Gregory L. Snow

Patients with respiratory failure increase ambulation after transfer to an intensive care unit where early activity is a priority

Objective:Ambulation of patients with acute respiratory failure may be unnecessarily limited in the acute intensive care setting. We hypothesized that ambulation of patients with acute respiratory failure would increase with transfer to an intensive care unit where activity is a key component of patient care. Design:Pre-post cohort study of respiratory failure patients. Setting:Adult intensive care units at LDS Hospital. Patients:Respiratory failure patients requiring >4 days of mechanical ventilation who were transferred from other LDS Hospital intensive care units to the respiratory intensive care unit. Interventions:We prospectively applied an early activity protocol to all consecutive respiratory failure patients transferred to the respiratory intensive care unit. Measurements and Main Results:We studied 104 respiratory failure patients who required mechanical ventilation for >4 days. Transferring a patient to the respiratory intensive care unit substantially increased the probability of ambulation (p < .0001). After 2 days in the respiratory intensive care unit, the number of patients ambulating had increased three-fold compared with pretransfer rates. Female gender (p = .019), the absence of sedatives (p = .009), and lower Acute Physiology and Chronic Health Evaluation II scores (p = .017) also predicted an increased probability of ambulation. Improvements in ambulation with transfer to the respiratory intensive care unit remained significant after adjustment for Acute Physiology and Chronic Health Evaluation II scores and other covariates. Conclusions:Transfer of acute respiratory failure patients to the respiratory intensive care unit substantially improved ambulation, independent of the underlying pathophysiology. The intensive care environment may contribute unnecessary immobilization throughout the course of acute respiratory failure. Sedatives, even given intermittently, substantially reduce the likelihood of ambulation. Controlled studies are needed to determine whether intensive care unit immobilization contributes to long-term neuromuscular dysfunction or whether early intensive care unit activity improves outcomes.

Electrocardiographic features in Andersen-Tawil syndrome patients with KCNJ2 mutations: Characteristic T-U-wave patterns predict the KCNJ2 genotype

Background—The ECG features of Andersen-Tawil syndrome (ATS) patients with KCNJ2 mutations (ATS1) have not been systematically assessed. This study aimed to define ECG features of KCNJ2 mutation carriers, to determine whether characteristic T-U–wave patterns exist, and to establish whether T-U patterns predict the ATS1 genotype. Methods and Results—In phase I, evaluation of T-U morphology in ECGs of 39 KCNJ2 mutation carriers identified characteristic T-U patterns: prolonged terminal T downslope, wide T-U junction, and biphasic and enlarged U waves. In phase II, ATS1 genotype prediction by T-U pattern was evaluated in the next 147 ECGs (57 other KCNJ2 mutation carriers, 61 unaffected family members, and 29 ATS patients without KCNJ2 mutations), with a sensitivity of 84% and specificity of 97%. Characteristic T-U patterns were present in 91% (87/96), in whom an enlarged U wave was predominant (73%). In phase III, QTc, QUc, and T- and U-wave duration/amplitude were compared in the 96 ATS1, 29 non-KCNJ2 ATS, and 75 normal subjects. In ATS1 patients, QUc, U-wave duration and amplitude, and QTc were all increased (P<0.001), but median QTc and interquartile range (IQR) were just 440 ms (IQR, 28 ms) compared with 420 ms (IQR, 20 ms) in normal subjects and 425 ms (IQR, 48 ms) in ATS non-KCNJ2 patients. Conclusions—In ATS1 patients, gene-specific T-U–wave patterns resulting from decreased IK1 owing to KCNJ2 mutations can aid diagnosis and direct genotyping. The normal QTc, distinct ECG, and other clinical features distinguish ATS1 from long-QT syndrome, and it is best designated as ATS1 rather than LQT7.

Is “transfusion-associated necrotizing enterocolitis” an authentic pathogenic entity?

BACKGROUND: Necrotizing enterocolitis (NEC) sometimes occurs after a transfusion, but it is unclear whether this is a chance association or cause and effect.

Forecasting daily patient volumes in the emergency department.

BACKGROUND Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. OBJECTIVES The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. METHODS Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. RESULTS All time series methods considered in this analysis provided improved in-sample model goodness of fit. However, post-sample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of post-sample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. CONCLUSIONS This study confirms the widely held belief that daily demand for ED services is characterized by seasonal and weekly patterns. The authors compared several time series forecasting methods to a benchmark multiple linear regression model. The results suggest that the existing methodology proposed in the literature, multiple linear regression based on calendar variables, is a reasonable approach to forecasting daily patient volumes in the ED. However, the authors conclude that regression-based models that incorporate calendar variables, account for site-specific special-day effects, and allow for residual autocorrelation provide a more appropriate, informative, and consistently accurate approach to forecasting daily ED patient volumes.

The STOP-Bang Equivalent Model and Prediction of Severity of Obstructive Sleep Apnea: Relation to Polysomnographic Measurements of the Apnea/Hypopnea Index

BACKGROUND Various models and questionnaires have been developed for screening specific populations for obstructive sleep apnea (OSA) as defined by the apnea/hypopnea index (AHI); however, almost every method is based upon dichotomizing a population, and none function ideally. We evaluated the possibility of using the STOP-Bang model (SBM) to classify severity of OSA into 4 categories ranging from none to severe. METHODS Anthropomorphic data and the presence of snoring, tiredness/sleepiness, observed apneas, and hypertension were collected from 1426 patients who underwent diagnostic polysomnography. Questionnaire data for each patient was converted to the STOP-Bang equivalent with an ordinal rating of 0 to 8. Proportional odds logistic regression analysis was conducted to predict severity of sleep apnea based upon the AHI: none (AHI < 5/h), mild (AHI ≥ 5 to < 15/h), moderate (≥ 15 to < 30/h), and severe (AHI ≥ 30/h). RESULTS Linear, curvilinear, and weighted models (R(2) = 0.245, 0.251, and 0.269, respectively) were developed that predicted AHI severity. The linear model showed a progressive increase in the probability of severe (4.4% to 81.9%) and progressive decrease in the probability of none (52.5% to 1.1%). The probability of mild or moderate OSA initially increased from 32.9% and 10.3% respectively (SBM score 0) to 39.3% (SBM score 2) and 31.8% (SBM score 4), after which there was a progressive decrease in probabilities as more patients fell into the severe category. CONCLUSIONS The STOP-Bang model may be useful to categorize OSA severity, triage patients for diagnostic evaluation or exclude from harm.

Cardiovascular Mortality Among Heart Transplant Recipients With Asymptomatic Antibody-Mediated or Stable Mixed Cellular and Antibody-Mediated Rejection

BACKGROUND Little has been reported on the clinical significance of asymptomatic antibody-mediated rejection (AMR) alone or mixed rejection (MR), defined as concurrent cellular rejection (CR) and AMR in heart transplantation. In this study, we examined whether a differential impact on cardiovascular mortality (CVM) existed when comparing asymptomatic AMR, to stable MR or CR. METHODS The Utah Transplantation Affiliated Hospitals (UTAH) Cardiac Transplant Program pathology database of all heart transplant recipients between 1985 and 2004 was queried. Patients were classified as cellular, antibody-mediated, or mixed rejectors based on their predominant pattern of rejection type in the first three months post-transplant. Kaplan-Meier survival curves were fit to each of the three groups and analyses were adjusted for age at the time of transplant, gender, and underlying primary cardiac disease. RESULTS Eight hundred and sixty nine heart transplant recipients qualified for analysis. Over the study period, patients with asymptomatic AMR or stable MR patterns had significantly worse CVM when compared to patients with stable CR pattern (AMR, 21.2%; MR, 18.0%; CR, 12.6%; AMR vs. CR, p = 0.009; MR vs. CR, p = 0.001). In contrast, CVM was comparable in patients with asymptomatic AMR or stable MR patterns (p = 0.9). CONCLUSIONS Asymptomatic or subclinical AMR and MR are clinically relevant, should be recognized, and deserve consideration for therapeutic intervention in hopes of avoiding adverse outcomes.

A multivariate time series approach to modeling and forecasting demand in the emergency department

STUDY OBJECTIVE The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. METHODS Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. RESULTS Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. CONCLUSION Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

Do platelet transfusions in the NICU adversely affect survival? Analysis of 1600 thrombocytopenic neonates in a multihospital healthcare system

Objective:Several studies have indicated a correlation between the number of platelet transfusions received by newborn intensive care unit (NICU) patients and the mortality rate. The number of platelet transfusions might be a marker for level of illness, and thus predictive of mortality. However, an alternative hypothesis is that multiple platelet transfusions themselves are harmful in this population.Study Design:We evaluated data from all thrombocytopenic neonates cared for in the Intermountain Healthcare NICUs in the past 4 years, seeking associations between the lowest platelet count recorded, number of platelet transfusions received and mortality rate. We also conducted a sensitivity analysis to examine the hypothesis that platelet transfusions were responsible for some fraction of the mortality rate.Result:Transfusion and outcome data were examined from 1600 thrombocytopenic NICU patients. At any level of platelet count, some patients received platelet transfusions but others did not. However, at all levels of platelet count, those that received platelet transfusions had a higher mortality rate. Neonates not given any platelet transfusions had a mortality rate of 2%, those with 1 or 2 transfusions had a mortality rate of 11% (P<0.001); those with >10 had a mortality rate of 35% (P<0.001); and those with ⩾20 had a mortality rate of 50% (P<0.001). A sensitivity analysis suggested that the platelet transfusions themselves were very likely responsible for some fraction of the increasing mortality rate.Conclusion:The number of platelet transfusions administered in the NICU predicts the mortality rate. Some of this correlation is ascribable to unknown and unmeasured factors such as level of illness. However, the present data and the sensitivity analysis both suggest that some of this correlation is due to harmful effects of multiple platelet transfusions in this group of patients.

Among very-low-birth-weight neonates is red blood cell transfusion an independent risk factor for subsequently developing a severe intraventricular hemorrhage?

BACKGROUND: A severe intraventricular hemorrhage (IVH) in a preterm neonate can result in life‐long disabilities or death. Pathogenic mechanisms responsible for IVH are incompletely understood. We postulated that if the timing of a severe IVH could be approximated by serial ultrasound, potentially relevant antecedents could be identified.

A Clinical Correlation Study of Severity of Antibody-mediated Rejection and Cardiovascular Mortality in Heart Transplantation

BACKGROUND The current International Society for Heart and Lung Transplantation (ISHLT) diagnostic criteria for antibody-mediated rejection (AMR) designate AMR as either absent (AMR 0) or present (AMR 1), without grading its severity. Yet, the extent of histologic and immunofluorescence (IF) findings of AMR varies across endomyocardial biopsies (EMBs). In this study, we hypothesized that the severity of AMR, as assessed on EMBs, correlates with cardiovascular mortality in heart transplant recipients. METHODS All EMBs from 1985 to 2005 were evaluated. Biopsy specimens were uniformly studied by light microscopy and IF early post-transplant. A comprehensive vascular score (V1: no AMR, to V5: severe AMR) was prospectively assigned to each EMB, based on severity of both histologic and IF findings. Univariate Cox proportional hazards regressions were performed using indicators of vascular scores alone, combined, and cumulatively. RESULTS Nine hundred six patients were transplanted and included in the study. Mean age was 46.6 +/- 15.5 years and 82% were male. A total of 26,236 EMBs comprised the study data. As expected, histologic and immunopathologic findings of AMR varied in severity. An incremental risk of cardiovascular mortality was found with more severe AMR whether vascular scores were analyzed individually (p = 0.001), in combination (p = 0.01) or cumulatively (p = 0.006). CONCLUSIONS The severity of AMR on EMBs correlates with an incremental cardiovascular mortality risk after heart transplantation, suggesting that AMR should be viewed as a spectrum rather than just as present or absent. Supplementing the ISHLT AMR diagnostic guidelines with a consensus severity scale is warranted.