The feasibility of emergency department observation units in the management of mild to moderate hyponatremia.

OBJECTIVE: To describe the feasibility of managing hyponatremia patients under outpatient observation status in an academic medical center, and compare outcomes based on the use of an emergency department observation unit (EDOU). METHODS: This is a retrospective cohort study of emergency department hyponatremic patients managed in four hospitals within a large urban academic medical center over 27 months. All patients had an admit-to-observation order, ICD-10 codes for hyponatremia, and mild (130-135 mmol/L) to moderate (121-129 mmol/L) hyponatremia. Observation settings were divided into two groups: EDOU and Non-Observation Unit (NOU) inpatient beds. Severe hyponatremia (≤120 mmol/L) was excluded. Primary clinical outcomes were inpatient admit rate, length of stay (LOS), total direct cost, the rate of adverse events and 30-day recidivism. RESULTS: 188 patients were managed as an observation patient, with 64 managed in an EDOU setting (age 74.0 yr, 70.3% female) and 124 managed in a NOU setting (age 71.5 yr, 64.5% female). Patient subgroups were similar in terms of presenting complaints, comorbidities, and medication histories. Initial and final sodium levels were similar between settings: EDOU (125.1 to 132.6 mmol/L) vs NOU (123.5 to 132.0 mmol/L). However, outcomes differed by setting for observation to inpatient admit rate (EDOU 28.1% vs NOU 37.9%, adjusted effect 0.70), overall length of stay (EDOU 19.2 h vs NOU 31.9 h; adjusted effect -10.5 h and total direct cost ($1230 vs $1531; adjusted effect -$167). EDOU sodium correction rates were faster (EDOU 0.44 mmol/L/h vs 0.24 mmol/L/h; adjusted effect 0.15 mmol/L/h) and 30-day recidivism rate was similar (EDOU 13% vs NOU 15%). There were no index visit deaths or intensive care unit admissions. CONCLUSION: Management of selected hyponatremia patients under observation status is feasible, with the EDOU setting demonstrating lower admit rates, shorter length of stay, and lower total direct costs with similar clinical outcomes.

Utility of QT interval corrected by Rautaharju method to predict drug-induced torsade de pointes.

INTRODUCTION: New QT correction formulae derived from large populations are available such as Rautaharju's [QTcRTH = QT * (120 + HR)/180] and Dmitrienko's [QTcDMT = QT/RR0.413]. These formulae were derived from 57,595 and 13,039 cases, respectively. Recently, a study has shown that they did not experience errors across a wide range of heart rates compared to others. OBJECTIVES: (1) To determine the best cut-off value of QTcRTH and QTcDMT as a predictor of torsade de pointes (TdP) and (2) to compare the sensitivity and specificity using the cut-off value of QTcRTH with those of the QTcBazett (QTcBZT), QTcFridericia (QTcFRD), and QT nomogram. METHODS: Data were derived from two data sets. All cases aged over 18 years with an exposure to QT-prolonging drugs. Group-1, all cases developed TdP. Data in Group-1 were obtained from systematic review of reported cases from Medline since its establishment until 10 December 2015. Group-2 is composed of those who overdosed on QT prolonging drugs but did not develop TdP. This data set was previously extracted from a chart review of three medical centers from January 2008 to December 2010. Data from both groups were used to calculate QTcRTH and QTcDMT. The cut-off values from QTcRTH and QTcDMT that provided the best sensitivity and specificity to predict TdP were then selected. The same method was applied to find those values from QTcBZT, QTcFRD, and QT nomogram. The receiver operating characteristic curve (ROC) was applied where appropriate. RESULTS: Group-1, 230 cases of drug-induced TdP were included from the systematic review of Medline. Group-2 (control group), which did not develop TdP, consisted of 292 cases. After applying all of the correction methods to the two datasets, the best cut-off values that provided the best accuracy (Ac) with the best sensitivity (Sn) and specificity (Sp) for each formula were as follows: QTcRTH at 477 milliseconds (ms), Ac = 89.08%, Sn = 91.30% (95%CI = 86.89-94.61), Sp = 87.33%(95%CI = 82.96-90.92); QTcDMT at 475 ms, Ac = 88.31%, Sn =91.30% (95%CI = 86.89-94.61), Sp = 85.96%(95%CI = 81.44-89.73); QTcBZT at 490 ms, Ac = 86.97%, Sn = 88.26% (95%CI = 83.38-92.12), Sp = 85.96% (95%CI = 81.44-89.73); QTcFRD at 473 ms, Ac = 88.89%, Sn = 89.13% (95%CI = 84.37-92.84), Sp =88.70% (95%CI = 84.50-92.09). We found a significant difference (p-value = 0.0020) between area under the ROC of the QTcRTH (0.9433) and QTcBZT (0.9225) but not QTcFRD (0.9338). The Ac, Sn, and Sp of the QT nomogram were 89.08%, 91.30% (95%CI = 86.89-94.61), and 87.33% (95%CI = 82.96-90.92), respectively, and they were all equal to those of QTcRTH. CONCLUSION: Rautaharju method not only produced minimal errors for QT interval correction but also at QTcRTH 477 ms, it could predict TdP as accurately as QT nomogram and was better than the QTcBZT.