Predictive value and interrater reliability of mental status and mobility assessment in the emergency department.

AIM: To investigate the predictive value of both mental status, assessed with the AVPUC (Alert, responds to Voice, responds to Pain, Unresponsive, and new Confusion) scale, and mobility assessments, and their interrater reliability (IRR) between triage clinicians and a research team. METHOD: Prospective study of consecutive patients who presented to an ED. Mental status and mobility were assessed by triage clinicians and by a dedicated research team. RESULTS: 4,191 patients were included. After adjustment for age and sex, patients with altered mental status have an odds ratio of 6.55 [4.09-10.24] to be admitted in the ICU and an odds ratio of 21.16 [12.06-37.01] to die within 30 days; patients with impaired mobility have an odds ratio of 7.08 [4.60-11.12] to be admitted in the ICU and an odds ratio of 12.87 [5.93-32.30] to die within 30 days. The kappa coefficient between triage clinicians and the research team for mental status assessment was 0.75, and 0.80 for mobility. CONCLUSION: Assessment of mental status by the AVPUC scale, and mobility by a simple dichotomous scale are suitable for ED triage. Both altered mental status and impaired mobility are associated with adverse outcomes. Mental status and mobility assessment have good interrater reliability.

Assessment of patient mobility improves the risk stratification of triage with the Emergency Severity Index: a prospective cohort study.

BACKGROUND AND IMPORTANCE: Formal triage may assign a low acuity to patients at high risk of deterioration and mortality. A patient's mobility can be easily assessed at triage. OBJECTIVE: To investigate if a simple assessment of mobility at triage can improve the Emergency Severity Index's (ESI) prediction of adverse outcomes. DESIGN, SETTING AND PARTICIPANTS: Prospective observational study of all patients attending the emergency department (ED) of a single academic hospital in Switzerland over a period of 3 weeks. OUTCOME MEASURES AND ANALYSIS: Triage clinicians classified participants as having normal or impaired mobility at triage. Impaired mobility was defined as the lack of a stable independent gait, regardless of its cause or duration (e.g. any patient who needed help to walk). The primary outcome was 30-day mortality. We performed a survival analysis stratified by mobility and ESI level. We compared the performance of regression models including the ESI alone or in combination with mobility as predictors of mortality using the Bayesian information criterion (BIC). MAIN RESULTS: 2523 patients were included in the study and 880 (34.9%) had impaired mobility. Patients with impaired mobility had a lower median 30-day survival in ESI levels 1-3. Survival of patients with normal mobility was similar regardless of their ESI level. CONCLUSION: The assessment of mobility at triage improves the ESI algorithm's risk stratification.

Derivation and validation of a universal vital assessment (UVA) score: a tool for predicting mortality in adult hospitalised patients in sub-Saharan Africa.

BACKGROUND: Critical illness is a leading cause of morbidity and mortality in sub-Saharan Africa (SSA). Identifying patients with the highest risk of death could help with resource allocation and clinical decision making. Accordingly, we derived and validated a universal vital assessment (UVA) score for use in SSA. METHODS: We pooled data from hospital-based cohort studies conducted in six countries in SSA spanning the years 2009-2015. We derived and internally validated a UVA score using decision trees and linear regression and compared its performance with the modified early warning score (MEWS) and the quick sepsis-related organ failure assessment (qSOFA) score. RESULTS: Of 5573 patients included in the analysis, 2829 (50.8%) were female, the median (IQR) age was 36 (27-49) years, 2122 (38.1%) were HIV-infected and 996 (17.3%) died in-hospital. The UVA score included points for temperature, heart and respiratory rates, systolic blood pressure, oxygen saturation, Glasgow Coma Scale score and HIV serostatus, and had an area under the receiver operating characteristic curve (AUC) of 0.77 (95% CI 0.75 to 0.79), which outperformed MEWS (AUC 0.70 (95% CI 0.67 to 0.71)) and qSOFA (AUC 0.69 (95% CI 0.67 to 0.72)). CONCLUSION: We identified predictors of in-hospital mortality irrespective of the underlying condition(s) in a large population of hospitalised patients in SSA and derived and internally validated a UVA score to assist clinicians in risk-stratifying patients for in-hospital mortality. The UVA score could help improve patient triage in resource-limited environments and serve as a standard for mortality risk in future studies.

When should a doctor see me when I get sick? A study of the time of day acutely ill medical patients present and the time they wait to see a doctor in Ireland.

BACKGROUND: Reconfiguration of the Irish Health Service has diverted of large numbers of acutely ill medical patients to a reduced number of hospitals and may have caused in delays in treatment. Although prompt care improves outcomes for patients with acute myocardial infarction, stroke, infection and shock, there is surprisingly little evidence for its value in other conditions. METHODS: The time of admission and time patients waited to be seen and clerked by a doctor was reviewed on all medical patients admitted to Nenagh Hospital prior to service reconfiguration (i.e. from 17 February 2000 to 6 March 2004). RESULTS: Over the study period of 1442,days 9435 patients were admitted (i.e. 6.5 patients per day or 0.3 per hour) and waited 37.6 SD 53.1min after admission before they were seen by a doctor. The peak time of admission is in the late afternoon and early evening and there was a liner correlation between the delay before seeing a doctor and the time of admission. The 1095 patients who waited 80min or more to be seen and clerked by a doctor (median delay 120min) were more likely to die (odds ratio 1.36 95% CI 1.03-1.81, p <0.03). CONCLUSION: Waiting to be seen by a doctor may increase the risk of death to some patients. For these patients it is probably safer to be seen quickly by any doctor, rather than travel many miles and wait several hours to see a better one.

Trajectories of the averaged abbreviated Vitalpac early warning score (AbEWS) and clinical course of 44,531 consecutive admissions hospitalized for acute medical illness.

BACKGROUND: It is not known how often, to what extent and over what time frame any early warning scores change, and what the implications of these changes are. SETTING: Thunder Bay Regional Health Sciences Center, Ontario, Canada. METHODS: The averaged vital signs measured over different time periods of 44,531 consecutive acutely ill medical admissions were determined and then combined to calculate the averaged abbreviated version of the Vitalpac early warning score (AbEWS) during each time period examined. RESULTS: 18% of all in-hospital deaths within 30 days are in patients with a low AbEWS on admission. Those admitted with a low AbEWS are more likely to increase their score and those admitted with a high score are more likely to lower it. Paradoxically, patients who have an averaged score over the first 6h in hospital that is lower than on admission have increased in-hospital mortality. Thereafter patients with an increase in the averaged score have almost twice the mortality of those with a decreased score. 4.7% of patients have a low averaged score on the day they die. CONCLUSION: AbEWS, without clinical judgment, cannot be used to detect those patients who do not need to be admitted to hospital or are suitable for discharge. A period of observation of at least 12h is required before the trajectory of AbEWS is of prognostic value, and any "improvement" that occurs before this time may be illusory.

Early warning scores generated in developed healthcare settings are not sufficient at predicting early mortality in Blantyre, Malawi: a prospective cohort study.

AIM: Early warning scores (EWS) are widely used in well-resourced healthcare settings to identify patients at risk of mortality. The Modified Early Warning Score (MEWS) is a well-known EWS used comprehensively in the United Kingdom. The HOTEL score (Hypotension, Oxygen saturation, Temperature, ECG abnormality, Loss of independence) was developed and tested in a European cohort; however, its validity is unknown in resource limited settings. This study compared the performance of both scores and suggested modifications to enhance accuracy. METHODS: A prospective cohort study of adults (≥18 yrs) admitted to medical wards at a Malawian hospital. Primary outcome was mortality within three days. Performance of MEWS and HOTEL were assessed using ROC analysis. Logistic regression analysis identified important predictors of mortality and from this a new score was defined. RESULTS: Three-hundred-and-two patients were included. Fifty-one (16.9%) died within three days of admission. With a cut-point ≥2, the HOTEL score had sensitivity 70.6% (95% CI: 56.2 to 82.5) and specificity 59.4% (95% CI: 53.0 to 65.5), and was superior to MEWS (cut-point ≥5); sensitivity: 58.8% (95% CI: 44.2 to 72.4), specificity: 56.2% (95% CI: 49.8 to 62.4). The new score, dubbed TOTAL (Tachypnoea, Oxygen saturation, Temperature, Alert, Loss of independence), showed slight improvement with a cut-point ≥2; sensitivity 76.5% (95% CI: 62.5 to 87.2) and specificity 67.3% (95% CI: 61.1 to 73.1). CONCLUSION: Using an EWS generated in developed healthcare systems in resource limited settings results in loss of sensitivity and specificity. A score based on predictors of mortality specific to the Malawian population showed enhanced accuracy but not enough to warrant clinical use. Despite an assumption of common physiological responses, disease and population differences seem to strongly determine the performance of EWS. Local validation and impact assessment of these scores should precede their adoption in resource limited settings.

READS: the rapid electronic assessment documentation system.

Patient documentation is time consuming and can detract from care. The authors report a novel computer programme that manipulates routinely collected information to quantify nursing workload, along with the reason for admission, functional status, estimates of in-hospital mortality and life expectancy. The programme stores information in a database, and produces a print-out in a situation/background/assessment/recommendation (SBAR) format. The average time taken to enter 629 patient encounters was 6.6 minutes. Pain was the most common presentation for low workload patients, while high workload patients often presented with altered mental status and reduced mobility. There was only a modest correlation between the risk of death and nursing workload. The programme measures nursing workload without further paperwork, and improves routine documentation with a legible brief report that is automatically generated. This report can be shared and provides data that is immediately available for day-to-day care, audit, quality control and service planning.

Should systematic risk assessment and immediate intervention of the acutely ill patient replace the traditional management paradigm?

The outcome of the traditional diagnostic history and physical depends entirely on the availability, ability and diligence of an individual doctor. An alternative is a team-based approach that performs the following tasks: a focused assessment, monitoring of the response to initial treatment, and then determining what further management is appropriate (calling for urgent help if it is required). This concept is based on risk prediction rather than diagnosis, and is captured by the mnemonic FAITH3 (Focused Assessment, Initial Treatment, hAssessing response, calling for Help and Handing over care).

An assessment tool for acutely ill medical patients.

This article reports the implementation and impact of a standardized systematic evidence-based predictive score for the initial assessment of acutely ill medical patients. The Simple Clinical Score (SCS) was introduced in the A&E department and the medical floor of the authors' hospital between June 2007 and July 2008. The SCS was well received by the staff - 67% felt it greatly improved patient assessment and was very valuable for ensuring appropriate placement of the patient after admission and improved the quality of care. This article describes the change process, the pilot evaluation and the training programme undertaken during the implementation of the SCS. It is hoped that this experience will be of value to other project teams who are undertaking similar initiatives.

Impedance cardiography: a rapid and cost-effective screening tool for cardiac disease.

Impedance cardiography (ICG) charts the rises and falls of thoracic impedance as the fluid content of the chest changes with each heartbeat. Breathing, arrhythmia, movements and posture interfere with the ICG. Modern pattern recognition software can now produce a composite signal-averaged ICG that considerably simplifies interpretation. The first derivative velocity waveform shows a smooth S wave that corresponds with systole, while the second derivative acceleration waveform (dZ/dt) contains several reference points that outline the A, S and O waves. Normally, the A wave follows atrial contraction and occurs in late diastole. It can, therefore, be abnormal in both atrial and ventricular arrhythmias and is abnormally increased when there is diastolic dysfunction. The S wave reflects ventricular contractility and is deformed by ventricular dyssynchrony. The O wave is associated with mitral valve opening and is abnormally enlarged in heart failure. These different patterns of ICG waveform are relatively easy to recognise and can be cost-effectively and quickly obtained to reliably distinguish between normal and abnormal cardiac function.

Should age be included as a component of track and trigger systems used to identify sick adult patients?

AIM OF STUDY: Few published "track and trigger systems" used to identify sick adult patients incorporate patient age as a variable. We investigated the relationship between vital signs, patient age and in-hospital mortality and investigated the impact of patient age on the function as predictors of in-hospital mortality of the two most commonly used track and trigger systems. MATERIALS AND METHODS: Using a database of 9987 vital signs datasets, we studied the relationship between admission vital signs and in-hospital mortality for a range of selected vital signs, grouped by patient age. We also used the vital signs data set to study the impact of patient age on the relationship between patient triggers using the "MET criteria" and "MEWS", and in-hospital mortality. RESULTS: At hospital discharge, there were 9152 (91.6%) survivors and 835 (8.4%) non-survivors. As admission vital signs worsened, mortality increased for each age range. Where groups of patients had triggered a certain MET criterion, mortality was higher as patient age increased. Mortality varied significantly with age (p<0.05; Fishers exact test) for breathing rate >36breathsmin(-1), systolic BP<90mmHg and decreased conscious level. For each age group, mortality also increased as total MEWS score increased. As the number of simultaneously occurring MEWS abnormalities, or simultaneously occurring MET criteria, increased, mortality increased for each age range. CONCLUSIONS: Age has a significant impact on in-hospital mortality. Our data suggest that the inclusion of age as a component of these systems could be advantageous in improving their function.

Determining the need for coronary revascularization by an exercise test assessment computer program (ETAP).

The rate at which coronary artery revascularization procedures are performed remains inconsistent, and their risks may be greater and long-term benefits less than imagined by the general public and open to considerable inter-individual variation. However, these risks and benefits can be explicitly estimated for an individual patient from a brief medical history and the results of a standard exercise test by a computer program that uses conventional medical decision making techniques. The program first estimates the prior and post-exercise test probability of coronary artery disease and then employs a decision analysis model to define the risks and benefits associated with different treatment options. These results are provided in a printed report that can become part of the clinical record to be reviewed with the patient. In contrast with traditional clinical intuition, the program consistently and explicitly defines the risks and benefits of coronary artery disease treatments. The program forces physicians and their patients to appraise critically the information and beliefs upon which they base their clinical decisions.