outcomes in patients who underwent cranial neurosurgery. The authors' findings indicate that the introduction of RRS can enhance patient survival rates after cranial neurosurgery.

Rapid response system and mortality in intensive care unit: a nationwide cohort study in South Korea.

The beneficial effects of a rapid response system (RRS) on clinical outcomes in patients admitted to a ward have been established. However, the relationship between RRS implementation and clinical outcomes in patients in the intensive care unit (ICU) has not yet been established. Therefore, we aimed to investigate whether the RRS affects clinical outcomes in critically ill patients admitted to the ICU. As a nationwide, population-based cohort study, all adult patients who were admitted to the ICU from 1 January 2019 to 31 December 2021 in South Korea were included. Patients in hospitals with an RRS formed the RRS group; those in hospitals lacking an RRS constituted the non-RRS group. In total, 900,606 patients admitted to the ICU were included in the final analysis. Among them, 365,305 (40.6%) were assigned to the RRS group, and 535,301 (59.4%) were assigned to the non-RRS group. After propensity score (PS) matching, a total of 454,748 patients (227,374 in each group) were included in the final analysis. In the PS-matched cohort, the RRS group showed 8% (odds ratio [OR]: 0.92, 95% confidence interval [CI]: 0.91, 0.94; P < 0.001) and 11% (hazard ratio: 0.89, 95% CI: 0.88, 0.90; P < 0.001) lower in-hospital mortality rates and 1-year all-cause mortality rates than the non-RRS group, respectively. In addition, ICU readmission rates and the occurrence rate for adverse events during hospitalization in the RRS group were 3% (OR: 0.97, 95% CI: 0.95, 0.98; P < 0.001) and 21% (OR: 0.79, 95% CI: 0.78, 0.80; P < 0.001) lower than those in the non-RRS group, respectively. RRS deployment was linked to lower in-hospital and 1-year all-cause mortality rates, ICU readmission rates, and the occurrence of adverse events during hospitalization among ICU patients. The findings indicate that using the RRS could assist not only patients in the ward but also critically ill patients in the ICU.

Prediction model of in-hospital cardiac arrest using machine learning in the early phase of hospitalization.

In hospitals, the deterioration of a patient's condition leading to death is often preceded by physiological abnormalities in the hours to days beforehand. Several risk-scoring systems have been developed to identify patients at risk of major adverse events; however, such systems often exhibit low sensitivity and specificity. To identify the risk factors associated with in-hospital cardiac arrest (IHCA), we conducted a retrospective cohort study at a tertiary medical center in Taiwan. Four machine learning algorithms were employed to identify the factors most predictive of IHCA. The support vector machine model was discovered to be the most effective at predicting IHCA. The ten most critical physiological parameters at 8 h prior to the event were pulse rate, age, white blood cell count, lymphocyte count, body temperature, body mass index, systolic and diastolic blood pressure, platelet count, and use of central nervous system-active medication. Using these parameters, we can enhance early warning and rapid response systems in our hospital, potentially reducing the incidence of IHCA in clinical practice.

Effects of Online Naloxone Training for Laypersons: An Extended-Baseline Assessment

Background: While laypersons can play a crucial role in administering naloxone in opioid overdoses, they must be recruited and trained to effectively manage overdose events as good Samaritans. This study aimed to examine the effectiveness of a technology-based intervention that recruited and trained laypersons to administer naloxone. Methods: Opioid Rapid Response System (ORRS) was an online recruitment and training intervention which capitalized on social cognitive theory and a digital media engagement model to mobilize laypersons to administer intranasal naloxone. ORRS was developed based on a randomized waitlisted controlled trial (N = 220). This secondary analysis is a within-group, extended-baseline assessment of the waitlisted group (n = 106), considering that they served as their own control prior to receiving the training. ORRS was conducted in five counties of Indiana with adults who did not self-identify as a certified first responder. Five indices were generated from 23 variables: knowledge of overdose signs, knowledge of overdose management, self-efficacy in responding, concerns about responding, and intent to respond. Paired t-test compared changes between 3 timepoints. Results: Three indices had significantly greater increases associated with training compared to extended baseline: recognizing opioid overdose signs (difference = 0.08; 95%CI = 0.02, 0.15; t = 2.48; p = 0.01); knowledge of overdose management (difference = 0.27; 95%CI = 0.18, 0.35; t = 5.99; p < 0.01); and self-efficacy in overdose management (difference = 0.68; 95%CI = 0.45, 0.91; t = 5.78; p < 0.01). Concerns related to overdose management significantly decreased as expected (difference = −1.53; 95%CI = −1.86, −1.21; t = −9.27; p < 0.01). Conclusions: ORRS provided strong support for self-efficacy, concerns, and knowledge related to overdose management, and the digital modality accelerates largescale dissemination.

A multi-nudge-based behavioural insight into ward nurses' respiratory rate measurement: An observational study.

This study observed changes in respiratory rate measurement (RRM) and identified barriers and challenges in clinical practice that influence healthcare worker behaviour, aiming to improve RRM in a hospital setting. An observational study was conducted. We observed and analysed changes in the behaviour of healthcare workers at a hospital where multi-nudges were introduced to improve RRM. We checked respiration rate using electronic data and discovered that the original measurement rates were low. Measurement rates rapidly increased after posters were added. Barriers such as time constraints and measurement equipment were also noted. RRM was found to be effective in promoting behavioural economics in medical settings. The results show that incorporating behavioural science principles into medical interventions has the potential to positively change behaviour. By increasing nurses' awareness of respiratory rate measurement and addressing barriers to it, the measurement rate of respiratory rate can also increase, leading to more accurate patient evaluations and triage. WHAT PROBLEM DID THE STUDY ADDRESS?: The proportion of respiratory rate measurements leading to rapid response system (RRS) calls was low. WHAT WERE THE MAIN FINDINGS?: The study observed that a multi-nudge approach effectively changes the behaviour of ward nurses, resulting in enhanced quality of medical care. WHERE AND ON WHOM WILL THE RESEARCH HAVE AN IMPACT?: This research can serve as a valuable reference for leaders promoting healthcare quality projects, by offering a method to encourage behavioural change. This study complied with the EQUATOR guidelines and its reporting adheres to the STROBE checklist. No patient or public contribution.

A Partial Near-infrared Guide Star Catalog for Thirty Meter Telescope Operations

At first light, the Thirty Meter Telescope (TMT) near-infrared (NIR) instruments will be fed by a multiconjugate adaptive optics instrument known as the Narrow Field Infrared Adaptive Optics System (NFIRAOS). NFIRAOS will use six laser guide stars to sense atmospheric turbulence in a volume corresponding to a field of view of 2′, but natural guide stars (NGSs) will be required to sense tip/tilt and focus. To achieve high sky coverage (50% at the north Galactic pole), the NFIRAOS client instruments use NIR on-instrument wave front sensors that take advantage of the sharpening of the stars by NFIRAOS. A catalog of guide stars with NIR magnitudes as faint as 22 mag in the J band (Vega system), covering the TMT-observable sky, will be a critical resource for the efficient operation of NFIRAOS, and no such catalog currently exists. Hence, it is essential to develop such a catalog by computing the expected NIR magnitudes of stellar sources identified in deep optical sky surveys using their optical magnitudes. This paper discusses the generation of a partial NIR Guide Star Catalog (IRGSC), similar to the final IRGSC for TMT operations. The partial catalog is generated by applying stellar atmospheric models to the optical data of stellar sources from the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) optical data and then computing their expected NIR magnitudes. We validated the computed NIR magnitudes of the sources in some fields by using the available NIR data for those fields. We identified the remaining challenges of this approach. We outlined the path for producing the final IRGSC using the Pan-STARRS data. We have named the Python code to generate the IRGSC as irgsctool, which generates a list of NGS for a field using optical data from the Pan-STARRS 3pi survey and also a list of NGSs having observed NIR data from the UKIRT Infrared Deep Sky Survey if they are available. irgsctool is available in the public domain on this GitHub public repository (https://github.com/sshah1502/irgsc), while the generated and validated IRGSC for the 20 test fields and additional Pan-STARRS Medium Deep Survey fields can be found on Zenodo.

The Discovery and Evolution of a Possible New Epoch of Cometary Activity by the Centaur (2060) Chiron

Centaurs are small solar system objects on chaotic orbits in the giant planet region, forming an evolutionary continuum with the Kuiper Belt objects and Jupiter-family comets. Some Centaurs are known to exhibit cometary activity, though unlike comets, this activity tends not to correlate with heliocentric distance, and the mechanism behind it is currently poorly understood. We utilize serendipitous observations from the Asteroid Terrestrial-impact Last Alert System, Zwicky Transient Facility, Panoramic Survey Telescope and Rapid Response System, Dark Energy Survey, and Gaia in addition to targeted follow-up observations from the Las Cumbres Observatory, TRAnsiting Planets and PlanetesImals Small Telescope South (TRAPPIST-South), and Gemini North telescope to analyze an unexpected brightening exhibited by the known active Centaur (2060) Chiron in 2021. This is highly indicative of a cometary outburst. As of 2023 February, Chiron had still not returned to its prebrightening magnitude. We find Chiron's rotational lightcurve, phase curve effects, and possible high-albedo surface features to be unlikely causes of this observed brightening. We consider the most likely cause to be an epoch of either new or increased cometary activity, though we cannot rule out a possible contribution from Chiron's reported ring system, such as a collision of as-yet-unseen satellites shepherding the rings. We find no evidence for a coma in our Gemini or TRAPPIST-South observations, though this does not preclude the possibility that Chiron is exhibiting a coma that is too faint for observation or constrained to the immediate vicinity of the nucleus.

Rapid response systems, antibiotic stewardship and medication reconciliation: a scoping review on implementation factors, activities and outcomes

IntroductionMany patient safety practices are only partly established in routine clinical care, despite extensive quality improvement efforts. Implementation science can offer insights into how patient safety practices can be successfully...

Machine learning algorithm for predicting 30-day mortality in patients receiving rapid response system activation: A retrospective nationwide cohort study

This study investigated the accuracy of a machine learning algorithm for predicting mortality in patients receiving rapid response system (RRS) activation. This retrospective cohort study used data from the In-Hospital Emergency Registry in Japan, which collects nationwide data on patients receiving RRS activation. The missing values in the dataset were replaced using multiple imputations (mode imputation, BayseRidge sklearn. linear model, and K-nearest neighbor model), and the enrolled patients were randomly assigned to the training and test cohorts. We established prediction models for 30-day mortality using the following four types of machine learning classifiers: Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting, random forest, and neural network. Fifty-two variables (patient characteristics, details of RRS activation, reasons for RRS initiation, and hospital capacity) were used to construct the prediction algorithm. The primary outcome was the accuracy of the prediction model for 30-day mortality. Overall, the data from 4,997 patients across 34 hospitals were analyzed. The machine learning algorithms using LightGBM demonstrated the highest predictive value for 30-day mortality (area under the receiver operating characteristic curve, 0.860 [95 % confidence interval, 0.825–0.895]). The SHapley Additive exPlanations summary plot indicated that hospital capacity, site of incidence, code status, and abnormal vital signs within 24 h were important variables in the prediction model for 30-day mortality.

Listen to me, I really am sick! Patient and family narratives of clinical deterioration before and during rapid response system intervention.

To explore patient and family narratives about their recognition and response to clinical deterioration and their interactions with clinicians prior to and during Medical Emergency Team (MET) activations in hospital. Research on clinical deterioration has mostly focused on clinicians' roles. Although patients and families can identify subtle cues of early deterioration, little research has focused on their experience of recognising, speaking up and communicating with clinicians during this period of instability. A narrative inquiry. Using narrative interviewing techniques, 33 adult patients and 14 family members of patients, who had received a MET call, in one private and one public academic teaching hospital in Melbourne, Australia were interviewed. Narrative analysis was conducted on the data. The core story of help seeking for recognition and response by clinicians to patient deterioration yielded four subplots: (1) identifying deterioration, recognition that something was not right and different from earlier; (2) voicing concerns to their nurse or by family members on their behalf; (3) being heard, desiring a response acknowledging the legitimacy of their concerns; and (4) once concerns were expressed, there was an expectation of and trust in clinicians to act on the concerns and manage the situation. Clinical deterioration results in an additional burden for hospitalised patients and families to speak up, seek help and resolve their concerns. Educating patients and families on what to be concerned about and when to notify staff requires a close partnership with clinicians. Clinicians must create an environment that enables patients and families to speak up. They must be alert to both subjective and objective information, to acknowledge and to act on the information accordingly. The consolidated criteria for reporting qualitative research (COREQ) guidelines were used for reporting. The consumer researcher was involved in design, data analysis and publication preparation.

NEural Engine for Discovering Luminous Events (NEEDLE): identifying rare transient candidates in real time from host galaxy images

ABSTRACT Known for their efficiency in analysing large data sets, machine learning-based classifiers have been widely used in wide-field sky survey pipelines. The upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will generate millions of real-time alerts every night, enabling the discovery of large samples of rare events. Identifying such objects soon after explosion will be essential to study their evolution. Using ∼5400 transients from the Zwicky Transient Facility (ZTF) Bright Transient Survey as training and test data, we develop NEEDLE (NEural Engine for Discovering Luminous Events), a novel hybrid (convolutional neural network + dense neural network) classifier to select for two rare classes with strong environmental preferences: superluminous supernovae (SLSNe) preferring dwarf galaxies, and tidal disruption events (TDEs) occurring in the centres of nucleated galaxies. The input data includes (i) cutouts of the detection and reference images, (ii) photometric information contained directly in the alert packets, and (iii) host galaxy magnitudes from Pan-STARRS (Panoramic Survey Telescope and Rapid Response System). Despite having only a few tens of examples of the rare classes, our average (best) completeness on an unseen test set reaches 73 per cent (86 per cent) for SLSNe and 80 per cent (87 per cent) for TDEs. While very encouraging for completeness, this may still result in relatively low purity for the rare transients, given the large class imbalance in real surveys. However, the goal of NEEDLE is to find good candidates for spectroscopic classification, rather than to select pure photometric samples. Our system will be deployed as an annotator on the UK alert broker, Lasair, to provide predictions of real-time alerts from ZTF and LSST to the community.

Improvement of the rapid response system at an acute rehabilitation hospital in New Mexico.

Aim: Enhance the Rapid Response System (RRS) in a free-standing acute rehabilitation hospital (ARH) by improving announcements, crash cart standardizationand role assignments. Materials & methods: Pre-intervention (PreIQ) and post-intervention questionnaires (PostIQ), conducted in English and utilizing a Likert scale, were distributed in-person to clinical staff, yielding a 100% response rate. The questionnaire underwent no prior testing. The PreIQ were disseminated in February 2021, and PostIQ in December 2022. Results: PostIQ illustrated theimprovement of audibility and improved the clarity of roles. The training positively impacted the RRS in the ARH. Conclusion: This study highlights the value of continuous RRS improvement in ARHs. Interventions led to notable enhancements, emphasizing the need for sustained efforts and future research on broader implementation.

Risk Factors for Deterioration Events in the Pediatric Acute Care Setting.

Rapid response system (RRS) activations resulting in emergency transfers (ETs) and codes outside the ICU are associated with increased mortality and length of stay. We aimed to evaluate the patient and care team characteristics of RRS activations resulting in ETs and codes outside the ICU (together classified as "deterioration events") versus those that did not result in a deterioration event. For each RRS activation at our institution from 2019 to 2021, data were gathered on patient demographics and medical diagnoses, care team and treatment factors, and ICU transfer. Descriptive statistics, bivariate analyses, and multivariable logistic regression using a backward elimination model selection method were performed to assess potential risk factors for deterioration events. Over the 3-year period, 1765 RRS activations were identified. Fifty-three (3%) activations were deemed acute care codes, 64 (4%) were noncode ETs, 921 (52%) resulted in nonemergent transfers to an ICU, and 727 (41%) patients remained in an acute care unit. In a multivariable model, any complex chronic condition (adjusted odds ratio, 6.26; 95% confidence interval, 2.83-16.60) and hematology/oncology service (adjusted odds ratio, 2.19; 95% confidence interval, 1.28-3.74) were independent risk factors for a deterioration event. Patients with medical complexity and patients on the hematology/oncology service had a higher risk of deterioration events than other patients with RRS activations. Further analyzing how our hospital evaluates and treats these specific patient populations is critical as we develop targeted interventions to reduce deterioration events.

Rapid response system for critically ill patients with haematological malignancies: A pre- and post-intervention study.

This study aimed to determine whether implementing a rapid response system (RRS) is associated with improved short-term outcomes in critically ill patients with haematological malignancies. Our monocentric pre- versus post-intervention study was conducted between January 2012 and April 2020. RRS was activated at early signs of haemodynamic or respiratory failure. The primary outcome was the reduction in Sequential Organ Failure Assessment (SOFA) score on Day 3 after intensive care unit (ICU) admission. Secondary outcomes included time to ICU admission and mortality. A total of 209 patients with a median age of 59 years were enrolled (108 in the pre-intervention period and 101 in the post-intervention period). 22% of them had received an allogeneic transplant. The post-intervention period was associated with a shorter time to ICU admission (195 vs. 390 min, p < .001), a more frequent favourable trend in SOFA score (57% vs. 42%, adjusted odds ratio, 2.02, 95% confidence interval, 1.09 to 3.76), no significant changes in ICU (22% vs. 26%, p = .48) and 1-year (62% vs. 58%, p = .62) mortality rates. Detection of early organ failure and activation of an RRS was associated with faster ICU admission and lower SOFA scores on Day 3 of admission in critically ill patients with haematological malignancies.