Differences in vital signs between elderly and nonelderly patients prior to ward cardiac arrest

2024 RECOVER Guidelines: Monitoring. Evidence and knowledge gap analysis with treatment recommendations for small animal CPR

OBJECTIVE

To systematically review evidence on and devise treatment recommendations for patient monitoring before, during, and following CPR in dogs and cats, and to identify critical knowledge gaps.

DESIGN

Standardized, systematic evaluation of literature pertinent to peri-CPR monitoring following Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. Prioritized questions were each reviewed by Evidence Evaluators, and findings were reconciled by Monitoring Domain Chairs and Reassessment Campaign on Veterinary Resuscitation (RECOVER) Co-Chairs to arrive at treatment recommendations commensurate to quality of evidence, risk:benefit relationship, and clinical feasibility. This process was implemented using an Evidence Profile Worksheet for each question that included an introduction, consensus on science, treatment recommendations, justification for these recommendations, and important knowledge gaps. A draft of these worksheets was distributed to veterinary professionals for comment for 4 weeks prior to finalization.

SETTING

Transdisciplinary, international collaboration in university, specialty, and emergency practice.

RESULTS

Thirteen questions pertaining to hemodynamic, respiratory, and metabolic monitoring practices for identification of cardiopulmonary arrest, quality of CPR, and postcardiac arrest care were examined, and 24 treatment recommendations were formulated. Of these, 5 recommendations pertained to aspects of end-tidal CO2 (ETco2) measurement. The recommendations were founded predominantly on very low quality of evidence, with some based on expert opinion.

CONCLUSIONS

The Monitoring Domain authors continue to support initiation of chest compressions without pulse palpation. We recommend multimodal monitoring of patients at risk of cardiopulmonary arrest, at risk of re-arrest, or under general anesthesia. This report highlights the utility of ETco2 monitoring to verify correct intubation, identify return of spontaneous circulation, evaluate quality of CPR, and guide basic life support measures. Treatment recommendations further suggest intra-arrest evaluation of electrolytes (ie, potassium and calcium), as these may inform outcome-relevant interventions.

Eleven years of experience in operating a pediatric rapid response system at a children's hospital in South Korea

BACKGROUND

Various rapid response systems have been developed to detect clinical deterioration in patients. Few studies have evaluated single-parameter systems in children compared to scoring systems. Therefore, in this study we evaluated a single-parameter system called the acute response system (ARS).

METHODS

This retrospective study was performed at a tertiary children's hospital. Patients under 18 years old admitted from January 2012 to August 2023 were enrolled. ARS parameters such as systolic blood pressure, heart rate, respiratory rate, oxygen saturation, and whether the ARS was activated were collected. We divided patients into two groups according to activation status and then compared the occurrence of critical events (cardiopulmonary resuscitation or unexpected intensive care unit admission). We evaluated the ability of ARS to predict critical events and calculated compliance. We also analyzed the correlation between each parameter that activates ARS and critical events.

RESULTS

The critical events prediction performance of ARS has a specificity of 98.5%, a sensitivity of 24.0%, a negative predictive value of 99.6%, and a positive predictive value of 8.1%. The compliance rate was 15.6%. Statistically significant increases in the risk of critical events were observed for all abnormal criteria except low heart rate. There was no significant difference in the incidence of critical events.

CONCLUSIONS

ARS, a single parameter system, had good specificity and negative predictive value for predicting critical events; however, sensitivity and positive predictive value were not good, and medical staff compliance was poor.

Continuous EEG Characteristics in Critically ill Patients Presenting With Seizures Prior to Death From Cardiac Arrest

Background: There have been limited reports about brain activity during cardiac arrest. Here we report 4 patients presenting with seizure who had cardiac arrest leading to their deaths while being on continuous video-EEG (cVEEG) monitoring and one-lead cardiac telemetry. Purpose: We illustrate characteristic stepwise EEG and EKG changes in these critically ill patients prior to their death. Research Design/Study Sample: All patients showed progressive broad spectrum of cardiac arrhythmias at or before the beginning of EEG suppression while there were no such changes seen in a control group of 4 randomly selected patients without cardiac arrest who had seizure on presentation and underwent cVEEG monitoring. Data Collection and Results: There was a progressive decline in EEG potentials associated with decreasing heart rate starting from the posterior region, more pronounced on the left, progressing to complete unilateral deactivation of the left fronto-central head regions while the right-sided networks became hyperactive before bilateral deactivation by the time of asystole. Conclusions: This case series provides a rare opportunity to compare EEG and EKG changes in patients who died while being on continuous EEG and EKG monitoring from hours to minutes prior to cardiac arrest and death.

Is Modified Early Warning Score associated with clinical outcomes of patients admitted to a university internal medicine ward?

OBJECTIVE

To assess the MEWS association with the clinical outcomes (CO) of patients admitted to an internal medicine ward (IMW) at a Brazilian university hospital (UH).

INTRODUCTION

It is important to quickly identify patients with clinical deterioration, especially in wards. The health team must recognize and act before the situation becomes an adverse event. In Brazil, nurses' work to overcome performance myths and the application of standardized predictive scales for patients in wards is still limited.

DESIGN

An observational cohort study designed and developed by a registered nurse that followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist.

METHODS

Data were collected from the IMW of a UH located in the city of São Paulo, Brazil (2017). An ROC curve was calculated to strengthen the use of a MEWS of < or ≥ 4 as a cutoff. CO of the two subgroups were compared.

RESULTS

Three hundred patients completed the study; their vital signs were recorded consecutively throughout hospitalization in the IMW. The highest MEWS value each day was considered for analysis. Scores < 4 were significantly associated with a higher probability of hospital discharge, a lower chance of transfer to the ICU, a lower total number of days of hospitalization, and a lower risk of death. Score ≥ 4 had worse CO (orotracheal intubation and cardiac monitoring), transfer to the ICU, and increased risk of death.

CONCLUSION

Scores < 4 were associated with positive outcomes, while scores ≥ 4 were associated with negative outcomes. MEWS can help prioritize interventions, increase certainty in decision-making, and improve patient safety, especially in a teaching IMW with medical teams undergoing professional development, thereby ensuring the central role of the nursing team in Brazil.

RELEVANCE FOR CLINICAL PRACTICE

MEWS aid nurses in identifying and managing patients, prioritizing interventions through assertive decision-making.

Early warning scores and trigger recommendations must be used with care in older home nursing care patients: Results from an observational study

AIMS

To explore modified early warning scores (MEWSs) and deviating vital signs among older home nursing care patients to determine whether the MEWS trigger recommendations were adhered to in cases of where registered nurses (RNs) suspected acute functional decline.

DESIGN

Prospective observational study with a descriptive, explorative design.

METHODS

Participants were included from April 2018 to February 2019. Demographic, health-related and clinical data were collected over a 3-month period.

RESULTS

In all, 135 older patients participated. Median MEWS (n = 444) was 1 (interquartile range (IQR) 1-2). Frequently deviating vital signs were respiratory (88.8%) and heart rate (15.3%). Median habitual MEWS (n = 51) was 1 (IQR 0-1). Deviating vital signs were respiratory (72.5%) and heart rate (19.6%). A significant difference between habitual MEWS and MEWS recorded in cases of suspected functional decline was found (p = 0.002). MEWS' trigger recommendations were adhered to in 68.9% of all MEWS measurements.

Differential screen and treatment of vestibular dysfunction in an elderly patient: A case report

BACKGROUND/PURPOSE

Concussion sequelae in the elderly is under recognized and negatively impacts quality of life. Labyrinthine concussion (LC) is an uncommon diagnosis, as is multiple canal (MC) benign paroxysmal positional vertigo (BPPV). This case report highlights physical therapist (PT) evaluation and treatment of an elderly male misdiagnosed with LC and successfully treated for MC BPPV.

CASE DESCRIPTION

A 72 year old male presented to his PT 23 days after falling off a ladder, resulting in a mild traumatic brain injury (mTBI). Diagnosed with LC, he was referred to PT due to ongoing symptoms of "falling backwards," poor gait, and diminished mobility. PT examination revealed an atypical BPPV. Thus, the patient was treated in two PT visits, which included canalith repositioning techniques and neuromuscular reeducation.

OUTCOMES

The PT diagnosis was MC BPPV, including the right lateral and left posterior semicircular canals. Initial positive findings of Head Impulse Test, Bow and Lean Test, Dix-Hallpike, and Roll Test were negative on the last visit. Patient-Specific Functional Scale improved from 0 to 9.9 (10 being no limitations). The patient progressed from minimum assistance to independence in bed mobility, transfers, gait, and previous activities.

DISCUSSION

The patient's presentation was atypical in signs and symptoms with a diagnosis of LC. PT examination and intervention successfully resolved the patient's signs and symptoms within two visits. Further research is needed regarding identification and treatment of elderly individuals with head injuries, such as MC BPPV, as well as the efficacy of a PT seeing patients shortly after mTBI.

Prevalence and clinical significance of point of care elevated lactate at emergency admission in older patients: a prospective study

OBJECTIVE

Patients who are over 65 years old represent up to 24% of emergency department (ED) admissions. They are at increased risk of under-triage due to impaired physiological responses. The primary objective of this study was to assess the prevalence of elevated lactate by point of care testing (POCT) in this population. The secondary objective was to assess the additional value of lactate level in predicting an early poor outcome, as compared to and combined with common clinical scores and triage scales.

METHODS

This monocentric prospective study recruited ED patients who were over 65 years old between July 19th 2019 and June 17th 2020. Patients consulting for seizures or needing immediate assessment were excluded. POCT lactates were considered elevated if ≥ 2.5 mmol/L. A poor outcome was defined based on certain complications or therapeutic decisions.

RESULTS

In total, 602 patients were included; 163 (27.1%) had elevated lactate and 44 (7.3%) had a poor outcome. There was no association between poor outcome and lactate level. Modified Early Warning Score (MEWS) was significantly associated with poor outcome, alongside National Early Warning Score (NEWS). Logistic regression also associated lactate level combined with MEWS and poor outcome.

CONCLUSION

The prevalence of elevated lactate was 27.1%. Lactate level alone or combined with different triage scales or clinical scores such as MEWS, NEWS and qSOFA was not associated with prediction of a poor outcome. MEWS alone performed best in predicting poor outcome. The usefulness of POCT lactate measurement at triage is questionable in the population of 65 and above.

A conceptual IoT-based early-warning architecture for remote monitoring of COVID-19 patients in wards and at home

Due to the COVID-19 pandemic, health services around the globe are struggling. An effective system for monitoring patients can improve healthcare delivery by avoiding in-person contacts, enabling early-detection of severe cases, and remotely assessing patients' status. Internet of Things (IoT) technologies have been used for monitoring patients' health with wireless wearable sensors in different scenarios and medical conditions, such as noncommunicable and infectious diseases. Combining IoT-related technologies with early-warning scores (EWS) commonly utilized in infirmaries has the potential to enhance health services delivery significantly. Specifically, the NEWS-2 has been showing remarkable results in detecting the health deterioration of COVID-19 patients. Although the literature presents several approaches for remote monitoring, none of these studies proposes a customized, complete, and integrated architecture that uses an effective early-detection mechanism for COVID-19 and that is flexible enough to be used in hospital wards and at home. Therefore, this article's objective is to present a comprehensive IoT-based conceptual architecture that addresses the key requirements of scalability, interoperability, network dynamics, context discovery, reliability, and privacy in the context of remote health monitoring of COVID-19 patients in hospitals and at home. Since remote monitoring of patients at home (essential during a pandemic) can engender trust issues regarding secure and ethical data collection, a consent management module was incorporated into our architecture to provide transparency and ensure data privacy. Further, the article details mechanisms for supporting a configurable and adaptable scoring system embedded in wearable devices to increase usefulness and flexibility for health care professions working with EWS.

Artificial intelligence in critically ill diabetic patients: current status and future prospects

Recent years have witnessed increasing numbers of artificial intelligence (AI) based applications and devices being tested and approved for medical care. Diabetes is arguably the most common chronic disorder worldwide and AI is now being used for making an early diagnosis, to predict and diagnose early complications, increase adherence to therapy, and even motivate patients to manage diabetes and maintain glycemic control. However, these AI applications have largely been tested in non-critically ill patients and aid in managing chronic problems. Intensive care units (ICUs) have a dynamic environment generating huge data, which AI can extract and organize simultaneously, thus analysing many variables for diagnostic and/or therapeutic purposes in order to predict outcomes of interest. Even non-diabetic ICU patients are at risk of developing hypo or hyperglycemia, complicating their ICU course and affecting outcomes. In addition, to maintain glycemic control frequent blood sampling and insulin dose adjustments are required, increasing nursing workload and chances of error. AI has the potential to improve glycemic control while reducing the nursing workload and errors. Continuous glucose monitoring (CGM) devices, which are Food and Drug Administration (FDA) approved for use in non-critically ill patients, are now being recommended for use in specific ICU populations with increased accuracy. AI based devices including artificial pancreas and CGM regulated insulin infusion system have shown promise as comprehensive glycemic control solutions in critically ill patients. Even though many of these AI applications have shown potential, these devices need to be tested in larger number of ICU patients, have wider availability, show favorable cost-benefit ratio and be amenable for easy integration into the existing healthcare systems, before they become acceptable to ICU physicians for routine use.

Comparison of Diagnostic Accuracies of qSOFA, NEWS, and MEWS to Identify Sepsis in Older Inpatients With Suspected Infection

OBJECTIVES

To determine and compare the accuracies of the quick Sequential (Sepsis-related) Organ Failure Assessment (qSOFA) and Modified and National Early Warning Scores (NEWS and MEWS) to identify sepsis in older inpatients with suspected infection.

DESIGN

Prospective diagnostic accuracy study.

SETTING AND PARTICIPANTS

Patients admitted to an acute geriatric unit of an Italian University Hospital with at least one sepsis risk factor and suspected infection defined as antibiotic prescription and associated culture test during hospital stay.

METHODS

Sepsis diagnosis was defined as the presence on discharge documents of International Classification of Diseases, Ninth revision, Clinical Modification codes for severe sepsis, septic shock, or for infection and acute organ disfunction. For each patient, clinical parameters were evaluated at least twice daily throughout hospital stay; qSOFA, NEWS, and MEWS were derived, and worst scores recorded. Positive cutoffs were set at ≥2, ≥7, and ≥5, respectively. Sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), and positive and negative likelihood ratios, as well as areas under the receiver operating characteristic curve (AUROCs) were calculated.

RESULTS

Among 230 geriatric patients with suspected infection at risk for sepsis (median age 86 years, 49% women), 30.9% had a sepsis diagnosis. A qSOFA ≥2 was recorded in 111 (48.3%) patients, a MEWS ≥5 in 65 (28.3%), and a NEWS ≥7 in 115 (50.0%). The qSOFA showed the highest sensitivity [81.7%, 95% confidence interval (CI) 71.7%-89.5%], but low specificity (66.7%, 95% CI 59.1%-73.7%), resulting in a high NPV (89.1%; 95% CI 82.7%-93.8%) and poor PPV (52.3%, 95% CI 43.0%-61.4%). The AUROC for qSOFA was 0.76 (95% CI 0.69-0.83), comparable with that of NEWS (0.74, 95% CI 0.67-0.81, P = .44), but significantly higher than that of MEWS (0.70, 95% CI 0.63-0.77, P = .04).

CONCLUSIONS AND IMPLICATIONS

Repeated qSOFA determinations are useful to rule out sepsis in geriatric inpatients with suspected infection, but poorly support its diagnosis due to low specificity. More complex MEWS and NEWS do not perform better. Implementation of clinical scores to reliably identify sepsis in older patients is urgently needed.

Symptom Prevalence of Anxiety and Depression in Older Cardiac Arrest Survivors: A Comparative Nationwide Register Study

Knowledge about psychological distress in older cardiac arrest (CA) survivors is sparse, and the lack of comparisons with general populations make it difficult to draw any strong conclusions about prevalence and potential changes caused by CA. Our aim was to compare psychological distress between older CA survivors and a general population. This study included survivors 65–80 years old and an age- and sex-matched general population. Data on survivors was collected from the Swedish Register of Cardiopulmonary Resuscitation. The Hospital Anxiety and Depression Scale was used to measure psychological distress. Data were analyzed with non-parametric statistics. The final sample included 1027 CA survivors and 1018 persons from the general population. In both groups, the mean age was 72 years (SD = 4) and 28% were women. The prevalence of anxiety was 9.9% for survivors and 9.5% for the general population, while the corresponding prevalence for depression was 11.3% and 11.5% respectively. Using the cut-off scores, no significant differences between the groups were detected. However, CA survivors reported significantly lower symptom levels using the subscale scores (ΔMdn = 1, p < 0.001). In conclusion, the CA survivors did not report higher symptom levels of anxiety and depression than the general population. However, since psychological distress is related to poor quality-of-life and recovery, screening for psychological distress remains important.

Incidence of in-hospital cardiac arrest at general wards before and after implementation of an early warning score

BACKGROUND

In order to reduce the incidence of in-hospital cardiac arrest (IHCA) at general wards, medical emergency teams (MET) were implemented in the Capital Region of Denmark in 2012 as the efferent part of a track and trigger system. The National Early Warning Score (NEWS) system became the afferent part. This study aims at investigating the incidence of IHCA at general wards before and after the implementation of the NEWS system.

MATERIAL AND METHODS

We included patients at least 18 years old with IHCA at general wards in our hospital in the periods of 2006 to 2011 (pre-EWS group) and 2013 to 2018 (post-EWS group). Data was obtained from a local database and the National In-Hospital Cardiac Arrest Registry (DANARREST). We calculated incidence rate ratios (IRR) for IHCA at general wards with 95% confidence interval (95% CI). Odds ratios (OR) for return of spontaneous circulation (ROSC) and 30-day survival were also calculated with 95% CI.

RESULTS

A total of 444 IHCA occurred before the implementation of NEWS at general wards while 494 IHCA happened afterwards. The incidence rate of IHCA at general wards was 1.13 IHCA per 1000 admissions in the pre-EWS group (2006-2011) and 1.11 IHCA per 1000 admissions in the post-EWS group (2013-2018). The IRR between the two groups was 0.98 (95% CI [0.86;1.11], p = 0.71). The implementation did not affect the chance of ROSC with a crude OR of 1.14 (95% CI [0.88;1.47], p = 0.32) nor did it change the 30-day survival with a crude OR 1.30 (95% CI [0.96;1.75], p = 0.09).

CONCLUSION

Implementation of the EWS system at our hospital did not decrease the incidence rate of in-hospital cardiac arrest at general wards.

European Resuscitation Council Guidelines 2021: Systems saving lives

The European Resuscitation Council (ERC) has produced these Systems Saving Lives guidelines, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include chain of survival, measuring performance of resuscitation, social media and smartphones apps for engaging community, European Restart a Heart Day, World Restart a Heart, KIDS SAVE LIVES campaign, lower-resource setting, European Resuscitation Academy and Global Resuscitation Alliance, early warning scores, rapid response systems, and medical emergency team, cardiac arrest centres and role of dispatcher.

Clinical decision-making in older adults following emergency admission to hospital. Derivation and validation of a risk stratification score: OPERA

OBJECTIVES OF THE STUDY

Demographic changes alongside medical advances have resulted in older adults accounting for an increasing proportion of emergency hospital admissions. Current measures of illness severity, limited to physiological parameters, have shortcomings in this cohort, partly due to patient complexity. This study aimed to derive and validate a risk score for acutely unwell older adults which may enhance risk stratification and support clinical decision-making.

METHODS

Data was collected from emergency admissions in patients ≥65 years from two UK general hospitals (April 2017- April 2018). Variables underwent regression analysis for in-hospital mortality and independent predictors were used to create a risk score. Performance was assessed on external validation. Secondary outcomes included seven-day mortality and extended hospital stay.

RESULTS

Derivation (n = 8,974) and validation (n = 8,391) cohorts were analysed. The model included the National Early Warning Score 2 (NEWS2), clinical frailty scale (CFS), acute kidney injury, age, sex, and Malnutrition Universal Screening Tool. For mortality, area under the curve for the model was 0.79 (95% CI 0.78-0.80), superior to NEWS2 0.65 (0.62-0.67) and CFS 0.76 (0.74-0.77) (P<0.0001). Risk groups predicted prolonged hospital stay: the highest risk group had an odds ratio of 9.7 (5.8-16.1) to stay >30 days.

CONCLUSIONS

Our simple validated model (Older Persons' Emergency Risk Assessment [OPERA] score) predicts in-hospital mortality and prolonged length of stay and could be easily integrated into electronic hospital systems, enabling automatic digital generation of risk stratification within hours of admission. Future studies may validate the OPERA score in external populations and consider an impact analysis.

The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise

Respiratory rate is a fundamental vital sign that is sensitive to different pathological conditions (e.g., adverse cardiac events, pneumonia, and clinical deterioration) and stressors, including emotional stress, cognitive load, heat, cold, physical effort, and exercise-induced fatigue. The sensitivity of respiratory rate to these conditions is superior compared to that of most of the other vital signs, and the abundance of suitable technological solutions measuring respiratory rate has important implications for healthcare, occupational settings, and sport. However, respiratory rate is still too often not routinely monitored in these fields of use. This review presents a multidisciplinary approach to respiratory monitoring, with the aim to improve the development and efficacy of respiratory monitoring services. We have identified thirteen monitoring goals where the use of the respiratory rate is invaluable, and for each of them we have described suitable sensors and techniques to monitor respiratory rate in specific measurement scenarios. We have also provided a physiological rationale corroborating the importance of respiratory rate monitoring and an original multidisciplinary framework for the development of respiratory monitoring services. This review is expected to advance the field of respiratory monitoring and favor synergies between different disciplines to accomplish this goal.

Implementation of the National Early Warning Score in UK care homes: a qualitative evaluation

BACKGROUND

The National Early Warning Score (NEWS) is a tool for identifying and responding to acute illness. When used in care homes, staff measure residents' vital signs and record them on a tablet computer, which calculates a NEWS to share with health services. This article outlines an evaluation of NEWS implementation in care homes across one clinical commissioning group area in northern England.

AIM

To identify challenges to implementation of NEWS in care homes.

DESIGN AND SETTING

Qualitative analysis of interviews conducted with 15 staff members from six care homes, five health professionals, and one clinical commissioning group employee.

METHOD

Interviews were intended to capture people's attitudes and experiences of using the intervention. Following an inductive thematic analysis, data were considered deductively against normalisation process theory constructs to identify the challenges and successes of implementing NEWS in care homes.

RESULTS

Care home staff and other stakeholders acknowledged that NEWS could enhance the response to acute illness, improve communication with the NHS, and increase the confidence of care home staff. However, the implementation did not account for the complexity of either the intervention or the care home setting. Challenges to engagement included competing priorities, insufficient training, and shortcomings in communication.

CONCLUSION

This evaluation highlights the need to involve care home staff and the primary care services that support them when developing and implementing interventions in care homes. The appropriateness and value of NEWS in non-acute settings requires ongoing monitoring.

Deep-learning approaches to identify critically Ill patients at emergency department triage using limited information

STUDY OBJECTIVE

Triage quickly identifies critically ill patients, facilitating timely interventions. Many emergency departments (EDs) use emergency severity index (ESI) or abnormal vital sign triggers to guide triage. However, both use fixed thresholds, and false activations are costly. Prior approaches using machinelearning have relied on information that is often unavailable during the triage process. We examined whether deep-learning approaches could identify critically ill patients only using data immediately available at triage.

METHODS

We conducted a retrospective, cross-sectional study at an urban tertiary care center, from January 1, 2012-January 1, 2020. De-identified triage information included structured (age, sex, initial vital signs) and textual (chief complaint) data, with critical illness (mortality or ICU admission within 24 hours) as the outcome. Four progressively complex deep-learning models were trained and applied to triage information from all patients. We compared the accuracy of the models against ESI as the standard diagnostic test, using area under the receiver-operator curve (AUC).

RESULTS

A total of 445,925 patients were included, with 60,901 (13.7%) critically ill. Vital sign thresholds identified critically ill patients with AUC 0.521 (95% confidence interval [CI] = 0.519-0.522), and ESI <3 demonstrated AUC 0.672 (95% CI = 0.671-0.674), logistic regression classified patients with AUC 0.803 (95% CI = 0.802-0.804), 2-layer neural network with structured data with AUC 0.811 (95% CI = 0.807-0.815), gradient tree boosting with AUC 0.820 (95% CI = 0.818-0.821), and the neural network model with textual data with AUC 0.851 (95% CI = 0.849-0.852). All successive increases in AUC were statistically significant.

CONCLUSION

Deep-learning techniques represent a promising method of augmenting triage, even with limited information. Further research is needed to determine if improved predictions yield clinical and operational benefits.

Characteristics of non-conveyed patients in emergency medical services (EMS): a one-year prospective descriptive and comparative study in a region of Sweden

Background

There has been an increasing demand for emergency medical services (EMS), and a growing number of patients are not conveyed; i.e., they are referred to levels of care other than ambulance conveyance to the emergency department. Patient safety issues have been raised regarding the ability of EMS to decide not to convey patients. To improve non-conveyance guidelines, information is needed about patients who are not conveyed by EMS. Therefore, the purpose of this study was to describe and compare the proportion and characteristics of non-conveyed EMS patients, together with assignment data.

Methods

A descriptive and comparative consecutive cohort design was undertaken. The decision of whether to convey patients was made by EMS according to a region-specific non-conveyance guideline. Non-conveyed patients’ medical record data were prospectively gathered from February 2016 to January 2017. Analyses was conducted using the chi-squared test, two-sample t test, proportion test and Mann-Whitneys U-test.

Results

Out of the 23,250 patients served during the study period, 2691 (12%) were not conveyed. For non-conveyed adults, the most commonly used Emergency Signs and Symptoms (ESS) codes were unspecific symptoms/malaise, abdomen/flank/groin pain, and breathing difficulties. For non-conveyed children, the most common ESS codes were breathing difficulties and fever of unclear origin. Most of the non-conveyed patients had normal vital signs. Half of all patients with a designated non-conveyance level of care were referred to self-care. There were statistically significant differences between men and women.

Conclusions

Fewer patients were non-conveyed in the studied region compared to national and international non-conveyance rates. The differences seen between men and women were not of clinical significance. Follow-up studies are needed to understand what effect patient outcome so that guidelines might improve.

Value of laboratory results in addition to vital signs in a machine learning algorithm to predict in-hospital cardiac arrest: A single-center retrospective cohort study

BACKGROUND

Although machine learning-based prediction models for in-hospital cardiac arrest (IHCA) have been widely investigated, it is unknown whether a model based on vital signs alone (Vitals-Only model) can perform similarly to a model that considers both vital signs and laboratory results (Vitals+Labs model).

METHODS

All adult patients hospitalized in a tertiary care hospital in Japan between October 2011 and October 2018 were included in this study. Random forest models with/without laboratory results (Vitals+Labs model and Vitals-Only model, respectively) were trained and tested using chronologically divided datasets. Both models use patient demographics and eight-hourly vital signs collected within the previous 48 hours. The primary and secondary outcomes were the occurrence of IHCA in the next 8 and 24 hours, respectively. The area under the receiver operating characteristic curve (AUC) was used as a comparative measure. Sensitivity analyses were performed under multiple statistical assumptions.

RESULTS

Of 141,111 admitted patients (training data: 83,064, test data: 58,047), 338 had an IHCA (training data: 217, test data: 121) during the study period. The Vitals-Only model and Vitals+Labs model performed comparably when predicting IHCA within the next 8 hours (Vitals-Only model vs Vitals+Labs model, AUC = 0.862 [95% confidence interval (CI): 0.855-0.868] vs 0.872 [95% CI: 0.867-0.878]) and 24 hours (Vitals-Only model vs Vitals+Labs model, AUC = 0.830 [95% CI: 0.825-0.835] vs 0.837 [95% CI: 0.830-0.844]). Both models performed similarly well on medical, surgical, and ward patient data, but did not perform well for intensive care unit patients.

CONCLUSIONS

In this single-center study, the machine learning model predicted IHCAs with good discrimination. The addition of laboratory values to vital signs did not significantly improve its overall performance.

Significance of body temperature in elderly patients with sepsis

Background

Elderly patients have a blunted host response, which may influence vital signs and clinical outcomes of sepsis. This study was aimed to investigate whether the associations between the vital signs and mortality are different in elderly and non-elderly patients with sepsis.

Methods

This was a retrospective observational study. A Japanese multicenter sepsis cohort (FORECAST, n = 1148) was used for the discovery analyses. Significant discovery results were tested for replication using two validation cohorts of sepsis (JAAMSR, Japan, n = 624; SPH, Canada, n = 1004). Patients were categorized into elderly and non-elderly groups (age ≥ 75 or < 75 years). We tested for association between vital signs (body temperature [BT], heart rate, mean arterial pressure, systolic blood pressure, and respiratory rate) and 90-day in-hospital mortality (primary outcome).

Results

In the discovery cohort, non-elderly patients with BT < 36.0 °C had significantly increased 90-day mortality (P = 0.025, adjusted hazard ratio 1.70, 95% CI 1.07–2.71). In the validation cohorts, non-elderly patients with BT < 36.0 °C had significantly increased mortality (JAAMSR, P = 0.0024, adjusted hazard ratio 2.05, 95% CI 1.29–3.26; SPH, P = 0.029, adjusted hazard ratio 1.36, 95% CI 1.03–1.80). These differences were not observed in elderly patients in the three cohorts. Associations between the other four vital signs and mortality were not different in elderly and non-elderly patients. The interaction of age and hypothermia/fever was significant (P < 0.05).

Conclusions

In septic patients, we found mortality in non-elderly sepsis patients was increased with hypothermia and decreased with fever. However, mortality in elderly patients was not associated with BT. These results illuminate the difference in the inflammatory response of the elderly compared to non-elderly sepsis patients.

Vital sign abnormalities as predictors of clinical deterioration in subacute care patients: A prospective case-time-control study

BACKGROUND

Emergency interhospital transfers from inpatient subacute care to acute care occur in 8% to 17.4% of admitted patients and are associated with high rates of acute care readmission and in-hospital mortality. Serious adverse events in subacute care (rapid response team or cardiac arrest team calls) and increased nursing surveillance are the strongest known predictors of emergency interhospital transfer from subacute to acute care hospitals. However, the epidemiology of clinical deterioration across sectors of care, and specifically in subacute care is not well understood.

OBJECTIVES

To explore the trajectory of clinical deterioration in patients who did and did not have an emergency interhospital transfer from subacute to acute care; and develop an internally validated predictive model to identify the role of vital sign abnormalities in predicting these emergency interhospital transfers.

DESIGN

This prospective, exploratory cohort study is a subanalysis of data derived from a larger case-time-control study.

SETTING

Twenty-two wards of eight subacute care hospitals in five major health services in Victoria, Australia. All subacute care hospitals were geographically separate from their health services' acute care hospitals.

PARTICIPANTS

All patients with an emergency transfer from inpatient rehabilitation or geriatric evaluation and management unit to an acute care hospital within the same health service were included. Patients receiving palliative care were excluded.

METHODS

Study data were collected between 22 August 2015 and 30 October 2016 by medical record audit. The Cochran-Mantel-Haenszel test and bivariate logistic regression analysis were used to compare cases with controls and to account for health service clustering effect.

RESULTS

Data were collected on 603 transfers (557 patients) and 1160 controls. Adjusted for health service, ≥2 vital sign abnormalities in subacute care (adjusted odds ratio=8.81, 95% confidence intervals:6.36-12.19, p<0.001) and serious adverse events during the first acute care admission (adjusted odds ratio=1.28, 95% confidence intervals:1.08-1.99, p=0.015) were the clinical factors associated with increased risk of emergency interhospital transfer. An internally validated predictive model showed that vital sign abnormalities can fairly predict emergency interhospital transfers from subacute to acute care hospitals.

CONCLUSION

Serious adverse events in acute care should be a key consideration in decisions about the location of subacute care delivery. During subacute care, 15.7% of cases had vital signs fulfilling organisational rapid response team activation criteria, yet missed rapid response team activations were common suggesting that further consideration of the criteria and strategies to optimise recognition and response to clinical deterioration in subacute care are needed.

Cross-sectional centiles of blood pressure by age and sex: a four-hospital database retrospective observational analysis

OBJECTIVES

National guidelines for identifying physiological deterioration and sepsis in hospitals depend on thresholds for blood pressure that do not account for age or sex. In populations outside hospital, differences in blood pressure are known to occur with both variables. Whether these differences remain in the hospitalised population is unknown. This database analysis study aims to generate representative centiles to quantify variations in blood pressure by age and sex in hospitalised patients.

DESIGN

Retrospective cross-sectional observational database analysis.

SETTING

Four near-sea-level hospitals between April 2015 and April 2017 PARTICIPANTS: 75 342 adult patients who were admitted to the hospitals and had at least one set of documented vital sign observations within 24 hours before discharge were eligible for inclusion. Patients were excluded if they died in hospital, had no vital signs 24 hours prior to discharge, were readmitted within 7 days of discharge, had missing age or sex or had no blood pressure recorded.

RESULTS

Systolic blood pressure (SBP) for hospitalised patients increases with age for both sexes. Median SBP increases from 122 (CI: 121.1 to 122.1) mm Hg to 132 (CI: 130.9 to 132.2) mm Hg in men, and 114 (CI: 113.1 to 114.4) mm Hg to 135 (CI: 134.5 to 136.2) mm Hg in women, between the ages of 20 and 90 years. Diastolic blood pressure peaked around 50 years for men 76 (CI: 75.5 to 75.9) mm Hg and women 69 (CI: 69.0 to 69.4) mm Hg. The blood pressure criterion for sepsis, systolic <100 mm Hg, was met by 2.3% of younger (20-30 years) men and 3.5% of older men (81-90 years). In comparison, the criterion was met by 9.7% of younger women and 2.6% of older women.

CONCLUSION

We have quantified variations in blood pressure by age and sex in hospitalised patients that have implications for recognition of deterioration. Nearly 10% of younger women met the blood pressure criterion for sepsis at hospital discharge.

Frailty and Associated Outcomes and Resource Utilization Among Older ICU Patients With Suspected Infection

OBJECTIVES

Suspected infection and sepsis are common conditions seen among older ICU patients. Frailty has prognostic importance among critically ill patients, but its impact on outcomes and resource utilization in older patients with suspected infection is unknown. We sought to evaluate the association between patient frailty (defined as a Clinical Frailty Scale ≥ 5) and outcomes of critically ill patients with suspected infection. We also evaluated the association between frailty and the quick Sequential Organ Failure Assessment score.

DESIGN

Analysis of a prospectively collected registry.

SETTING

Two hospitals within a single tertiary care level hospital system between 2011 and 2016.

PATIENTS

We analyzed 1,510 patients 65 years old or older (at the time of ICU admission) and with suspected infection at the time of ICU admission. Of these, 507 (33.6%) were categorized as "frail" (Clinical Frailty Scale ≥ 5).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The primary outcome was in-hospital mortality. A total of 558 patients (37.0%) died in-hospital. Frailty was associated with increased risk of in-hospital death (adjusted odds ratio, 1.81 [95% CIs, 1.34-2.49]). Frailty was also associated with higher likelihood of discharge to long-term care (adjusted odds ratio, 2.06 [95% CI, 1.50-2.64]) and higher likelihood of readmission within 30 days (adjusted odds ratio, 1.83 [95% CI, 1.38-2.34]). Frail patients had increased ICU resource utilization and total costs. The combination of frailty and quick Sequential Organ Failure Assessment greater than or equal to 2 further increased the risk of death (adjusted odds ratio, 7.54 [95% CI, 5.82-9.90]).

CONCLUSIONS

The presence of frailty among older ICU patients with suspected infection is associated with increased mortality, discharge to long-term care, hospital readmission, resource utilization, and costs. This work highlights the importance of clinical frailty in risk stratification of older ICU patients with suspected infection.

Use of the National Early Warning Score for predicting in-hospital mortality in older adults admitted to the emergency department

Objective

The National Early Warning Score (NEWS), based on the patients’ vital signs, detects clinical deterioration in critically ill patients and is used to reduce the incidence of in-hospital cardiac arrest. However, although mortality prediction based on vital signs may be difficult in older patients, the effectiveness of the NEWS has not yet been evaluated in this population. This study aimed to test the hypothesis that an elevated NEWS at admission increases the mortality risk in older patients admitted to the emergency department (ED).

Methods

We conducted a single-center retrospective study, including patients admitted to the ED between November 2016 and February 2017. We included patients aged >65 years who were admitted to the ED for any medical problem. The NEWS was calculated at the time of ED admission. The primary outcome was in-hospital mortality.

Results

In total, 3,169 patients were included in this study. Median age was 75 years (interquartile range [IQR], 70 to 80 years), and 1,557 (49.1%) patients were male. The in-hospital mortality rate was 5.1% (161 patients). Median NEWS was higher in non-survivors than in survivors (5 [IQR, 3–8] vs. 1 [IQR, 0–3], P<0.001). Multivariate logistic analysis showed that the NEWS was associated with in-hospital mortality, after adjusting for other confounders. The area under the curve of the NEWS for predicting in-hospital mortality was 0.820 (95% confidence interval, 0.806 to 0.833).

Conclusion

Our results show that the NEWS at admission is associated with in-hospital mortality among patients aged >65 years.

Performance of patient acuity rating by rapid response team nurses for predicting short-term prognosis

Background

Although scoring and machine learning methods have been developed to predict patient deterioration, bedside assessment by nurses should not be overlooked. This study aimed to evaluate the performance of subjective bedside assessment of the patient by the rapid response team (RRT) nurses in predicting short-term patient deterioration.

Methods

Patients noticed by RRT nurses based on the vital sign instability, abnormal laboratory results, and direct contact via phone between November 1, 2016, and December 12, 2017, were included. Five RRT nurses visited the patients according to their shifts and assessed the possibility of patient deterioration. Patient acuity rating (PAR), a scale of 1–7, was used as the tool of bedside assessment. Other scores, including the modified early warning score, VitalPAC early warning score, standardised early warning score, and cardiac arrest risk triage, were calculated afterwards. The performance of these scores in predicting mortality and/or intensive care unit admission within 1 day was compared by calculating the area under the receiver operating curve.

Results

A total of 1,426 patients were included in the study, of which 258 (18.1%) died or were admitted to the intensive care unit within 1 day. The area under the receiver operating curve of PAR was 0.87 (95% confidence interval [CI] 0.84–0.89), which was higher than those of modified early warning score (0.66, 95% CI 0.62–0.70), VitalPAC early warning score (0.69, 95% CI 0.66–0.73), standardised early warning score (0.67, 95% CI 0.63–0.70) and cardiac arrest risk triage (0.63, 95% CI 0.59–0.66) (P<0.001).

Conclusions

PAR assessed by RRT nurses can be a useful tool for assessing short-term patient prognosis in the RRT setting.

Aging is independently associated with an increasing normal respiratory rate among an older adult population in a clinical setting: A cross-sectional study

AIM

Clinical prediction scores for older patients are inaccurate, partially because they do not account for the effects of aging on the respiratory rate. The principal aim of the present study was to assess the effects of aging on the normal respiratory rate in older patients in a clinical setting.

METHODS

We recruited 634 participants aged >59 years to <100 years who presented to our hospital (Iwakuni Municipal Miwa Hospital, for regular appointments without any new symptoms. We assessed the relationship between age and respiratory rate using Pearson's correlation coefficient and the Jonckheere-Terpstra test. We carried out multiple linear regression analysis, with sex, age, blood pressure, heart rate and 14 comorbidities as dependent variables, and respiratory rate as the independent variable.

RESULTS

The mean ± standard deviation respiratory rate for all for all participants was 16.1 ± 4.28. The mean ± standard deviation respiratory rates for individuals aged in their 60s, 70s, 80s and 90s were 14.8 ± 4.28, 15.5 ± 3.62, 16.37 ± 4.48 and 17.1 ± 4.45, respectively. Pearson's correlation coefficient between age and respiratory rate was 0.17 (95% confidence interval 0.10-0.25). The Jonckheere-Terpstra test and multiple linear regression analysis showed a significant positive trend between age group and respiratory rate (P < 0.001).

CONCLUSIONS

Although the correlation coefficient between age and respiratory rate was low (R = 0.17), aging was a statistically significant factor in determining the normal respiratory rate in older patients. Furthermore, the respiratory rate increased with age. Geriatr Gerontol Int 2019; 19: 1179-1183.

Novel model for predicting inpatient mortality after emergency admission to hospital in Singapore: retrospective observational study

OBJECTIVES

To identify risk factors for inpatient mortality after patients' emergency admission and to create a novel model predicting inpatient mortality risk.

DESIGN

This was a retrospective observational study using data extracted from electronic health records (EHRs). The data were randomly split into a derivation set and a validation set. The stepwise model selection was employed. We compared our model with one of the current clinical scores, Cardiac Arrest Risk Triage (CART) score.

SETTING

A single tertiary hospital in Singapore.

PARTICIPANTS

All adult hospitalised patients, admitted via emergency department (ED) from 1 January 2008 to 31 October 2017 (n=433 187 by admission episodes).

MAIN OUTCOME MEASURE

The primary outcome of interest was inpatient mortality following this admission episode. The area under the curve (AUC) of the receiver operating characteristic curve of the predictive model with sensitivity and specificity for optimised cut-offs.

RESULTS

15 758 (3.64%) of the episodes were observed inpatient mortality. 19 variables were observed as significant predictors and were included in our final regression model. Our predictive model outperformed the CART score in terms of predictive power. The AUC of CART score and our final model was 0.705 (95% CI 0.697 to 0.714) and 0.817 (95% CI 0.810 to 0.824), respectively.

CONCLUSION

We developed and validated a model for inpatient mortality using EHR data collected in the ED. The performance of our model was more accurate than the CART score. Implementation of our model in the hospital can potentially predict imminent adverse events and institute appropriate clinical management.

Outcomes of Older Hospitalized Patients Requiring Rapid Response Team Activation for Acute Deterioration

OBJECTIVES

Rapid response teams are groups of healthcare providers that have been implemented by many hospitals to respond to acutely deteriorating patients admitted to the hospital wards. Hospitalized older patients are at particular risk of deterioration. We sought to examine outcomes of older patients requiring rapid response team activation.

DESIGN

Analysis of a prospectively collected registry.

SETTING

Two hospitals within a single tertiary care level hospital system between 2012 and 2016.

PATIENTS

Five-thousand nine-hundred ninety-five patients were analyzed. Comparisons were made between older patients (defined as ≥ 75 yr old) and younger patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

All patient information, outcomes, and rapid response team activation information were gathered at the time of rapid response team activation and assessment. The primary outcome was in-hospital mortality, analyzed using multivariate logistic regression. Two-thousand three-hundred nine were older patients (38.5%). Of these, 835 (36.2%) died in-hospital, compared with 998 younger patients (27.1%) (adjusted odds ratio, 1.83 [1.54-2.18]; p < 0.001). Among patients admitted from home, surviving older patients were more likely to be discharged to a long-term care facility (adjusted odds ratio, 2.38 [95% CI, 1.89-3.33]; p < 0.001). Older patients were more likely to have prolonged delay to rapid response team activation (adjusted odds ratio, 1.79 [1.59-2.94]; p < 0.001). Among patients with goals of care allowing for ICU admission, older patients were less likely to be admitted to the ICU (adjusted odds ratio, 0.66 [0.36-0.79]), and less likely to have rapid response team activation during daytime hours (adjusted odds ratio, 0.73 [0.62-0.98]; p < 0.001).

CONCLUSIONS

Older patients with in-hospital deterioration requiring rapid response team activation had increased odds of death and long-term care disposition. Rapid response team activation for older patients was more likely to be delayed, and occur during nighttime hours. These findings highlight the worse outcomes seen among older patients with in-hospital deterioration, identifying areas for future quality improvement.

Rerouting Geriatric Medicine by Complementing Static Frailty Measures With Dynamic Resilience Indicators of Recovery Potential

Medicine is still very inadequate in forecasting recovery of tipping points in health and disease, especially in older adults. However, increasingly, diseases and invasive treatments unexpectedly push older patients with low resilience over their tipping points (TPs). These TPs are the points in human physiology that separate more healthy conditions from disease conditions or malfunctioning of the older human’s subsystems or organs, such as delirium, syncope and falls in old age, which threaten the functioning of the older person as a whole. Either the person may recover from the perturbation induced by such a subsystem TP and the balance of the whole system is restored, or the TP may set in motion a cascade of events driving the system down to a state of more decline, ultimately leading to death. A main unanswered question here is how to predict whether these older persons will recover or not. To improve this TP-recovery-forecasting, intriguing findings on measures of resilience found in other complex biological systems may be translated to humans. New dynamic resilience biomarkers for resilience can enrich clinical prediction for pathophysiological recovery and could test interventions for their effectiveness in improving resilience. Therefore, we hypothesize that dynamic, stimulus-response measures of recovery rate over time, observed after having received a minor stressor in a healthy condition, can be used to quantify recovery potential following subsystem TPs in disease and following invasive treatments in humans and thus the person’s resilience. Current static frailty prognostics can predict risks for death, institutionalization, delirium, falls, and other TP transitions, but it has not been proven that they can predict recovery. Our hypothesis on dynamic indicators of recovery is logical and timely, as it can now be studied with sensor technology to create a fundamentally different approach of variables that may be validated to forecast recovery potential. By generating dynamic measures of systemic resilience over various organ systems, we may subsequently model resilience generically across many chronic diseases, affecting different organ systems. Next, quantifying systemic resilience may reroute scientific and clinical pathways by predicting and preventing irreversible tipping points and by improving recovery by older adults.

Exploring nursing competence to care for older patients in municipal in-patient acute care: A qualitative study

AIM

To identify critical aspects of nursing competence to care for older patients in the context of municipal in-patient acute care.

BACKGROUND

An increasingly complex and advanced primary healthcare system requires attention to the extent of nursing competence in municipal services. However, competence in complex and advanced care settings must be explored using perspectives which acknowledge the complexity of nurses' performance.

DESIGN

A phenomenological hermeneutic, qualitative approach with individual in-depth interviews was used. COREQ reporting guidelines have been applied.

METHODS

A sample of eight nurses and two physicians employed in municipal in-patient acute care units (MAUs) were purposively recruited to participate. Data were collected between May and June of 2017. Analysis and interpretation were conducted systematically in three steps: naïve reading, structural analysis and comprehensive understanding.

FINDINGS

Two main themes were revealed. The first was the following: "The meaning of the individual nursing competence" including the themes "Having competence in clinical assessments, decision-making, and performing interventions"; "Having competence to collaborate, coordinate and facilitate"; and "Being committed." The second was the following: "The meaning of environmental and systemic factors for nursing competence," included the themes "Having professional leadership"; "Having a sufficiently qualified staff"; and "Working in an open, cooperative and professional work environment."

CONCLUSION

Individual nursing competence in MAUs should include the capability to detect patient deterioration and to care for older patients in a holistic perspective. In addition, the professional environmental culture, supportive leadership and systemic factors seemed to be crucial to success.

RELEVANCE TO CLINICAL PRACTICE

This study illustrates the nurses' responsibility for older patients' safety and quality of care in the MAUs. These findings can act as a foundation for the development and adaptation of educational programmes to accommodate requirements for nursing competence in MAUs. The broad perspective of nursing competence can give directions for quality improvements in MAUs.

Risk assessment models for potential use in the emergency department have lower predictive ability in older patients compared to the middle-aged for short-term mortality - a retrospective cohort study

Background

Older patients is a complex group at increased risk of adverse outcomes compared to younger patients, which should be considered in the risk assessment performed in emergency departments. We evaluated whether the predictive ability of different risk assessment models for acutely admitted patients is affected by age.

Methods

Cohort study of middle-aged and older patients. We investigated the accuracy in discriminating between survivors and non-survivors within 7 days of different risk assessment models; a traditional triage algorithm, a triage algorithm with clinical assessment, vital signs, routine biomarkers, and the prognostic biomarker soluble urokinase plasminogen activator receptor (suPAR).

Results

The cohort included 22,653 (53.2%) middle-aged patients (age 40–69 years), and 19,889 (46.8%) older patients (aged 70+ years). Death within 7 days occurred in 139 patients (0.6%) in middle-aged patients and 596 (3.0%) of the older patients. The models based on vital signs and routine biomarkers had the highest area under the curve (AUC), and both were significantly better at discriminating 7-day mortality in middle-aged patients compared to older patients; AUC (95% CI): 0.88 (0.84–0.91), 0.75 (0.72–0.78), P < 0.01, and 0.86 (0.82–0.90), 0.76 (0.73–0.78), P < 0.001. In a subgroup of the total cohort (6.400 patients, 15.0%), the suPAR level was available. suPAR had the highest AUC of all individual predictors with no significant difference between the age groups, but further research in this biomarker is required before it can be used.

Conclusion

The predictive value was lower in older patients compared to middle-aged patients for all investigated models. Vital signs or routine biomarkers constituted the best models for predicting 7-day mortality and were better than the traditional triage model. Hence, the current risk assessment for short-term mortality can be strengthened, but modifications for age should be considered when constructing new risk assessment models in the emergency department.

Electronic supplementary material

The online version of this article (10.1186/s12877-019-1154-7) contains supplementary material, which is available to authorized users.

Prognostic accuracy of the Hamilton Early Warning Score (HEWS) and the National Early Warning Score 2 (NEWS2) among hospitalized patients assessed by a rapid response team

Background

Rapid response teams (RRTs) respond to hospitalized patients experiencing clinical deterioration and help determine subsequent management and disposition. We sought to evaluate and compare the prognostic accuracy of the Hamilton Early Warning Score (HEWS) and the National Early Warning Score 2 (NEWS2) for prediction of in-hospital mortality following RRT activation. We secondarily evaluated a subgroup of patients with suspected infection.

Methods

We retrospectively analyzed prospectively collected data (2012–2016) of consecutive RRT patients from two hospitals. The primary outcome was in-hospital mortality. We calculated the number needed to examine (NNE), which indicates the number of patients that need to be evaluated in order to detect one future death.

Results

Five thousand four hundred ninety-one patients were included, of whom 1837 (33.5%) died in-hospital. Mean age was 67.4 years, and 51.6% were male. A HEWS above the low-risk threshold (≥ 5) had a sensitivity of 75.9% (95% confidence interval (CI) 73.9–77.9) and specificity of 67.6% (95% CI 66.1–69.1) for mortality, with a NNE of 1.84. A NEWS2 above the low-risk threshold (≥ 5) had a sensitivity of 84.5% (95% CI 82.8–86.2), and specificity of 49.0% (95% CI: 47.4–50.7), with a NNE of 2.20. The area under the receiver operating characteristic curve (AUROC) was 0.76 (95% CI 0.75–0.77) for HEWS and 0.72 (95% CI: 0.71–0.74) for NEWS2. Among suspected infection patients (n = 1708), AUROC for HEWS was 0.79 (95% CI 0.76–0.81) and for NEWS2, 0.75 (95% CI 0.73–0.78).

Conclusions

The HEWS has comparable clinical accuracy to NEWS2 for prediction of in-hospital mortality among RRT patients.

Electronic supplementary material

The online version of this article (10.1186/s13054-019-2355-3) contains supplementary material, which is available to authorized users.

Prognostic value of Modified Early Warning Score generated in a Chinese emergency department: a prospective cohort study

OBJECTIVES

This study aimed to validate the performance of the Modified Early Warning Score (MEWS) in a Chinese emergency department and to determine the best cut-off value for in-hospital mortality prediction.

DESIGN

A prospective, single-centred observational cohort study.

SETTING

This study was conducted at a tertiary hospital in South China.

PARTICIPANTS

A total of 383 patients aged 18 years or older who presented to the emergency department from 17 May 2017 through 27 September 2017, triaged as category 1, 2 or 3, were enrolled.

OUTCOMES

The primary outcome was a composite of in-hospital mortality and admission to the intensive care unit. The secondary outcome was using MEWS to predict hospitalised and discharged patients.

RESULTS

A total of 383 patients were included in this study. In-hospital mortality was 13.6% (52/383), and transfer to the intensive care unit was 21.7% (83/383). The area under the receiver operating characteristic curve of MEWS for in-hospital mortality prediction was 0.83 (95% CI 0.786 to 0.881). When predicting in-hospital mortality with the cut-off point defined as 3.5, 158 patients had MEWS >3.5, with a specificity of 66%, a sensitivity of 87%, an accuracy of 69%, a positive predictive value of 28% and a negative predictive value of 97%, respectively.

CONCLUSION

Our findings support the use of MEWS for in-hospital mortality prediction in patients who were triaged category 1, 2 or 3 in a Chinese emergency department. The cut-off value for in-hospital mortality prediction defined in this study was different from that seen in many other studies.

Improving weekend review for trauma and elective orthopaedic patients in the post-operative period

Purpose

Weekend surgery carries higher mortality than weekday surgery, with complications most commonly arising within the first 48 hours. There is a reduced ability to identify complications at the weekend, with early signs going undetected in the absence of thorough early patient review, particularly in the elderly with multiple co-morbidities. Weekend working practices vary amongst UK hospitals and specialties. The weekend effect has been a prominent feature in the literature over the past decade. The purpose of this paper is to identify the number of patients undergoing weekend surgery who receive a Day 1 post-operative review and improve this outcome by implementing an effective change.

Design/methodology/approach

It was observed that not all patients undergoing surgery on a Friday or Saturday at the authors’ District General Hospital were receiving Day 1 post-operative review by a clinician. A retrospective audit was carried out to identify percentage of patients reviewed on post-operative Day 1 at the weekend. A change in handover practice was implemented before re-audit.

Findings

In Phase 1, 54 per cent of patients received Day 1 post-operative reviews at the weekend against a set standard of 100 per cent. A simple change to handover practice was implemented to improve patient safety in the immediate post-operative period resulting in 96 per cent of patients reviewed on Day 1 post-operatively at re-audit.

Originality/value

This study confirms that simple changes in handover practices can produce effective and translatable improvements to weekend working. This further contributes to the body of literature that acknowledges the existence of a weekend effect, but aims to evolve weekend working practices to accommodate improvement within current staffing and resource availability by maximising efficiency and communication.

Evaluation of the efficacy of the National Early Warning Score in predicting in-hospital mortality via the risk stratification

PURPOSE

To investigate the efficacy of the National Early Warning Score (NEWS) in predicting in-hospital mortality.

MATERIALS AND METHODS

This was a retrospective observational study and the electronic medical records of the patients were reviewed based on NEWS at the time of admission.

RESULTS

The performance of NEWS was effective in predicting hospital mortality (area under the curve: 0.765; 95% confidence interval: 0.659-0.846). Based on the Kaplan Meier survival curves, the survival time of patients who are at high risk according to NEWS was significantly shorter than that of patients who are at low risk (p < 0.001). Results of the multivariate Cox proportional hazards regression analysis showed that the hazard ratios of patients who are at medium and high risk based on NEWS were 2.6 and 4.7, respectively (p < 0.001). In addition, our study showed that the combination model that used other factors, such as age and diagnosis, was more effective than NEWS alone in predicting hospital mortality (NEWS: 0.765; combination model: 0.861; p < 0.005).

CONCLUSIONS

NEWS is a simple and useful bedside tool for predicting in-hospital mortality. In addition, the rapid response team must consider other clinical factors as well as screening tools to improve clinical outcomes.

Risk factors for cardiopulmonary and respiratory arrest in medical and surgical hospital patients on opioid analgesics and sedatives

BACKGROUND

Opioid induced respiratory depression is a known cause of preventable death in hospitals. Medications with sedative properties additionally potentiate opioid-induced respiratory and sedative effects, thereby elevating the risk for adverse events. The goal of this study was to determine what specific factors increase the risk of in-hospital cardiopulmonary and respiratory arrest (CPRA) in medical and surgical patients on opioid and sedative therapy.

METHODS

The present study analyzed 14,504,809 medical inpatient and 6,771,882 surgical inpatient discharges reported into the Premier database from 2008 to 2012. Patients were divided in four categories: on opioids; on sedatives; on both opioids and sedatives; and on neither opioids nor sedatives.

RESULTS

During hospital admission, 57% of all medical patients and 90% of all surgical patients were prescribed opioids, sedatives, or both. Surgical patients had a higher incidence of CPRA than medical patients (6.17 vs. 3.77 events per 1000 admissions; Relative Risk: 1.64 [95%CI: 1.62-1.66; p<0.0001). Opioids and sedatives were found to be independent predictors of CPRA (adjusted OR of 2.24 [95%CI: 2.18-2.29] for opioids and adjusted OR 1.80 [95%CI: 1.75-1.85] for sedatives in medical patients, and adjusted OR of 1.12 [95%CI: 1.07-1.16] for opioids and adjusted OR of 1.58 [95%CI: 1.51-1.66] for sedatives in surgical patients), with the highest risk in groups who received both types of medications (adjusted OR of 3.83 [95% CI: 3.74-3.92] in medical patients, and adjusted OR of 2.34 [95% CI: 2.25-2.42] in surgical patients) compared with groups that received neither type of medication. The common risk factors of CPRA in medical and surgical patients receiving both opioids and sedatives were Hispanic origin, mild liver disease, obesity, and COPD. Additionally, medical and surgical groups had their own unique risk factors for CPRA when placed on opioid and sedative therapy.

CONCLUSIONS

Opioids and sedatives are independent and additive predictors of CPRA in both medical and surgical patients. Receiving both classes of medications further exacerbates the risk of CPRA for these patients. By identifying groups at risk among medical and surgical in-hospital patients, this study provides a step towards improving our understanding of how to use opioid and sedative medications safely, which may influence our treatment strategies and outcomes. More precise monitoring of selected high-risk patients may help prevent catastrophic cardiorespiratory complications from these medications. As a retrospective administrative database analysis, this study does not establish the causality or the temporality of the events but rather draws statistically significant associations between the clinical factors and outcomes.

Accuracy of a Wrist-Worn Heart Rate Sensing Device during Elective Pediatric Surgical Procedures

The reliability of wearable photoplethysmography (PPG) sensors to measure heart rate (HR) in hospitalized patients has only been demonstrated in adults. We evaluated the accuracy of HR monitoring with a personal fitness tracker (PFT) in children undergoing surgery. HR monitoring was performed using a wrist-worn PFT (Fitbit Charge HR) in 30 children (8.21 ± 3.09 years) undergoing laparoscopy (n = 8) or open surgery (n = 22). HR values were analyzed preoperatively and during surgery. The accuracy of HR recordings was compared with measurements recorded during continuous electrocardiographic (cECG) monitoring; HRs derived from continuous monitoring with pulse oximetry (SpO2R) were used as a positive control. PFT-derived HR values were in agreement with those recorded during cECG (r = 0.99) and SpO2R (r = 0.99) monitoring. PFT performance remained high in children < 8 years (r = 0.99), with a weight < 30 kg (r = 0.99) and when the HR was < 70 beats per minute (bpm) (r = 0.91) or > 140 bpm (r = 0.99). PFT accuracy was similar during laparoscopy and open surgery, as well as preoperatively and during the intervention (r > 0.9). PFT–derived HR showed excellent accuracy compared with HRs measured by cECG and SpO2R during pediatric surgical procedures. Further clinical evaluation is needed to define whether PFTs can be used in different health care settings.

Assessment of three risk evaluation systems for patients aged ≥70 in East China: performance of SinoSCORE, EuroSCORE II and the STS risk evaluation system

Objectives

To assess and compare the predictive ability of three risk evaluation systems (SinoSCORE, EuroSCORE II and the STS risk evaluation system) in patients aged ≥70, and who underwent coronary artery bypass grafting (CABG) in East China.

Methods

Three risk evaluation systems were applied to 1,946 consecutive patients who underwent isolated CABG from January 2004 to September 2016 in two hospitals. Patients were divided into two subsets according to their age: elderly group (age ≥70) with a younger group (age <70) used for comparison. The outcome of interest in this study was in-hospital mortality. The entire cohort and subsets of patients were analyzed. The calibration and discrimination in total and in subsets were assessed by the Hosmer-Lemeshow and the C statistics respectively.

Results

Institutional overall mortality was 2.52%. The expected mortality rates of SinoSCORE, EuroSCORE II and the STS risk evaluation system were 0.78(0.64)%, 1.43(1.14)% and 0.78(0.77)%, respectively. SinoSCORE achieved the best discrimination (the area under the receiver operating characteristic curve (AUC) = 0.829), followed by the STS risk evaluation system (AUC = 0.790) and EuroSCORE II (AUC = 0.769) in the entire cohort. In the elderly group, the observed mortality rate was 4.82% while it was 1.38% in the younger group. SinoSCORE (AUC = .829) also achieved the best discrimination in the elderly group, followed by the STS risk evaluation system (AUC = .730) and EuroSCORE II (AUC = 0.640) while all three risk evaluation systems all had good performances in the younger group. SinoSCORE, EuroSCORE II and the STS risk evaluation system all achieved positive calibrations in the entire cohort and subsets.

Conclusion

The performance of the three risk evaluation systems was not ideal in the entire cohort. In the elderly group, SinoSCORE appeared to achieve better predictive efficiency than EuroSCORE II and the STS risk evaluation system.

Novel Modification of Potassium Chloride Induced Cardiac Arrest Model for Aged Mice

Experimental cardiac arrest (CA) in aging research is infrequently studied in part due to the limitation of animal models. We aimed to develop an easily performed mouse CA model to meet this need. A standard mouse KCl-induced CA model using chest compressions and intravenous epinephrine for resuscitation was modified by blood withdrawal prior to CA onset, so as to decrease the requisite KCl dose to induce CA by decreasing the circulating blood volume. The modification was then compared to the standard model in young adult mice subjected to 8 min CA. 22-month old mice were then subjected to 8 min CA, resuscitated, and compared to young adult mice. Post-CA functional recovery was evaluated by measuring spontaneous locomotor activity pre-injury, and on post-CA days 1, 2, and 3. Neurological score and brain histology were examined on day 3. Brain elF2α phosphorylation levels were measured at 1 h to verify tissue stress. Compared to the standard model, the modification decreased cardiopulmonary resuscitation duration and increased 3-day survival in young mice. For aged mice, survival was 100 % at 24 h and 54% at 72 h. Neurological deficit was present 3 days post-CA, although more severe versus young mice. Mild neuronal necrosis was present in the cortex and hippocampus. The modified model markedly induced elF2α phosphorylation in both age groups. This modified procedure makes the CA model feasible in aged mice and provides a practical platform for understanding injury mechanisms and developing therapeutics for elderly patients.

Use of wearable devices for post-discharge monitoring of ICU patients: a feasibility study

BACKGROUND

Wearable devices generate signals detecting activity, sleep, and heart rate, all of which could enable detailed and near-continuous characterization of recovery following critical illness.

METHODS

To determine the feasibility of using a wrist-worn personal fitness tracker among patients recovering from critical illness, we conducted a prospective observational study of a convenience sample of 50 stable ICU patients. We assessed device wearability, the extent of data capture, sensitivity and specificity for detecting heart rate excursions, and correlations with questionnaire-derived sleep quality measures.

RESULTS

Wearable devices were worn over a 24-h period, with excellent capture of data. While specificity for the detection of tachycardia was high (98.8%), sensitivity was low to moderate (69.5%). There was a moderate correlation between wearable-derived sleep duration and questionnaire-derived sleep quality (r = 0.33, P = 0.03). Devices were well-tolerated and demonstrated no degradation in quality of data acquisition over time.

CONCLUSIONS

We found that wearable devices could be worn by patients recovering from critical illness and could generate useful data for the majority of patients with little adverse effect. Further development and study are needed to better define and enhance the role of wearables in the monitoring of post-ICU recovery.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT02527408.

Attenuation of the physiological response to infection on adults over 65 years old admitted to the emergency room (ER)

It has been considered that the elderly have clinical manifestations different from the ones observed in middle-age adults during an injury event. This hypothesis has not been extensively explored in sepsis and bacterial infections. Secondary analysis of two prospective studies including 2611 patients over 18 years of age admitted to the emergency room with confirmed or probable bacterial infections and sepsis. The outcome measures were heart rate, respiratory rate, systolic blood pressure, temperature, Glasgow Coma Scale, creatinine, PaO₂/FiO₂ and platelets daily during the first week. Compared to survivors younger than 65, the deceased under 65 had an average heart rate of 12.5 beats per minute per day higher (95% CI 9.32; 15.61), while patients over 65 who died barely had an average 5.7 beats per minute per day higher than the same reference group (95% CI 3.45; 8.06). The systolic blood pressure had a significant decreased in those who died younger than 65, compared to survivors with the same age, in both cohorts (-5.2 mmHg, 95% CI -8.17; -2.23 and -8.5 mmHg, 95% CI -13.48; -3.54, respectively), while those older than 65 who died had a nonsignificant increase (+1.6 mmHg, 95% CI -1.33; 4.62 and +0.1, 95% CI -6.48; 6.72, respectively) compared to the same reference group. The behavior of most clinical and laboratory variables suggests a less pronounced response of subjects above 65 years of age who died 28 days after being diagnosed with sepsis.

Initial disease severity and quality of care of emergency department sepsis patients who are older or younger than 70 years of age

Objective

Due to atypical symptom presentation older patients are more prone to delayed sepsis recognition. We investigated whether initial disease severity before emergency department (ED) treatment (including treatable acute organ dysfunction), quality of ED sepsis care and the impact on mortality was different between patients older and younger than 70 years. If differences exist, improvements are needed for ED management of older patients at risk for sepsis.

Methods

In this observational multicenter study, ED patients who were hospitalized with a suspected infection were stratified by age <70 and ≥70 years. The presence of treatable and potentially reversible acute organ dysfunction was measured by the RO components of the Predisposition, Infection, Response and Organ dysfunction (PIRO) score, reflecting acute sepsis-related organ dysfunction developed before ED presentation. Quality of care, as assessed by the full compliance with nine quality performance measures and the standardized mortality ratio (SMR: observed/expected in-hospital mortality), was compared between older and younger patients.

Results

The RO-components of the PIRO score were 8 (interquartile range; 4–9) in the 833 older patients, twice as high as the 4 (2–8; P<0.001) in the 1537 younger patients. However, full compliance with all nine quality performance measures was achieved in 34.2 (31.0–37.4)% of the older patients, not higher than the 33.0 (30.7–35.4)% in younger patients (P = 0.640). In-hospital mortality was 9.2% (95%-CI, 7.3–11.2) in patients ≥70, twice as high as the 4.6% (3.6–5.6) in patients <70 years, resulting in an SMR (in study period) of ~0.7 in both groups (P>0.05).

Conclusion

Older sepsis patients are sicker at ED presentation but are not treated more expediently or reliably despite their extra acuity The presence of twice as much treatable acute organ dysfunction before ED treatment suggests that acute organ dysfunction is recognized relatively late by general practitioners or patients in the out of hospital setting.

The most commonly used disease severity scores are inappropriate for risk stratification of older emergency department sepsis patients: an observational multi-centre study

Background

Sepsis recognition in older emergency department (ED) patients is difficult due to atypical symptom presentation. We therefore investigated whether the prognostic and discriminative performance of the five most commonly used disease severity scores were appropriate for risk stratification of older ED sepsis patients (≥70 years) compared to a younger control group (<70 years).

Methods

This was an observational multi-centre study using an existing database in which ED patients who were hospitalized with a suspected infection were prospectively included. Patients were stratified by age < 70 and ≥70 years. We assessed the association with in-hospital mortality (primary outcome) and the area under the curve (AUC) with receiver operator characteristics of the Predisposition, Infection, Response, Organ dysfunction (PIRO), quick Sequential Organ Failure Assessment (qSOFA), Mortality in ED Sepsis (MEDS), and the Modified and National Early Warning (MEWS and NEWS) scores.

Results

In-hospital mortality was 9.5% ((95%-CI); 7.4–11.5) in the 783 included older patients, and 4.6% (3.6–5.7) in the 1497 included younger patients. In contrast to younger patients, disease severity scores in older patients associated poorly with mortality. The AUCs of all disease severity scores were poor and ranged from 0.56 to 0.64 in older patients, significantly lower than the good AUC range from 0.72 to 0.86 in younger patients. The MEDS had the best AUC (0.64 (0.57–0.71)) in older patients. In older and younger patients, the newly proposed qSOFA score (Sepsis 3.0) had a lower AUC than the PIRO score (sepsis 2.0).

Conclusion

The prognostic and discriminative performance of the five most commonly used disease severity scores was poor and less useful for risk stratification of older ED sepsis patients.

Electronic supplementary material

The online version of this article (10.1186/s13049-017-0436-3) contains supplementary material, which is available to authorized users.

A review of recent advances in data analytics for post-operative patient deterioration detection

Most deaths occurring due to a surgical intervention happen postoperatively rather than during surgery. The current standard of care in many hospitals cannot fully cope with detecting and addressing post-surgical deterioration in time. For millions of patients, this deterioration is left unnoticed, leading to increased mortality and morbidity. Postoperative deterioration detection currently relies on general scores that are not fully able to cater for the complex post-operative physiology of surgical patients. In the last decade however, advanced risk and warning scoring techniques have started to show encouraging results in terms of using the large amount of data available peri-operatively to improve postoperative deterioration detection. Relevant literature has been carefully surveyed to provide a summary of the most promising approaches as well as how they have been deployed in the perioperative domain. This work also aims to highlight the opportunities that lie in personalizing the models developed for patient deterioration for these particular post-surgical patients and make the output more actionable. The integration of pre- and intra-operative data, e.g. comorbidities, vitals, lab data, and information about the procedure performed, in post-operative early warning algorithms would lead to more contextualized, personalized, and adaptive patient modelling. This, combined with careful integration in the clinical workflow, would result in improved clinical decision support and better post-surgical care outcomes.