Early Detection of In-Patient Deterioration: One Prediction Model Does Not Fit All.

OBJECTIVES: Early detection of subacute potentially catastrophic illnesses using available data is a clinical imperative, and scores that report risk of imminent events in real time abound. Patients deteriorate for a variety of reasons, and it is unlikely that a single predictor such as an abnormal National Early Warning Score will detect all of them equally well. The objective of this study was to test the idea that the diversity of reasons for clinical deterioration leading to ICU transfer mandates multiple targeted predictive models. DESIGN: Individual chart review to determine the clinical reason for ICU transfer; determination of relative risks of individual vital signs, laboratory tests and cardiorespiratory monitoring measures for prediction of each clinical reason for ICU transfer; and logistic regression modeling for the outcome of ICU transfer for a specific clinical reason. SETTING: Cardiac medical-surgical ward; tertiary care academic hospital. PATIENTS: Eight-thousand one-hundred eleven adult patients, 457 of whom were transferred to an ICU for clinical deterioration. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We calculated the contributing relative risks of individual vital signs, laboratory tests and cardiorespiratory monitoring measures for prediction of each clinical reason for ICU transfer, and used logistic regression modeling to calculate receiver operating characteristic areas and relative risks for the outcome of ICU transfer for a specific clinical reason. The reasons for clinical deterioration leading to ICU transfer were varied, as were their predictors. For example, the three most common reasons-respiratory instability, infection and suspected sepsis, and heart failure requiring escalated therapy-had distinct signatures of illness. Statistical models trained to target-specific reasons for ICU transfer performed better than one model targeting combined events. CONCLUSIONS: A single predictive model for clinical deterioration does not perform as well as having multiple models trained for the individual specific clinical events leading to ICU transfer.

Daytime QT by Routine 12-Lead ECG Is Prolonged in Patients with Severe Obstructive Sleep Apnea.

BACKGROUND: Obstructive sleep apnea (OSA) has been linked to sudden cardiac death (SCD). Prolonged QT is a recognized electrocardiographic (ECG) marker of abnormal ventricular repolarization linked to increased risk of SCD. We hypothesized that individuals with OSA have more pronounced abnormality in daytime QT interval. METHODS: We reviewed consecutive patients who underwent clinically indicated polysomnography with 12-lead ECG within 1 year at a single center. Heart rate-corrected QT interval (QTc) was compared by OSA severity class (normal/mild: apnea-hypopnea index (AHI) < 15/hr (n = 72); moderate: 15-30 (n = 72); moderate: 15-30 (n = 72); moderate: 15-30 (. RESULTS: A total of 249 patients were included. QTc was similar between the normal/mild and moderate groups, and the overall QTc trend increased across OSA (normal/mild: 435.6 ms; moderate: 431.36; severe: 444.4; p trend = 0.03). Abnormal QTc was found amongst 34% of male and 31% of female patients. Patients with severe OSA had longer QTc compared with normal/mild OSA (mean difference (95% CI): 10.0 ms (0.5, 19.0), p trend = 0.03). Abnormal QTc was found amongst 34% of male and 31% of female patients. Patients with severe OSA had longer QTc compared with normal/mild OSA (mean difference (95% CI): 10.0 ms (0.5, 19.0), p trend = 0.03). Abnormal QTc was found amongst 34% of male and 31% of female patients. Patients with severe OSA had longer QTc compared with normal/mild OSA (mean difference (95% CI): 10.0 ms (0.5, 19.0), p trend = 0.03). Abnormal QTc was found amongst 34% of male and 31% of female patients. Patients with severe OSA had longer QTc compared with normal/mild OSA (mean difference (95% CI): 10.0 ms (0.5, 19.0). CONCLUSIONS: In a sleep clinic cohort, severe OSA was associated with higher QTc and clinically defined abnormal QTc compared with nonsevere OSA.

Sleep Apnea and Sudden Cardiac Death.

Sleep plays an integral role in maintaining health and quality of life. Obstructive sleep apnea (OSA) is a prevalent sleep disorder recognized as a risk factor for cardiovascular disease (CVD) and arrhythmias. Sudden cardiac death (SCD) is a common and devastating event. Out-of-hospital SCD accounts for the majority of deaths from cardiac disease, which is the leading cause of death globally. A limited but emerging body of research have further elaborated on the link between OSA and SCD. In this article, we aim to provide a critical review of the existing evidence by addressing the following: What epidemiologic evidence exists linking OSA to SCD? What evidence exists for a pathophysiologic connection between OSA and SCD? Are there electrocardiographic markers of SCD found in patients with OSA? Does heart failure represent a major effect modifier regarding the relationship between OSA and SCD? What is the impact of sleep apnea treatment on SCD and cardiovascular outcomes? Finally, we elaborate on ongoing research to enhance our understanding of the OSA-SCD association.

Atrial Fibrillation and Objective Sleep Quality by Slow Wave Sleep.

BACKGROUND: Self-reported poor sleep quality has been suggested in patients with AF. Slow wave sleep (SWS) is considered the most restorative sleep stage and represents an important objective measure of sleep quality. The aim of this study was to compare quantity of SWS between patients with and without AF. METHODS AND RESULTS: We included patients with and without a documented history of AF by reviewing clinically indicated polysomnography data from a single sleep center. Patients on medications with potential influence on sleep architecture were excluded. Logistic regression was performed to determine the association between AF and SWS time (low vs. high) adjusting for age, gender, body mass index, and sleep apnea. In a 2:1 case-control set-up, a total of 205 subjects (139 with AF, 66 without AF) were included. Mean age was 62 (SD: 14.3) years and 59% were men. Patients with AF had lower SWS time (11.1 vs. 16.6 min, p=0.02). In multivariable analysis, prevalent AF was associated with low SWS independent of sleep apnea and other potential confounders (OR 2.5 [1.3, 5.0], p=0.006). Limiting the analysis to patients whose total sleep time was greater than 4 hours (by excluding N=31) resulted in more robust results (OR 3.9 [1.7, 9.7]. p=0.002). CONCLUSION: AF is associated with more impaired sleep quality as indicated by lower quantity of SWS. More studies are needed to explore the mechanistic interactions between AF and sleep.

Plasma Volume and Renal Function Predict Six-Month Survival after Hospitalization for Acute Decompensated Heart Failure.

BACKGROUND: Plasma volume (PV) is contracted in stable patients with heart failure (HF) due to decongestion strategies. On the other hand, increased PV can adversely affect the trajectory of HF. We therefore examined the effects of increased percentage change in PV (%ΔPV), blood urea nitrogen (BUN), and %ΔPV stratified by BUN and glomerular filtration rate (GFR) on survival after discharge in patients hospitalized for acute decompensated HF (ADHF). METHODS: We used the Strauss-Davis-Rosenbaum formula to calculate the %ΔPV between baseline and hospital discharge in a cohort from the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness trial (ESCAPE). Kaplan-Meier curves were constructed for survival over 6 months. Cox proportional hazards regression was used to obtain adjusted hazard ratios (HR) and 95% confidence intervals (95% CI) for the associations between survival after discharge and %ΔPV, BUN, and %ΔPV stratified by BUN and GFR. RESULTS: Of the 324 patients included in our study (age 56.1 ± 13.6 years, 26.5% female), those with increased or no %ΔPV at discharge were less likely to survive at 6 months compared with those having reduced %ΔPV (log rank, p = 0.0093). Increased %ΔPV (HR 1.08 per 10% increase; 95% CI: 1.02-1.14) and increased BUN at discharge (HR 1.02 per mg/dL; 95% CI: 1.01-1.03) were independently associated with worse survival. Decreasing %ΔPV had a greater association with improved survival in patients with discharge BUN <31 mg/dL (p = 0.02) and discharge GFR >40 mL/min/1.73 m2 (p = 0.047). CONCLUSIONS: Increased %ΔPV and BUN at discharge predicted worse 6-month survival in patients with ADHF. Decreased %ΔPV with low BUN or high GFR at discharge was associated with improved survival.