A validated clinical model to predict the need for admission and length of stay in children with acute bronchiolitis.

OBJECTIVE: To develop and validate a logistic regression model to predict need for admission and length of hospital stay in children presenting to the Emergency Department with bronchiolitis. SETTING: Two children's hospitals in Dublin, Ireland. METHODS: We reviewed 118 episodes of bronchiolitis in 99 children admitted from the Emergency Department. Those discharged within 24 h by a consultant/attending paediatrician were retrospectively categorized as suitable for discharge. We then validated the model using a cohort of 182 affected infants from another paediatric Emergency Department in a bronchiolitis season 2 years later. In the validation phase actual admission, failed discharge, and age less than 2 months defined the need for admission. RESULTS: The model predicted admission with 91% sensitivity and 83% specificity in the validation cohort. Age [odds ratio (OR) 0.86, 95% confidence interval (CI) 0.76-0.97], dehydration (OR 2.54, 95% CI 1.34-4.82), increased work of breathing (OR 3.39, 95% CI 1.29-8.92) and initial heart rate above the 97th centile (OR 3.78, 95% CI 1.05-13.57) predicted the need for admission and a longer hospital stay. CONCLUSION: We derived and validated a severity of illness model for bronchiolitis. This can be used for outcome prediction in decision support tools or severity of illness stratification in research/audit.     

EMS blood collection from patients with acute chest pain reduces emergency department length of stay

BackgroundExpediting the measurement of serum troponin by leveraging EMS blood collection could reduce the diagnostic time for patients with acute chest pain and help address Emergency Department (ED) overcrowding. However, this practice has not been examined among an ED chest pain patient population in the United States.MethodsA prospective observational cohort study of adults with non-traumatic chest pain without ST-segment elevation myocardial infarction was conducted in three EMS agencies between 12/2016–4/2018. During transport, paramedics obtained a patient blood sample that was sent directly to the hospital core lab for troponin measurement. On ED arrival HEART Pathway assessments were completed by ED providers as part of standard care. ED providers were blinded to troponin results from EMS blood samples. To evaluate the potential impact on length of stay (LOS), the time difference between EMS blood draw and first clinical ED draw was calculated. To determine the safety of using troponin measures from EMS blood samples, the diagnostic performance of the HEART Pathway for 30-day major adverse cardiac events (MACE: composite of cardiac death, myocardial infarction (MI), coronary revascularization) was determined using EMS troponin plus arrival ED troponin and EMS troponin plus a serial 3-h ED troponin.ResultsThe use of EMS blood samples for troponin measures among 401 patients presenting with acute chest pain resulted in a mean potential reduction in LOS of 72.5 ± SD 35.7 min. MACE at 30 days occurred in 21.0% (84/401), with 1 cardiac death, 78 MIs, and 5 revascularizations without MI. Use of the HEART Pathway with EMS and ED arrival troponin measures yielded a NPV of 98.0% (95% CI: 89.6–100). NPV improved to 100% (95% CI: 92.9–100) when using the EMS and 3-h ED troponin measures.ConclusionsEMS blood collection used for core lab ED troponin measures could significantly reduce ED LOS and appears safe when integrated into the HEART Pathway.     

The Timed Up and Go Test does not predict length of stay on an acute geriatric ward

This study aimed to determine whether the admission Timed Up and Go Test (TUG) predicted the length of stay of patients in an acute geriatric ward. Consecutive patients were quasi-randomly allocated to either a model development sample or a model validation sample. Multivariate Cox proportional hazards regression was used to model length of stay. Variables considered for inclusion in the development model were risk factors for length of stay reported in the literature and univariate predictors from our dataset (p < 0.05). Variables selected for use in the development sample were then tested in the validation sample. Of 2463 patients of mean age 82.1 years, 932 (37.8%) were able to complete the TUG. Despite a significant, though weak, relationship between the length of stay and the TUG time (Spearman coefficient 0.18, p < 0.001), no time clearly identified patients with longer length of stay. Patients unable to complete the TUG had a median length of stay of 11 days (IQR 7 to 18), 40% longer than those able to complete the TUG (median 8 days, IQR 8 to 12, p < 0.001). Other significant (p < 0.05) predictors of length of stay in both samples were number of active medical diagnoses, referral from the emergency department, in-patient fall, and diagnosis of ulcer or infection. The admission TUG time should not be used to screen for patients likely to have longer lengths of stay. The value of the TUG lies in determining the patient's ability to complete it, rather than the time taken.     

The use of length of stay distributions to predict hospital discharges.

Many hospital admissions scheduling or admissions control systems reported in the literature rely on estimates of future discharges to help control the variance in daily patient census. One of the two most frequently reported methods of estimating discharges attempts to explain the variance in historical length of stay (LPS) data. This paper explores the relationship between LOS variance explanation and the ability to predict discharges and concludes that even a large improvement in the ability to explain LOS variance will only marginally reduce the errors in the associated discharge predictions. In drawing this conclusion, a general discharge prediction model is developed and a more relevant statistic than per cent variance explained is introduced.     

Substantiation of patients' length stay in hospital after acute myocardial infarct

AIM: To study and validate the duration of optimal hospital stay for postmyocardial infarction patients and to specify indications for their discharge. MATERIALS AND METHODS: The trial enrolled 187 patients with large- and small-focal acute myocardial infarction. The patients were divided into two groups by different speed of activization and hospital stay. RESULTS: There were no significant differences between the groups with different duration of hospital stay by working ability and invalidism. Temporary disability in patients who have undergone standard rehabilitation was longer than in patients on the shorter-program rehabilitation. Performance of exercise tests on day 14 distinguished patients with a favourable long-term prognosis who were candidates for shorter rehabilitation program. CONCLUSION: The program of quicker rehabilitation (a two-times decrease in the hospital stay) can be applied to patients with uncomplicated myocardial infarction without damage to their health.     

Do trauma scores accurately predict outcomes for patients with burns?

A highly refined quality assurance program relies on accurate outcome evaluations and the identification of patients who are truly worthy of peer review. In our hospital, the Glasgow Coma Score, the Trauma Score, and the Injury Severity Score are used to monitor patients with burns. A retrospective review of 511 admitted patients with burns was performed to determine whether the existing monitors (Trauma Score, Glasgow Coma Score, Injury Severity Score) or the use of the Baux Score, the Edlich Burn Score, and the Zawacki Score would provide a more precise monitoring system. Logistic regression techniques demonstrated that the Baux Score, the Edlich Burn Score, and the Zawacki Score were highly correlated with patient outcome (p less than 0.001). Linear regression techniques demonstrated that only the Baux Score, the Edlich Burn Score, and the Zawacki Score were correlated with length of stay (p less than 0.01). On the basis of this retrospective review, the Baux Score, the Edlich Burn Score, and the Zawacki Score more accurately predicted outcomes for patients with burns than did the Trauma Score, the Injury Severity Score, and the Glasgow Coma Score; these scores can thus provide the most valuable information for quality assurance activities.     

An artificial neural network ensemble to predict disposition and length of stay in children presenting with bronchiolitis.

BACKGROUND: Artificial neural networks apply complex non-linear functions to pattern recognition problems. An ensemble is a 'committee' of neural networks that usually outperforms single neural networks. Bronchiolitis is a common manifestation of viral lower respiratory tract infection in infants and toddlers. OBJECTIVE: To train artificial neural network ensembles to predict the disposition and length of stay in children presenting to the Emergency Department with bronchiolitis. METHODS: A specifically constructed database of 119 episodes of bronchiolitis was used to train, validate, and test a neural network ensemble. We used EasyNN 7.0 on a 200 Mhz pentium PC with a maths co-processor. The ensemble of neural networks constructed was subjected to fivefold validation. Comparison with actual and predicted dispositions was measured using the kappa statistic for disposition and the Kaplan-Meier estimations and log rank test for predictions of length of stay. RESULTS: The neural network ensembles correctly predicted disposition in 81% (range 75-90%) of test cases. When compared with actual disposition the neural network performed similarly to a logistic regression model and significantly better than various 'dumb machine' strategies with which we compared it. The prediction of length of stay was poorer, 65% (range 60-80%), but the difference between observed and predicted lengths of stay were not significantly different. CONCLUSION: Artificial neural network ensembles can predict disposition for infants and toddlers with bronchiolitis; however, the prediction of length of hospital stay is not as good.     

Factors related to length of stay of laminectomy patients

A retrospective record audit was done to address the following research question: Are there factors associated with the length of hospital stay of laminectomy patients? According to the information on their records, patients with the following characteristics tended to have longer stays: were of the black race, had other medical diagnoses, had cervical region procedure, had "partial" procedure, had "extensive" pathology, and had greater use of pain medications. Those who were employed prior to admission, who were permitted to be more active, and who had muscle spasms had significantly shorter stays. The implications for nursing practice are discussed.     

Salvage of ear cartilage in patients with acute full-thickness burns

Three cases in which the temporoparietal fascial flap was used to salvage denuded ear cartilage during the acute period after burn injury are reported. Patients' burns ranged from 30% to 75% total body surface area. The full-thickness burn was acutely excised, exposing the auricular cartilage. The temporoparietal facial flap was elevated and wrapped around the cartilage. The flap was then covered with a split-thickness skin graft. All flaps and skin grafts survived. Additional reconstructive procedures have been performed on two of the patients and are planned for the third.     

A cross-national study of differences in length of stay of patients with cardiac diagnoses

To determine the reason for large regional differences in average hospital length of stay shown in federal discharge abstract data, the medical records of 482 cardiac patients from hospitals belonging to two metropolitan area PSROs of Baltimore, Maryland, and 438 cardiac patients from hospitals in the Metropolitan area PSRO from Portland, Oregon, were reviewed, stratified by diagnosis and complications, and compared for length of stay. Cardiac patients were hospitalized between 2.5 and 7 days longer in Baltimore than in Portland. Federal data on length of hospital stay were basically correct for the diagnostic categories studied. Length-of-stay differences could not be explained by patient differences and appeared to be due to differences in physician practice patterns.