The Simple Clinical Score predicts mortality for 30 days after admission to an acute medical unit

Predicting Short-Term Mortality in Older Patients Discharged from Acute Hospitalizations Lasting Less Than 24 Hours

Purpose

Over coming decades, a rise in the number of short, acute hospitalizations of older people is to be expected. To help physicians identify high-risk patients prior to discharge, we aimed to develop a model capable of predicting the risk of 30-day mortality for older patients discharged from short, acute hospitalizations and to examine how model performance changed with an increasing amount of information.

Methods

This registry-based study included acute hospitalizations in Denmark for 2016-2018 lasting ≤24 hours where patients were permanent residents, ≥65 years old, and discharged alive. Utilizing many different predictor variables, we developed random forest models with an increasing amount of information, compared their performance, and examined important variables.

Results

We included 107,132 patients with a median age of 75 years. Of these, 3.3% (n=3575) died within 30 days of discharge. Model performance improved especially with the addition of laboratory results and information on prior acute admissions (AUROC 0.835), and again with comorbidities and number of prescription drugs (AUROC 0.860). Model performance did not improve with the addition of sociodemographic variables (AUROC 0.861), apart from age and sex. Important variables included age, dementia, number of prescription drugs, C-reactive protein, and eGFR.

Conclusion

The best model accurately estimated the risk of short-term mortality for older patients following short, acute hospitalizations. Trained on a large and heterogeneous dataset, the model is applicable to most acute clinical settings and could be a useful tool for physicians prior to discharge.

Factors associated with in-hospital mortality of patients admitted to an intensive care unit in a tertiary hospital in Malawi

Objective

To determine factors associated with in-hospital death among patients admitted to ICU and to evaluate the predictive values of single severely deranged vital signs and several severity scoring systems.

Methods

A combined retrospective and prospective cohort study of patients admitted to the adult ICU in a tertiary hospital in Malawi was conducted between January 2017 and July 2019. Predefined potential risk factors for in-hospital death were studied with univariable and multivariable logistic regression models, and the performance of severity scores was assessed.

Results

The median age of the 822 participants was 31 years (IQR 21–43), and 50% were female. Several factors at admission were associated with in-hospital mortality: the presence of one or more severely deranged vital signs, adjusted odds ratio (aOR) 1.9 (1.4–2.6); treatment with vasopressor aOR 2.3 (1.6–3.4); received cardiopulmonary resuscitation aOR 1.7 (1.2–2.6) and treatment with mechanical ventilation aOR 1.5 (1.1–2.1). Having had surgery had a negative association with in-hospital mortality aOR 0.5 (0.4–0.7). The predictive accuracy of the severity scoring systems had varying sensitivities and specificities, but none were sufficiently accurate to be clinically useful.

Conclusions

In conclusion, the presence of one or more severely deranged vital sign in patients admitted to ICU may be useful as a simple marker of an increased risk of in-hospital death.

Can the ECG be used to estimate age-related survival?

BACKGROUND

There are few reports of the relationship between electrocardiogram (ECG) findings and the age-related survival of acutely ill patients.

AIM

This study compared the 1-year survival curves of patients attending two Danish emergency departments (EDs) with normal and abnormal ECGs. Patients were divided into age groups from 20 to 90 years of age, and an abnormal ECG was defined as low QRS voltage (i.e. lead I + II <1.4 mV) or QTc interval prolongation >434 ms.

METHODS

A retrospective register-based observational study on 35 496 patients attending two Danish EDs, with 100% follow-up for 1 year.

RESULTS

ECG abnormality increases linearly with age, and between 30 and 70 years of age. Patients aged 20-29 years with ECG abnormalities are more than four times more likely to die within a year than patients of the same age with a normal ECG. An individual with an abnormal ECG has the same risk of dying within a year as an individual with a normal ECG who is 10 years older. After 70 years of age this tight relationship ends, but for younger individuals with an abnormal ECG the increase in mortality is even higher.

CONCLUSION

An ECG may be a simple practical estimate of age-related survival. For a patient under 70 years, an abnormal QRS voltage or a prolonged QTc interval may increase 1-year mortality to that of a patient ∼10 years older.

Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case-control study in Japan

OBJECTIVE

To clarify the factors associated with prolonged hospital stays, focusing on the COMplexity PRediction Instrument (COMPRI) score's accuracy in predicting the length of stay of newly hospitalised patients in general internal medicine wards.

DESIGN

A case-control study.

SETTING

Three general internal medicine wards in Chiba Prefecture, Japan.

PARTICIPANTS

Thirty-four newly hospitalised patients were recruited between November 2017 and December 2019, with a final analytic sample of 33 patients. We included hospitals in different cities with general medicine outpatient and ward facilities, who agreed to participate. We excluded any patients who were re-hospitalised within 2 weeks of a prior discharge.

PRIMARY AND SECONDARY OUTCOME MEASURES

Patients' COMPRI scores and their consequent lengths of hospital stay.

RESULTS

The 17 patients (52%) allocated to the long-term hospitalisation group (those hospitalised ≥14 days) had a significantly higher average age, COMPRI score and percentage of participants with comorbid chronic illnesses than the short-term hospitalisation group (<14 days). A logistic regression model (model A, comprising only the COMPRI score as the explanatory variable) and a multiple logistic regression model (model B, comprising variables other than the COMPRI score as explanatory variables) were created as prediction models for the long-term hospitalisation group. When age ≥75 years, a COMPRI score ≥6 and a physician with 10 years' experience were set as explanatory variables, model A showed better predictive accuracy compared with model B (fivefold cross-validation, area under curve of 0.87 vs 0.78). The OR of a patient with a COMPRI score of ≥6 joining the long-term hospitalisation group was 4.25 (95% CI=1.43 to 12.63).

CONCLUSIONS

Clinicians can use the COMPRI score when screening for complexity assessment to identify hospitalised patients at high risk of prolonged hospitalisation. Providing such patients with multifaceted and intensive care may shorten hospital stays.

A literature review of severity scores for adults with influenza or community-acquired pneumonia - implications for influenza vaccines and therapeutics

Influenza vaccination and antiviral therapeutics may attenuate disease, decreasing severity of illness in vaccinated and treated persons. Standardized assessment tools, definitions of disease severity, and clinical endpoints would support characterizing the attenuating effects of influenza vaccines and antivirals. We review potential clinical parameters and endpoints that may be useful for ordinal scales evaluating attenuating effects of influenza vaccines and antivirals in hospital-based studies. In studies of influenza and community-acquired pneumonia, common physiologic parameters that predicted outcomes such as mortality, ICU admission, complications, and duration of stay included vital signs (hypotension, tachypnea, fever, hypoxia), laboratory results (blood urea nitrogen, platelets, serum sodium), and radiographic findings of infiltrates or effusions. Ordinal scales based on these parameters may be useful endpoints for evaluating attenuating effects of influenza vaccines and therapeutics. Factors such as clinical and policy relevance, reproducibility, and specificity of measurements should be considered when creating a standardized ordinal scale for assessment.

A catalogue of tools and variables from crisis and routine care to support decision-making about allocation of intensive care beds and ventilator treatment during pandemics: Scoping review

PURPOSE

This scoping review sought to identify objective factors to assist clinicians and policy-makers in making consistent, objective and ethically sound decisions about resource allocation when healthcare rationing is inevitable.

MATERIALS AND METHODS

Review of guidelines and tools used in ICUs, hospital wards and emergency departments on how to best allocate intensive care beds and ventilators either during routine care or developed during previous epidemics, and association with patient outcomes during and after hospitalisation.

RESULTS

Eighty publications from 20 countries reporting accuracy or validity of prognostic tools/algorithms, or significant correlation between prognostic variables and clinical outcomes met our eligibility criteria: twelve pandemic guidelines/triage protocols/consensus statements, twenty-two pandemic algorithms, and 46 prognostic tools/variables from non-crisis situations. Prognostic indicators presented here can be combined to create locally-relevant triage algorithms for clinicians and policy makers deciding about allocation of ICU beds and ventilators during a pandemic. No consensus was found on the ethical issues to incorporate in the decision to admit or triage out of intensive care.

CONCLUSIONS

This review provides a unique reference intended as a discussion starter for clinicians and policy makers to consider formalising an objective a locally-relevant triage consensus document that enhances confidence in decision-making during healthcare rationing of critical care and ventilator resources.

Internal validation and comparison of the prognostic performance of models based on six emergency scoring systems to predict in-hospital mortality in the emergency department

Background

Medical scoring systems are potentially useful to make optimal use of available resources. A variety of models have been developed for illness measurement and stratification of patients in Emergency Departments (EDs). This study was aimed to compare the predictive performance of the following six scoring systems: Simple Clinical Score (SCS), Worthing physiological Score (WPS), Rapid Acute Physiology Score (RAPS), Rapid Emergency Medicine Score (REMS), Modified Early Warning Score (MEWS), and Routine Laboratory Data (RLD) to predict in-hospital mortality.

Methods

A prospective single-center observational study was conducted from March 2016 to March 2017 in Edalatian ED in Emam Reza Hospital, located in the northeast of Iran. All variables needed to calculate the models were recorded at the time of admission and logistic regression was used to develop the models’ prediction probabilities. The Area Under the Curve for Receiver Operating Characteristic (AUC-ROC) and Precision-Recall curves (AUC-PR), Brier Score (BS), and calibration plots were used to assess the models’ performance. Internal validation was obtained by 1000 bootstrap samples. Pairwise comparison of AUC-ROC was based on the DeLong test.

Results

A total of 2205 patients participated in this study with a mean age of 61.8 ± 18.5 years. About 19% of the patients died in the hospital. Approximately 53% of the participants were male. The discrimination ability of SCS, WPS, RAPS, REMS, MEWS, and RLD methods were 0.714, 0.727, 0.661, 0.678, 0.698, and 0.656, respectively. Additionally, the AUC-PR of SCS, WPS, RAPS, REMS, EWS, and RLD were 0.39, 0.42, 0.35, 0.34, 0.36, and 0.33 respectively. Moreover, BS was 0.1459 for SCS, 0.1713 for WPS, 0.0908 for RAPS, 0.1044 for REMS, 0.1158 for MEWS, and 0.073 for RLD. Results of pairwise comparison which was performed for all models revealed that there was no significant difference between the SCS and WPS. The calibration plots demonstrated a relatively good concordance between the actual and predicted probability of non-survival for the SCS and WPS models.

Conclusion

Both SCS and WPS demonstrated fair discrimination and good calibration, which were superior to the other models. Further recalibration is however still required to improve the predictive performance of all available models and their use in clinical practice is still unwarranted.

Which symptoms pose the highest risk in patients calling for an ambulance? A population-based cohort study from Denmark

BACKGROUND

Emergency medical service patients are a vulnerable population and the risk of mortality is considerable. In Denmark, healthcare professionals receive 112-emergency calls and assess the main reason for calling. The main aim was to investigate which of these reasons, i.e. which symptoms or mechanism of injury, contributed to short-term risk of death. Secondary aim was to study 1-30 day-mortality for each symptom/ injury.

METHODS

Historic population-based cohort study of emergency medical service patients calling 112 in the North Denmark Region between 01.01.2016-31.12.2018. We defined 1-day mortality as death on the same or the following day. The frequency of each symptom and cumulative number of deaths on day 1 and 30 together with 1- and 30-day mortality for each symptom/mechanism of injury is presented in proportions. Poisson regression with robust variance estimation was used to estimate incident rates (IR) of mortality with 95% confidence intervals (CI), crude and age and sex adjusted, mortality rates on day 1 per 100,000 person-year in the population.

RESULTS

The five most frequent reasons for calling 112 were "chest pain" (15.9%), "unclear problem" (11.9%), "accidents" (11.2%), "possible stroke" (10.9%), and "breathing difficulties" (8.3%). Four of these contributed to the highest numbers of deaths: "breathing difficulties" (17.2%), "unclear problem" (13.2%), "possible stroke" (8.7%), and "chest pain" (4.7%), all exceeded by "unconscious adult - possible cardiac arrest" (25.3%). Age and sex adjusted IR of mortality per 100,000 person-year was 3.65 (CI 3.01-4.44) for "unconscious adult - possible cardiac arrest" followed by "breathing difficulties" (0.45, CI 0.37-0.54), "unclear problem"(0.30, CI 0.11-0.17), "possible stroke"(0.13, CI 0.11-0.17) and "chest pain"(0.07, CI 0.05-0.09).

CONCLUSION

In terms of risk of death on the same day and the day after the 112-call, "unconscious adult/possible cardiac arrest" was the most deadly symptom, about eight times more deadly than "breathing difficulties", 12 times more deadly than "unclear problem", 28 times more deadly than "possible stroke", and 52 times more deadly than "chest pain". "Breathing difficulties" and "unclear problem" as presented when calling 112 are among the top three contributing to short term deaths when calling 112, exceeding both stroke symptoms and chest pain.

Consensus on predictors of clinical deterioration in emergency departments: A Delphi process study

AIM

The study aim was to determine relevance and applicability of generic predictors of clinical deterioration in emergency departments based on consensus among clinicians.

METHODS

Thirty-three predictors of clinical deterioration identified from literature were assessed in a modified two-stage Delphi-process. Sixty-eight clinicians (physicians and nurses) participated in the first round and 48 in the second round; all treating hospitalized patients in Danish emergency departments, some with pre-hospital experience. The panel rated the predictors for relevance (relevant marker of clinical deterioration) and applicability (change in clinical presentation over time, generic in nature and possible to detect bedside). They rated their level of agreement on a 9-point Likert scale and were also invited to propose additional generic predictors between the rounds. New predictors suggested by more than one clinician were included in the second round along with non-consensus predictors from the first round. Final decisions of non-consensus predictors after second round were made by a research group and an impartial physician.

RESULTS

The Delphi-process resulted in 19 clinically relevant and applicable predictors based on vital signs and parameters (respiratory rate, saturation, dyspnoea, systolic blood pressure, pulse rate, abnormal electrocardiogram, altered mental state and temperature), biochemical tests (serum c-reactive protein, serum bicarbonate, serum lactate, serum pH, serum potassium, glucose, leucocyte counts and serum haemoglobin), objective clinical observations (skin conditions) and subjective clinical observations (pain reported as new or escalating, and relatives' concerns).

CONCLUSION

The Delphi-process led to consensus of 19 potential predictors of clinical deterioration widely accepted as relevant and applicable in emergency departments.

[Characteristics of patients admitted from emergency units in 18 internal medicine departments and organisation of these departments: A cross sectional study from SNFMI (SiFMI study group) in 2015]

INTRODUCTION

Patients admitted from emergency units represent a large portion of the population in internal medicine departments. The aim of this study is to identify characteristics of patients and organization of these departments.

METHODS

Between June 29th and July 26th 2015, voluntary internal medicine departments from the SiFMI group prospectively filled anonymized internet forms to collect data of each patients admitted in their ward from emergency units, during seven consecutive days.

RESULTS

Three hundred and sixty-five patients from emergency departments were admitted in 18 internal medicine inpatients departments, totalling 1100 beds and 33,530 annual stays, 56% of them for emergency units inpatients. Mean age was 68 years, 54% were women, mean Charlson score was 2.6 and 44% of the patients took at least three drugs. Main causes of hospitalization were infectious (29%) and neurological (17%) diseases. Mean length of stay was 9.2 days. The medical team was composed by a median value of 4,5 [2,75-6,25] senior full-time equivalents, 86% were internists. Each department except one received residents, two third of them were from general medicine.

CONCLUSION

This study highlights a high organizational variability among internal medicine departments and patients, and sets internal medicine as a specialty with a great capacity to achieve an integrative/comprehensive management of patients and to offer a comprehensive basis for physicians in training.

Early warning score validation methodologies and performance metrics: a systematic review

BACKGROUND

Early warning scores (EWS) have been developed as clinical prognostication tools to identify acutely deteriorating patients. In the past few years, there has been a proliferation of studies that describe the development and validation of novel machine learning-based EWS. Systematic reviews of published studies which focus on evaluating performance of both well-established and novel EWS have shown conflicting conclusions. A possible reason is the heterogeneity in validation methods applied. In this review, we aim to examine the methodologies and metrics used in studies which perform EWS validation.

METHODS

A systematic review of all eligible studies from the MEDLINE database and other sources, was performed. Studies were eligible if they performed validation on at least one EWS and reported associations between EWS scores and inpatient mortality, intensive care unit (ICU) transfers, or cardiac arrest (CA) of adults. Two reviewers independently did a full-text review and performed data abstraction by using standardized data-worksheet based on the TRIPOD (Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) checklist. Meta-analysis was not performed due to heterogeneity.

RESULTS

The key differences in validation methodologies identified were (1) validation dataset used, (2) outcomes of interest, (3) case definition, time of EWS use and aggregation methods, and (4) handling of missing values. In terms of case definition, among the 48 eligible studies, 34 used the patient episode case definition while 12 used the observation set case definition, and 2 did the validation using both case definitions. Of those that used the patient episode case definition, 18 studies validated the EWS at a single point of time, mostly using the first recorded observation. The review also found more than 10 different performance metrics reported among the studies.

CONCLUSIONS

Methodologies and performance metrics used in studies performing validation on EWS were heterogeneous hence making it difficult to interpret and compare EWS performance. Standardizing EWS validation methodology and reporting can potentially address this issue.

Early warning scores for detecting deterioration in adult hospital patients: systematic review and critical appraisal of methodology

OBJECTIVE

To provide an overview and critical appraisal of early warning scores for adult hospital patients.

DESIGN

Systematic review.

DATA SOURCES

Medline, CINAHL, PsycInfo, and Embase until June 2019.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Studies describing the development or external validation of an early warning score for adult hospital inpatients.

RESULTS

13 171 references were screened and 95 articles were included in the review. 11 studies were development only, 23 were development and external validation, and 61 were external validation only. Most early warning scores were developed for use in the United States (n=13/34, 38%) and the United Kingdom (n=10/34, 29%). Death was the most frequent prediction outcome for development studies (n=10/23, 44%) and validation studies (n=66/84, 79%), with different time horizons (the most frequent was 24 hours). The most common predictors were respiratory rate (n=30/34, 88%), heart rate (n=28/34, 83%), oxygen saturation, temperature, and systolic blood pressure (all n=24/34, 71%). Age (n=13/34, 38%) and sex (n=3/34, 9%) were less frequently included. Key details of the analysis populations were often not reported in development studies (n=12/29, 41%) or validation studies (n=33/84, 39%). Small sample sizes and insufficient numbers of event patients were common in model development and external validation studies. Missing data were often discarded, with just one study using multiple imputation. Only nine of the early warning scores that were developed were presented in sufficient detail to allow individualised risk prediction. Internal validation was carried out in 19 studies, but recommended approaches such as bootstrapping or cross validation were rarely used (n=4/19, 22%). Model performance was frequently assessed using discrimination (development n=18/22, 82%; validation n=69/84, 82%), while calibration was seldom assessed (validation n=13/84, 15%). All included studies were rated at high risk of bias.

CONCLUSIONS

Early warning scores are widely used prediction models that are often mandated in daily clinical practice to identify early clinical deterioration in hospital patients. However, many early warning scores in clinical use were found to have methodological weaknesses. Early warning scores might not perform as well as expected and therefore they could have a detrimental effect on patient care. Future work should focus on following recommended approaches for developing and evaluating early warning scores, and investigating the impact and safety of using these scores in clinical practice.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017053324.

Is it possible to quickly identify acutely unwell patients who can be safely managed as outpatients? The need for a "Universal Safe to Discharge Score"

If scores or algorithms were developed that quickly identified patients who are bound to have 100% survival, if even only for a few days, more patients could be safely discharged from emergency department, this eliminating the risks of hospitalization for many patients. This hypothesis proposes that it is possible to develop a "Universal Safe to Discharge Score", and suggests how it might be developed and validated.

Prognostic performance of ECG abnormalities compared to vital signs in acutely ill patients in a resource-poor hospital in Uganda

Background

There are few reports of electrocardiogram (ECG) findings and their prognostic value in acutely ill patients admitted to low resource hospitals in sub-Saharan Africa.

Methods

We undertook an observational study of acutely ill medical patients admitted to a low-resource hospital in Uganda. Vital signs were used to calculate the National Early Warning Score (NEWS), and all ECGs were assessed using Tan et al.’s scoring system as described in Clin Cardiol 2009;32:82–86.

Results

There were 1361 ECGs performed, covering 68% of all acutely ill medical patients admitted to the hospital during the study. The most common ECG abnormality was a prolonged QTc interval (42% of all patients) and left ventricular hypertrophy (13.5%). Compared to the 519 patients (38%) with no Tan score abnormality, the 842 (62%) patients with one or more abnormalities were more likely to die in hospital (OR = 2.82; CI_95% = 1.50–5.36) and within 30 days of discharge (OR = 2.46; CI_95% = 1.50–4.08). There was no relationship between age and mortality; however, after adjustment by logistic regression, any NEWS ≥1 on admission, a Tan score of ≥1, and male sex all remained clinically significant predictors of both in-hospital and 30-day mortality.

Discussion

The majority of acutely ill medical patients admitted in a low-resource hospital in sub-Saharan Africa had ECG abnormalities, of which prolonged QTc and left ventricular hypertrophy were most common. Those with any Tan score abnormality were twice as likely to die as those without an abnormality.

Prospective Validation of a Checklist to Predict Short-term Death in Older Patients After Emergency Department Admission in Australia and Ireland

BACKGROUND

Emergency departments (EDs) are pressured environment where patients with supportive and palliative care needs may not be identified. We aimed to test the predictive ability of the CriSTAL (Criteria for Screening and Triaging to Appropriate aLternative care) checklist to flag patients at risk of death within 3 months who may benefit from timely end-of-life discussions.

METHODS

Prospective cohorts of >65-year-old patients admitted for at least one night via EDs in five Australian hospitals and one Irish hospital. Purpose-trained nurses and medical students screened for frailty using two instruments concurrently and completed the other risk factors on the CriSTAL tool at admission. Postdischarge telephone follow-up was used to determine survival status. Logistic regression and bootstrapping techniques were used to test the predictive accuracy of CriSTAL for death within 90 days of admission as primary outcome. Predictability of in-hospital death was the secondary outcome.

RESULTS

A total of 1,182 patients, with median age 76 to 80 years (IRE-AUS), were included. The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% confidence interval [CI] = 7.7-8.6) versus 5.7 (95% CI = 5.1-6.2) and Irish mean of 7.7 (95% CI = 6.9-8.5) versus 5.7 (95% CI = 5.1-6.2). The model with Fried frailty score was optimal for the derivation (Australian) cohort but prediction with the Clinical Frailty Scale (CFS) was also good (areas under the receiver-operating characteristic [AUROC] = 0.825 and 0.81, respectively). Values for the validation (Irish) cohort were AUROC = 0.70 with Fried and 0.77 using CFS. A minimum of five of 29 variables were sufficient for accurate prediction, and a cut point of 7+ or 6+ depending on the cohort was strongly indicative of risk of death. The most significant independent predictor of short-term death in both cohorts was frailty, carrying a twofold risk of death. CriSTAL's accuracy for in-hospital death prediction was also good (AUROC = 0.795 and 0.81 in Australia and Ireland, respectively), with high specificity and negative predictive values.

CONCLUSIONS

The modified CriSTAL tool (with CFS instead of Fried's frailty instrument) had good discriminant power to improve certainty of short-term mortality prediction in both health systems. The predictive ability of models is anticipated to help clinicians gain confidence in initiating earlier end-of-life discussions. The practicalities of embedding screening for risk of death in routine practice warrant further investigation.

Association between the level of municipality healthcare services and outcome among acutely older patients in the emergency department: a Danish population-based cohort study

OBJECTIVES

This study aims to describe the association between use of municipality healthcare services before an emergency department (ED) contact and mortality, hospital reattendance and institutionalisation.

DESIGN

Population-based prospective cohort study.

SETTING

ED of a large university hospital.

PARTICIPANTS

All medical patients ≥65 years of age from a single municipality with a first attendance to the ED during a 1-year period (November 2013 to November 2014).

PRIMARY AND SECONDARY OUTCOME MEASURES

Patients were categorised as independent of home care, dependent of home care or in residential care depending on municipality healthcare before ED contact. Patients were followed 360 days after discharge. Outcomes were postdischarge mortality, hospital reattendance and institutionalisation.

RESULTS

A total of 3775 patients were included (55% women), aged (median (IQR) 78 years (71-85)). At baseline, 48.9% were independent, 34.9% received home care and 16.2% were in residential care. Receiving home care or being in residential care was a strong predictor of mortality, hospital reattendance and institutionalisation. Among patients who were independent, 64.3% continued being independent up to 360 days after discharge. Even among patients ≥85 years, 35.4% lived independently in their own house 1 year after ED contact.

CONCLUSION

Prehospital information on municipality healthcare is closely related to patient outcome in older ED patients. It might have the potential to be used in risk stratification and planning of needs of older acute medical patients attending the ED.

Predictive validity of the CriSTAL tool for short-term mortality in older people presenting at Emergency Departments: a prospective study

ABSTRACT

To determine the validity of the Australian clinical prediction tool Criteria for Screening and Triaging to Appropriate aLternative care (CRISTAL) based on objective clinical criteria to accurately identify risk of death within 3 months of admission among older patients.

METHODS

Prospective study of ≥ 65 year-olds presenting at emergency departments in five Australian (Aus) and four Danish (DK) hospitals. Logistic regression analysis was used to model factors for death prediction; Sensitivity, specificity, area under the ROC curve and calibration with bootstrapping techniques were used to describe predictive accuracy.

RESULTS

2493 patients, with median age 78-80 years (DK-Aus). The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% CI 7.7-8.6 vs. 5.8 95% CI 5.6-5.9) and Danish mean 7.1 (95% CI 6.6-7.5 vs. 5.5 95% CI 5.4-5.6). The model with Fried Frailty score was optimal for the Australian cohort but prediction with the Clinical Frailty Scale (CFS) was also good (AUROC 0.825 and 0.81, respectively). Values for the Danish cohort were AUROC 0.764 with Fried and 0.794 using CFS. The most significant independent predictors of short-term death in both cohorts were advanced malignancy, frailty, male gender and advanced age. CriSTAL's accuracy was only modest for in-hospital death prediction in either setting.

CONCLUSIONS

The modified CriSTAL tool (with CFS instead of Fried's frailty instrument) has good discriminant power to improve prognostic certainty of short-term mortality for ED physicians in both health systems. This shows promise in enhancing clinician's confidence in initiating earlier end-of-life discussions.

The PARIS score can reliably predict 7-day all-cause mortality for both acute medical and surgical patients: an international validation study

BACKGROUND

We believe errors in the risk assessment of acutely ill patients occur because only vital signs without concurrent functional capacity are considered. We, therefore, developed the PARIS risk score based on blood pressure, age, respiratory rate, loss of independence and oxygen saturation.

AIM

Validation of the PARIS score in four independent cohorts from three countries.

METHODS

Retrospective cohort study of acutely ill patients admitted to hospitals in Denmark, Ireland and Uganda. Vital signs and functional capacity (registered as ability to stand or walk or get into bed unaided) was recorded upon arrival. Patients were followed up for 7 days (Denmark and Ireland) or until discharge (Uganda) and mortality recorded. The discriminatory power (ability to identify patients at increased risk) was determined using area under the receiver operating characteristics curve (AUROC) and calibration (precision) using Hosmer-Lemeshow goodness of fit test.

RESULTS

Out of 14 447 patients, 327 (2.3%) died within 7 days: median age was 59 (39-75) years and 7458 (51.8%) were female. Seven-day mortality increased from 0.3% with a score of 0-26.7% with a score of 5. The score's AUROC as 0.833 [95% confidence interval (95% CI) 0.811-0.856], 0.817 (95% CI 0.792-0.842) and 0.894 (95% CI 0.813-0.974) for all patients, medical patients and surgical patients, respectively. However, except for surgical patients, calibration of the score was poor.

CONCLUSION

The PARIS score can identify both high and low risk acutely admitted medical and surgical patients, but calibration was poor for medical patients.

Are Early Warning Scores Useful Predictors for Mortality and Morbidity in Hospitalised Acutely Unwell Older Patients? A Systematic Review

BACKGROUND

Early warning scores (EWSs) are used to identify deteriorating patients for appropriate interventions. We performed a systematic review to examine the usefulness of EWSs in predicting inpatient mortality and morbidity (transfer to higher-level care and length of hospital stay) in older people admitted to acute medical units with sepsis, acute cardiovascular events, or pneumonia.

METHODS

A systematic review of published and unpublished databases was conducted. Cochrane's tool for assessing Risk of Bias in Non-Randomised Studies-of Interventions (ROBINS-I) was used to appraise the evidence. A narrative synthesis was performed due to substantial heterogeneity.

RESULTS

Five studies (n = 12,057) were eligible from 1033 citations. There was an overall "moderate" risk of bias for all studies. The predictive ability of EWSs regarding mortality was reported in one study (n = 274), suggesting EWSs were better at predicting survival, (negative predictive value >90% for all scores). Three studies (n = 1819) demonstrated a significant association between increasing modified EWSs (MEWSs) and increased risk of mortality. Hazards ratios for a composite death/intensive care (ICU) admission with MEWSs ≥5 were significant in one study (p = 0.003). Two studies (n = 1421) demonstrated that a MEWS ≥6 was associated with 21 times higher probability of mortality (95% Confidence Interval (CI): 2.71⁻170.57) compared with a MEWS ≤1. A MEWS of ≥5 was associated with 22 times higher probability of mortality (95% CI: 10.45⁻49.16).

CONCLUSION

Increasing EWSs are strongly associated with mortality and ICU admission in older acutely unwell patients. Future research should be targeted at better understanding the usefulness of high and increasing EWSs for specific acute illnesses in older adults.

QRS voltage is a predictor of in-hospital mortality of acutely ill medical patients

BACKGROUND

Low QRS voltage has been shown to be associated with increased mortality in the general population and in a small pilot study the combined QRS voltage of ECG leads I and II was found to be associated with in-hospital mortality.

HYPOTHESIS

Confirm that low QRS voltage predicts the in-hospital mortality of acutely ill patients, and compare QRS voltage with other predictors of mortality that can be easily, quickly and cheaply obtained at the bedside.

METHODS

Prospective observational study of vital signs, QRS voltage and simple tools used to assess mental, functional and nutritional status at the bedside in unselected acutely ill patients admitted to a resource-poor hospital in sub-Saharan Africa.

RESULTS

Out of 1486 patients, 77 died (5.2%) in hospital. A combined lead I + II voltage <1.8 mV was present in 789 (53.1%) of patients, and significantly associated with in-hospital mortality (odds ratio 3.6, 95% CI 2.0-6.5, χ² 21.2, P < 0.00001). On logistic regression impaired mobility, the National Early Warning Score, male gender and lead I + II voltage were the only independent predictors of mortality. None of the 445 patients who were mobile on admission with a lead I + II voltage ≥ 1.8 mV died in hospital.

CONCLUSIONS

Low QRS voltage, male gender, NEWS, and impaired mobility were independent predictors of in-hospital mortality in the study population. These four variables, which are easily obtained at the bedside, could potentially provide a rapid, easy, and cheap risk stratification system.

Should impaired mobility on presentation be a vital sign?

INTRODUCTION

Vital signs are routinely used to assess acutely ill patients, but they do not detect all patients at risk of death. This retrospective multicenter cohort study compares the prediction of death by impaired mobility with age, co-morbidities, and vital sign changes.

METHODS

On first assessment, patients from a combined cohort of 9684 Danish and Irish patients and a separate cohort of 1010 Ugandan patients were stratified by impaired mobility on presentation (IMOP), vital sign changes assessed by the National Early Warning Score (NEWS), the Charlson Co-morbidity Index, and age.

RESULTS

Fourteen percent of Danish and Irish patients had IMOP compared with 42% of Ugandan patients. The odds ratios of IMOP for 7-day mortality were similar for both cohorts (i.e. 11.8, 95% CI 5.8-24.0 for Ugandan patients versus 6.7, 95% CI 5.0-9.0 for Danish and Irish patients). Univariate analysis of Ugandan patients showed that none of the parameters tested (i.e. low blood pressure, pulse, elevated respiratory rate, hypothermia, low oxygen saturation, old age, and coma) had a statistically higher odds ratio for either 7-day mortality than IMOP. Multivariate logistic regression analysis of Danish and Irish patients also showed that none of these parameters or the Charlson Co-morbidity Index had a statistically higher odds ratio than IMOP for either 7-day or 30-day mortality.

CONCLUSION

Immobility on presentation is a vital sign and predicts mortality for acutely ill patients independently of the traditional vital signs, age, and co-morbidities.

Clonal Clusters and Virulence Factors of Group C and G Streptococcus Causing Severe Infections, Manitoba, Canada, 2012-2014

These strains are more likely to cause invasive infection, which is an emerging public health concern as incidence and disease severity are on the rise.

The incidence of group C and G Streptococcus (GCGS) bacteremia, which is associated with severe disease and death, is increasing. We characterized clinical features, outcomes, and genetic determinants of GCGS bacteremia for 89 patients in Winnipeg, Manitoba, Canada, who had GCGS bacteremia during 2012–2014. Of the 89 patients, 51% had bacteremia from skin and soft tissue, 70% had severe disease features, and 20% died. Whole-genome sequencing analysis was performed on isolates derived from 89 blood samples and 33 respiratory sample controls: 5 closely related genetic lineages were identified as being more likely to cause invasive disease than non-clade isolates (83% vs. 57%, p = 0.002). Virulence factors cbp, fbp, speG, sicG, gfbA, and bca clustered clonally into these clades. A clonal distribution of virulence factors may account for severe and fatal cases of bacteremia caused by invasive GCGS.

A Prospective Validation of National Early Warning Score in Emergency Intensive Care Unit Patients at Beijing

Introduction

National Early Warning Score (NEWS) was launched in 2012 by the Royal College of Physicians in UK with an aim to improve the assessment of critical patients and timely detection of clinical deterioration.

Objective

To assess the performance of NEWS in emergency intensive care unit (EICU) patients in Beijing, PROC.

Design

prospective cohort study.

Setting

EICU in a university hospital.

Methods

The inclusion criteria were patients who stayed in the EICU beds under Department of Emergency Medicine, Xuanwu Hospital of Capital Medical University. Data of patients on admission were collected and calculated NEWS. Main outcome measure was death within 24 hours. The ability to predict mortality was assessed by area under the receiver operating characteristic curve (AUROC) analysis.

Results

Data on 540 consecutive EICU patients were collected from 1st January, 2013 to 31st March, 2013. Scores of 7 or more were associated with increased risk of death (OR=16.8; 95% CI 6.6-42.9). The AUROC for death within 24 h of admission was 0.85 (95% CI 0.79-0.90).

Conclusions

NEWS is applicable and feasible for EICU patients in Beijing. This study shows that the prediction power of NEWS for death within 24 hours of acutely ill patients attending Xuan Wu Hospital is comparable to that reported for the United Kingdom patients. (Hong Kong j.emerg.med. 2015;22:137-144)

Sepsis in Internal Medicine wards: current knowledge, uncertainties and new approaches for management optimization

Sepsis represents a global health problem in terms of morbidity, mortality, social and economic costs. Although usually managed in Intensive Care Units, sepsis showed an increased prevalence among Internal Medicine wards in the last decade. This is substantially due to the ageing of population and to multi-morbidity. These characteristics represent both a risk factor for sepsis and a relative contra-indication for the admission to Intensive Care Units. Although there is a lack of literature on the management of sepsis in Internal Medicine, the outcome of these patients seems to be gradually improving. This is due to Internists' increased adherence to guidelines and "bundles". The routine use of SOFA score helps physicians in the definition of septic patients, even if the optimal score has still to come. Point-of-care ultrasonography, lactates, procalcitonin and beta-d-glucan are of help for treatment optimization. The purpose of this narrative review is to focus on the management of sepsis in Internal Medicine departments, particularly on crucial concepts regarding diagnosis, risk assessment and treatment. Key Messages Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. The prevalence of sepsis is constantly increasing, affecting more hospital patients than any other disease. At least half of patients affected by sepsis are admitted to Internal Medicine wards. Adherence to guidelines, routine use of clinical and lab scores and point-of-care ultrasonography are of help for early recognition of septic patients and treatment optimization.

Anticipating care needs of patients after discharge from hospital: Frail and elderly patients without physiological abnormality on day of admission are more likely to require social services input

INTRODUCTION

Acute admissions to hospital are rising. As a part of a service evaluation we examined pathways of patients following hospital discharge depending on data available on admission to hospital.

METHODS

We merged data available on admission to the Wrexham Maelor hospital from an existing data-base in the Acute Medical Unit with follow up data from local social services as part of a data sharing agreement. Patients requiring support by social services post-discharge were matched with patients not requiring social services from the same post-code.

RESULTS

Stepwise logistic regression analysis identified candidate variables predicting likely support need. Decision tree analysis identified sub-groups of patients with higher likelihood to require support by social services after discharge from hospital. We found patients with normal physiology on admission as evidenced by a value of zero for the National Early Warning Score who were frail or older than 85years were most likely to require support after discharge.

CONCLUSIONS

Information available on admission to hospital might inform long term care needs. Prospective testing is needed. The algorithms are prone to be dependent on availability of local services but our methodology is expected to be transferable to other organizations.

Recognising older frail patients near the end of life: What next?

Frailty is a state of vulnerability resulting from cumulative decline in many physiological systems during a lifetime. It is progressive and considered largely irreversible, but its progression may be controlled and can be slowed down and its precursor -pre-frailty- can be treated with multidisciplinary intervention. The aim of this narrative review is to provide an overview of the different ways of measuring frailty in community settings, hospital, emergency, general practice and residential aged care; suggest occupational groups who can assess frailty in various services; discuss the feasibility of comprehensive geriatric assessments; and summarise current evidence of its management guidelines. We also suggest practical recommendations to recognise frail patients near the end of life, so discussions on goals of care, advance care directives, and shared decision-making including early referrals to palliative and supportive care can take place before an emergency arises. We acknowledge the barriers to systematically assess frailty and the absence of consensus on best instruments for different settings. Nevertheless, given its potential consequences including prolonged suffering, disability and death, we recommend identification of frailty levels should be universally attempted in older people at any health service, to facilitate care coordination, and honest discussions on preferences for advance care with patients and their caregivers.

Does how the patient feels matter? A prospective observational study of the outcome of acutely ill medical patients who feel their condition has improved on their first re-assessment after admission to hospital

BACKGROUND

Although asking how a patient feels is the first enquiry most clinicians make the value of the answer has never been examined in acutely ill patients.

METHODS

Prospective observational study that compared the predictive value of how well acutely ill medical patients felt after admission to a resource poor sub-Saharan hospital with their mental alertness, mobility and vital signs.

RESULTS

In total, 403 patients were studied. Patients who felt better when re-assessed 18.0 SD 9.1 h after admission to hospital were less likely to die in hospital (OR 0.18 95% CI 0.08-0.43, P = 0.00001) and more likely to be independent of others at discharge (OR 5.64 95% CI 3.04-10.47, P = 0.00001). Feeling better was an independent predictor of in-hospital death along with vital sign changes and gait stability, and an independent predictor of independence at discharge along with vital sign changes, gait stability and female gender.

CONCLUSION

In this patient cohort a subjective feeling of improvement at the first re-assessment after admission to hospital is a powerful independent predictor of reduced in-hospital mortality.

Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED)

The primary aim of this prospective study is to develop and validate a new prognostic model for predicting the risk of mortality in Emergency Department (ED) patients. The study involved 1765 patients in the development cohort and 1728 in the validation cohort. The main outcome was mortality up to 30 days after admission. Potential risk factors included clinical characteristics, vital signs, and routine haematological and biochemistry tests. The Bayesian Model Averaging method within the Cox’s regression model was used to identify independent risk factors for mortality. In the development cohort, the incidence of 30-day mortality was 9.8%, and the following factors were associated with a greater risk of mortality: male gender, increased respiratory rate and serum urea, decreased peripheral oxygen saturation and serum albumin, lower Glasgow Coma Score, and admission to intensive care unit. The area under the receiver operating characteristic curve for the model with the listed factors was 0.871 (95% CI, 0.844–0.898) in the development cohort and 0.783 (95% CI, 0.743–0.823) in the validation cohort. Calibration analysis found a close agreement between predicted and observed mortality risk. We conclude that the risk of mortality among ED patients could be accurately predicted by using common clinical signs and biochemical tests.

A scoring system for assessing the severity of acute diarrhea of adult patients

BACKGROUND

Diarrhea is frequently seen in developed and developing countries, and severe diarrhea is characterized by the high risk of death. Thus, it is very important to assess the severity of diarrhea early. We conducted a multi-center study to identify risk factors for the severity of diarrhea in adult patients and formulate an adult diarrhea state score (ADSS) for out-patient clinicians.

METHODS

A total of 219 adult patients with acute diarrhea were divided into two groups: 132 patients with mild diarrhea and 87 with severe diarrhea. Logistic regression was used to determine risk factors for the severity of diarrhea. The risk factors were assessed and an ADSS was formulated. Receiver operating characteristic (ROC) analysis was made to evaluate the diagnostic accuracy of ADSS, and the Kappa test was used to confirm the diagnostic reliability.

RESULTS

Five risk factors for evaluating the severity of diarrhea in adults included age (P<0.05), axillary temperature (P<0.01), mean arterial pressure (P<0.01), white blood cell count (WBC; P<0.01), and WBC in stool (P<0.01). The area under the ROC curve for ADSS was 0.958 when the cut off value was 4 (a sensitivity of 0.909; a specificity of 0.874), and the Kappa value was 0.781 (P<0.05).

CONCLUSION

The risk factors associated with the pathogenic condition of diarrhea were identified, quantified and formulated into an ADSS, which has high diagnostic accuracy and reliability for the early identification of patients with severe acute diarrhea.

Predicting mortality in acutely hospitalized older patients: a retrospective cohort study

Acutely hospitalized older patients have an increased risk of mortality, but at the moment of presentation this risk is difficult to assess. Early identification of patients at high risk might increase the awareness of the physician, and enable tailored decision-making. Existing screening instruments mainly use either geriatric factors or severity of disease for prognostication. Predictive performance of these instruments is moderate, which hampers successive interventions. We conducted a retrospective cohort study among all patients aged 70 years and over who were acutely hospitalized in the Acute Medical Unit of the Leiden University Medical Center, the Netherlands in 2012. We developed a prediction model for 90-day mortality that combines vital signs and laboratory test results reflecting severity of disease with geriatric factors, represented by comorbidities and number of medications. Among 517 patients, 94 patients (18.2 %) died within 90 days after admission. Six predictors of mortality were included in a model for mortality: oxygen saturation, Charlson comorbidity index, thrombocytes, urea, C-reactive protein and non-fasting glucose. The prediction model performs satisfactorily with an 0.738 (0.667-0.798). Using this model, 53 % of the patients in the highest risk decile (N = 51) were deceased within 90 days. In conclusion, we are able to predict 90-day mortality in acutely hospitalized older patients using a model with directly available clinical data describing disease severity and geriatric factors. After further validation, such a model might be used in clinical decision making in older patients.

Prediction of en-route complications during interfacility transport by outcome predictive scores in ED

OBJECTIVE

The objective was to determine the accuracy of the outcome predictive scores (Modified Early Warning Score [MEWS]; Hypotension, Low Oxygen Saturation, Low Temperature, Abnormal ECG, Loss of Independence [HOTEL] score; and Simple Clinical Score [SCS]) in predicting en-route complications during interfacility transport (IFT) in emergency department.

DESIGN

This was a retrospective cohort study.

METHODS

All IFT cases by ambulances with either nurse-led or physician-led escort, occurring between 1 January 2011 and 31 December 2012, were included. Obstetric and pediatric cases (age < 18 years) were excluded. The condition of patients was quantified by using the predictive scores (MEWS, HOTEL, and SCS) at triage station and on ambulance departure. The accuracy of predictive scores was compared by the receiver operating characteristic (ROC) curves.

RESULTS

A total of 659 cases were included. Seventeen cases had en-route complications (2.6%). The complication rate in physician-escorted transport (2.2%) was similar to that in nurse-escorted transport (2.6%). None of the 57 intubated cases had en-route complications. The area under the ROC curve for MEWS was 0.662 (triage) and 0.479 (departure). The accuracy of MEWS at triage was better than that at departure (P = .049). The area under the ROC curve for HOTEL was 0.613 (triage) and 0.597 (departure), and that for SCS was 0.6 (triage) and 0.568 (departure). In general, the predictive scores at triage were better than those on departure.

CONCLUSION

None of the scores had good accuracy in prediction of en-route complications during IFT. MEWS at triage was among the best one already but was not ideal.

The formation and design of the TRIAGE study--baseline data on 6005 consecutive patients admitted to hospital from the emergency department

BACKGROUND

Patient crowding in emergency departments (ED) is a common challenge and associated with worsened outcome for the patients. Previous studies on biomarkers in the ED setting has focused on identification of high risk patients, and and the ability to use biomarkers to identify low-risk patients has only been sparsely examined. The broader aims of the TRIAGE study are to develop methods to identify low-risk patients appropriate for early ED discharge by combining information from a wide range of new inflammatory biomarkers and vital signs, the present baseline article aims to describe the formation of the TRIAGE database and characteristize the included patients.

METHODS

We included consecutive patients ≥ 17 years admitted to hospital after triage staging in the ED. Blood samples for a biobank were collected and plasma stored in a freezer (-80 °C). Triage was done by a trained nurse using the Danish Emergency Proces Triage (DEPT) which categorizes patients as green (not urgent), yellow (urgent), orange (emergent) or red (rescusitation). Presenting complaints, admission diagnoses, comorbidities, length of stay, and 'events' during admission (any of 20 predefined definitive treatments that necessitates in-hospital care), vital signs and routine laboratory tests taken in the ED were aslo included in the database.

RESULTS

Between September 5(th) 2013 and December 6(th) 2013, 6005 patients were included in the database and the biobank (94.1 % of all admissions). Of these, 1978 (32.9 %) were categorized as green, 2386 (39.7 %) yellow, 1616 (26.9 %) orange and 25 (0.4 %) red. Median age was 62 years (IQR 46-76), 49.8 % were male and median length of stay was 1 day (IQR 0-4). No events were found in 2658 (44.2 %) and 158 (2.6 %) were admitted to intensive or intermediate-intensive care unit and 219 (3.6 %) died within 30 days. A higher triage acuity level was associated with numerous events, including acute surgery, endovascular intervention, i.v. treatment, cardiac arrest, stroke, admission to intensive care, hospital transfer, and mortality within 30 days (p < 0.001).

CONCLUSION

The TRIAGE database has been completed and includes data and blood samples from 6005 unselected consecutive hospitalized patients. More than 40 % experienced no events and were therefore potentially unnecessary hospital admissions.

Can the simple clinical score usefully predict the mortality risk and length of stay for a recently admitted patient?

OBJECTIVES

The aim of the present study was to determine whether an aggregate simple clinical score (SCS) has a role in predicting the imminent mortality and in-hospital length of stay (LOS) of newly admitted, acutely unwell General Medical in-patients.

METHODS

Data were collected prospectively from adult patients admitted through an Acute Medical Unit between February and August 2013. Using logistic regression analysis before and after adjustment for age, the SCS was assessed for its association with LOS and mortality, including 30-day mortality, just for those patients for full resuscitation. Changes in sensitivity and specificity after adding SCS to age as a predictor, as well as the change in the net reclassification index, were determined using the predicted probabilities from the logistic regression models.

RESULTS

The SCS was superior to age in predicting mortality of any patient within 30 days. It did not assist in predicting 30-day mortality for those patients who were for full resuscitation. The ability of the SCS to predict long stay (> 72h) remained relatively low (64%) and was inferior to published rates achieved by bedside clinician assessment (74%-82%).

CONCLUSION

There was no useful prospective role for the SCS in predicting LOS and mortality of in-patients newly admitted to a General Medicine service.

Model to predict inpatient mortality from information gathered at presentation to an emergency department: The Triage Information Mortality Model (TIMM)

OBJECTIVES

To derive and validate a mortality prediction model from information available at ED triage.

METHODS

Multivariable logistic regression of variables from administrative datasets to predict inpatient mortality of patients admitted through an ED. Accuracy of the model was assessed using the receiver operating characteristic area under the curve (ROC-AUC) and calibration using the Hosmer-Lemeshow goodness of fit test. The model was derived, internally validated and externally validated. Derivation and internal validation were in a tertiary referral hospital and external validation was in an urban community hospital.

RESULTS

The ROC-AUC for the derivation set was 0.859 (95% CI 0.856-0.865), for the internal validation set was 0.848 (95% CI 0.840-0.856) and for the external validation set was 0.837 (95% CI 0.823-0.851). Calibration assessed by the Hosmer-Lemeshow goodness of fit test was good.

CONCLUSIONS

The model successfully predicts inpatient mortality from information available at the point of triage in the ED.

The prognostic significance of respiratory rate in patients with pneumonia: a retrospective analysis of data from 705,928 hospitalized patients in Germany from 2010-2012

BACKGROUND

Measurement of the respiratory rate is an important instrument for assessing the severity of acute disease. The respiratory rate is often not measured in routine practice because its clinical utility is inadequately appreciated. In Germany, documentation of the respiratory rate is obligatory when a patient with pneumonia is hospitalized. This fact has enabled us to study the prognostic significance of the respiratory rate in reference to a large medical database.

METHOD

We retrospectively analyzed data from the external quality-assurance program for community-acquired pneumonia for the years 2010-2012. All patients aged 18 years or older who were not mechanically ventilated on admission were included in the analysis. Logistic regression was used to determine the significance of the respiratory rate as a risk factor for in-hospital mortality.

RESULTS

705,928 patients were admitted to the hospital with community-acquired pneumonia (incidence: 3.5 cases per 1000 adults per year). The in-hospital mortality of these patients was 13.1% (92 227 persons). The plot of mortality as a function of respiratory rate on admission was U-shaped and slanted to the right, with the lowest mortality at a respiratory rate of 20/min on admission. If patients with a respiratory rate of 12-20/min are used as a baseline for comparison, patients with a respiratory rate of 27-33/min had an odds ratio (OR) of 1.72 for in-hospital death, and those with a respiratory rate above 33/min had an OR of 2.55. Further independent risk factors for in-hospital death were age, admission from a nursing home, hospital, or rehabilitation facility, chronic bedridden state, disorientation, systolic blood pressure, and pulse pressure.

CONCLUSION

Respiratory rate is an independent risk marker for in-hospital mortality in community-acquired pneumonia. It should be measured when patients are admitted to the hospital with pneumonia and other acute conditions.

Seven-day mortality can be predicted in medical patients by blood pressure, age, respiratory rate, loss of independence, and peripheral oxygen saturation (the PARIS score): a prospective cohort study with external validation

BACKGROUND

Most existing risk stratification systems predicting mortality in emergency departments or admission units are complex in clinical use or have not been validated to a level where use is considered appropriate. We aimed to develop and validate a simple system that predicts seven-day mortality of acutely admitted medical patients using routinely collected variables obtained within the first minutes after arrival.

METHODS AND FINDINGS

This observational prospective cohort study used three independent cohorts at the medical admission units at a regional teaching hospital and a tertiary university hospital and included all adult (≥ 15 years) patients. Multivariable logistic regression analysis was used to identify the clinical variables that best predicted the endpoint. From this, we developed a simplified model that can be calculated without specialized tools or loss of predictive ability. The outcome was defined as seven-day all-cause mortality. 76 patients (2.5%) met the endpoint in the development cohort, 57 (2.0%) in the first validation cohort, and 111 (4.3%) in the second. Systolic blood Pressure, Age, Respiratory rate, loss of Independence, and peripheral oxygen Saturation were associated with the endpoint (full model). Based on this, we developed a simple score (range 0-5), ie, the PARIS score, by dichotomizing the variables. The ability to identify patients at increased risk (discriminatory power and calibration) was excellent for all three cohorts using both models. For patients with a PARIS score ≥ 3, sensitivity was 62.5-74.0%, specificity 85.9-91.1%, positive predictive value 11.2-17.5%, and negative predictive value 98.3-99.3%. Patients with a score ≤ 1 had a low mortality (≤ 1%); with 2, intermediate mortality (2-5%); and ≥ 3, high mortality (≥ 10%).

CONCLUSIONS

Seven-day mortality can be predicted upon admission with high sensitivity and specificity and excellent negative predictive values.

Development of a tool for defining and identifying the dying patient in hospital: Criteria for Screening and Triaging to Appropriate aLternative care (CriSTAL)

OBJECTIVE

To develop a screening tool to identify elderly patients at the end of life and quantify the risk of death in hospital or soon after discharge for to minimise prognostic uncertainty and avoid potentially harmful and futile treatments.

DESIGN

Narrative literature review of definitions, tools and measurements that could be combined into a screening tool based on routinely available or obtainable data at the point of care to identify elderly patients who are unavoidably dying at the time of admission or at risk of dying during hospitalisation.

MAIN MEASUREMENTS

Variables and thresholds proposed for the Criteria for Screening and Triaging to Appropriate aLternative care (CriSTAL screening tool) were adopted from existing scales and published research findings showing association with either in-hospital, 30-day or 3-month mortality.

RESULTS

Eighteen predictor instruments and their variants were examined. The final items for the new CriSTAL screening tool included: age ≥65; meeting ≥2 deterioration criteria; an index of frailty with ≥2 criteria; early warning score >4; presence of ≥1 selected comorbidities; nursing home placement; evidence of cognitive impairment; prior emergency hospitalisation or intensive care unit readmission in the past year; abnormal ECG; and proteinuria.

CONCLUSIONS

An unambiguous checklist may assist clinicians in reducing uncertainty patients who are likely to die within the next 3 months and help initiate transparent conversations with families and patients about end-of-life care. Retrospective chart review and prospective validation will be undertaken to optimise the number of prognostic items for easy administration and enhanced generalisability. Development of an evidence-based tool for defining and identifying the dying patient in hospital: CriSTAL.

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.

Implementation of a mortality prediction rule for real-time decision making: feasibility and validity

BACKGROUND

A previously published, retrospectively derived prediction rule for death within 30 days of hospital admission has the potential to launch parallel interdisciplinary team activities. Whether or not patient care improves will depend on the validity of prospectively generated predictions, and the feasibility of generating them on demand for a critical proportion of inpatients.

OBJECTIVE

To determine the feasibility of generating mortality predictions on admission and to validate their accuracy using the scoring weights of the retrospective rule.

DESIGN

Prospective, sequential cohort.

SETTING

Large, tertiary care, community hospital in the Midwestern United States

PATIENTS

Adult patients admitted from the emergency department or scheduled for elective surgery

RESULTS

Mortality predictions were generated on demand at the beginning of the hospitalization for 9312 (92.9%) out of a possible 10,027 cases. The area under the receiver operating curve for 30-day mortality was 0.850 (95% confidence interval: 0.833-0.866), indicating very good to excellent discrimination. The prospectively generated 30-day mortality risk had a strong association with the receipt of palliative care by hospital discharge, in-hospital mortality, and 180-day mortality, a fair association with the risk for 30-day readmissions and unplanned transfers to intensive care, and weak associations with receipt of intensive unit care ever within the hospitalization or the development of a new diagnosis that was not present on admission (ie, complication).

CONCLUSIONS

Important prognostic information is feasible to obtain in a real-time, single-assessment process for a sizeable proportion of hospitalized patients.

A pragmatic triage system to reduce length of stay in medical emergency admission: feasibility study and health economic analysis

BACKGROUND

Departments of Internal Medicine tend to treat patients on a first come first served basis. The effects of using triage systems are not known.

METHODS

We studied a cohort in an Acute Medical Unit (AMU). A computer-assisted triage system using acute physiology, pre-existing illness and mobility identified five distinct risk categories. Management of the category of very low risk patients was streamlined by a dedicated Navigator. Main outcome parameters were length of hospital stay (LOS) and overall costs. Results were adjusted for the degree of frailty as measured by the Clinical Frailty Scale (CFS). A six month baseline phase and intervention phase were compared.

RESULTS

6764 patients were included: 3084 in the baseline and 3680 in the intervention phase. Patients with very low risk of death accounted for 40% of the cohort. The LOS of the 1489 patients with very low risk of death in the intervention group was reduced by a mean of 1.85days if compared with the 1276 patients with very low risk in the baseline cohort. This was true even after adjustment for frailty. Over the six month period the cost of care was reduced by £250,158 in very low patients with no increase in readmissions or 30day mortality.

CONCLUSIONS

Implementation of an advanced triage system had a measurable impact on cost of care for patients with very low risk of death. Patients were safely discharged earlier to their own home and the intervention was cost-effective.

Hyponatraemia in Emergency Medical Admissions-Outcomes and Costs

Healthcare systems in the developed world are struggling with the demand of emergency room presentations; the study of the factors driving such demand is of fundamental importance. From a database of all emergency medical admissions (66,933 episodes in 36,271 patients) to St James’ Hospital, Dublin, Ireland, over 12 years (2002 to 2013) we have explored the impact of hyponatraemia on outcomes (30 days in-hospital mortality, length of stay (LOS) and costs). Identified variables, including Acute Illness Severity, Charlson Co-Morbidity and Chronic Disabling Disease that proved predictive univariately were entered into a multivariable logistic regression model to predict the bivariate of 30 days in-hospital survival. A zero truncated Poisson regression model assessed LOS and episode costs and the incidence rate ratios were calculated. Hyponatraemia was present in 22.7% of episodes and 20.3% of patients. The 30 days in-hospital mortality rate for hyponatraemic patients was higher (15.9% vs. 6.9% p < 0.001) and the LOS longer (6.3 (95% CI 2.9, 12.2) vs. 4.0 (95% CI 1.5, 8.2) p < 0.001). Both parameters worsened with the severity of the initial sodium level. Hospital costs increased non-linearly with the severity of initial hyponatraemia. Hyponatraemia remained an independent predictor of 30 days in-hospital mortality, length of stay and costs in the multi-variable model.

External validation of the simple clinical score and the HOTEL score, two scores for predicting short-term mortality after admission to an acute medical unit

Background

Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs.

Methods

Pre-planned prospective observational cohort study.

Setting

Danish 460-bed regional teaching hospital.

Findings

We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774–0.879) for 30-day mortality, and goodness-of-fit test, χ² = 2.68 (10 degrees of freedom), P = 0.998 and χ² = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901–0.962) for 24-hours mortality and goodness-of-fit test, χ² = 5.56 (10 degrees of freedom), P = 0.234.

Conclusion

We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision.

Comparison of risk prediction scoring systems for ward patients: a retrospective nested case-control study

INTRODUCTION

The rising prevalence of rapid response teams has led to a demand for risk-stratification tools that can estimate a ward patient's risk of clinical deterioration and subsequent need for intensive care unit (ICU) admission. Finding such a risk-stratification tool is crucial for maximizing the utility of rapid response teams. This study compares the ability of nine risk prediction scores in detecting clinical deterioration among non-ICU ward patients. We also measured each score serially to characterize how these scores changed with time.

METHODS

In a retrospective nested case-control study, we calculated nine well-validated prediction scores for 328 cases and 328 matched controls. Our cohort included non-ICU ward patients admitted to the hospital with a diagnosis of infection, and cases were patients in this cohort who experienced clinical deterioration, defined as requiring a critical care consult, ICU admission, or death. We then compared each prediction score's ability, over the course of 72 hours, to discriminate between cases and controls.

RESULTS

At 0 to 12 hours before clinical deterioration, seven of the nine scores performed with acceptable discrimination: Sequential Organ Failure Assessment (SOFA) score area under the curve of 0.78, Predisposition/Infection/Response/Organ Dysfunction Score of 0.76, VitalPac Early Warning Score of 0.75, Simple Clinical Score of 0.74, Mortality in Emergency Department Sepsis of 0.74, Modified Early Warning Score of 0.73, Simplified Acute Physiology Score II of 0.73, Acute Physiology and Chronic Health Evaluation II of 0.72, and Rapid Emergency Medicine Score of 0.67. By measuring scores over time, it was found that average SOFA scores of cases increased as early as 24 to 48 hours prior to deterioration (P = 0.01). Finally, a clinical prediction rule which also accounted for the change in SOFA score was constructed and found to perform with a sensitivity of 75% and a specificity of 72%, and this performance is better than that of any SOFA scoring model based on a single set of physiologic variables.

CONCLUSIONS

ICU- and emergency room-based prediction scores can also be used to prognosticate risk of clinical deterioration for non-ICU ward patients. In addition, scoring models that take advantage of a score's change over time may have increased prognostic value over models that use only a single set of physiologic measurements.