Accuracy of Noninvasive Blood Pressure Monitoring in Critically Ill Adults.

Background: Blood pressure (BP) is routinely invasively monitored by an arterial catheter in the intensive care unit (ICU). However, the available data comparing the accuracy of noninvasive methods to arterial catheters for measuring BP in the ICU are limited by small numbers and diverse methodologies. Purpose: To determine agreement between invasive arterial blood pressure monitoring (IABP) and noninvasive blood pressure (NIBP) in critically ill patients. Methods: This was a single center, observational study of critical ill adults in a tertiary care facility evaluating agreement (≤10% difference) between simultaneously measured IABP and NIBP. We measured clinical features at time of BP measurement inclusive of patient demographics, laboratory data, severity of illness, specific interventions (mechanical ventilation and dialysis), and vasopressor dose to identify particular clinical scenarios in which measurement agreement is more or less likely. Results: Of the 1852 critically ill adults with simultaneous IABP and NIBP readings, there was a median difference of 6 mm Hg in mean arterial pressure (MAP), interquartile range (1-12), P < .01. A logistic regression analysis identified 5 independent predictors of measurement discrepancy: increasing doses of norepinephrine (adjusted odds ratio [aOR] 1.10 [95% confidence interval, CI 1.08-1.12] P = .03 for every change in 5 µg/min), lower MAP value (aOR 0.98 [0.98-0.99] P < .01 for every change in 1 mm Hg), higher body mass index (aOR 1.04 [1.01-1.09] P = .01 for an increase in 1), increased patient age (aOR 1.31 [1.30-1.37] P < .01 for every 10 years), and radial arterial line location (aOR 1.74 [1.16-2.47] P = .04). Conclusions: There was broad agreement between IABP and NIBP in critically ill patients over a range of BPs and severity of illness. Several variables are associated with measurement discrepancy; however, their predictive capacity is modest. This may guide future study into which patients may specifically benefit from an arterial catheter.

Responsiveness of Inhaled Epoprostenol in Respiratory Failure due to COVID-19.

BACKGROUND: Inhaled pulmonary vasodilators are used as adjunctive therapies for the treatment of refractory hypoxemia. Available evidence suggest they improve oxygenation in a subset of patients without changing long-term trajectory. Given the differences in respiratory failure due to COVID-19 and "traditional" ARDS, we sought to identify their physiologic impact. METHODS: This is a retrospective observational study of patients mechanically ventilated for COVID-19, from the ICUs of 2 tertiary care centers, who received inhaled epoprostenol (iEpo) for the management of hypoxemia. The primary outcome is change in PaO2/FiO2. Additionally, we measured several patient level features to predict iEpo responsiveness (or lack thereof). RESULTS: Eighty patients with laboratory confirmed SARS-CoV2 received iEpo while mechanically ventilated and had PaO2/FiO2 measured before and after. The median PaO2/FiO2 prior to receiving iEpo was 92 mmHg and interquartile range (74 - 122). The median change in PaO2/FiO2 was 9 mmHg (-9 - 37) corresponding to a 10% improvement (-8 - 41). Fifty-percent (40 / 80) met our a priori definition of a clinically significant improvement in PaO2/FiO2 (increase in 10% from the baseline value). Prone position and lower PaO2/FiO2 when iEpo was started predicted a more robust response, which held after multivariate adjustment. For proned individuals, improvement in PaO2/FiO2 was 14 mmHg (-6 to 45) vs. 3 mmHg (-11 - 20), p = 0.04 for supine individuals; for those with severe ARDS (PaO2/FiO2 < 100, n = 49) the median improvement was 16 mmHg (-2 - 46). CONCLUSION: Fifty percent of patients have a clinically significant improvement in PaO2/FiO2 after the initiation of iEpo. This suggests it is worth trying as a rescue therapy; although generally the benefit was modest with a wide variability. Those who were prone and had lower PaO2/FiO2 were more likely to respond.

Opioid prescription use in patients with interstitial cystitis.

INTRODUCTION AND HYPOTHESIS: The opioid epidemic is a recent focus of national initiatives to reduce opioid misuse and related addiction. As interstitial cystitis (IC) is a chronic pain state at risk for narcotic use, we sought to assess opioid prescription use in patients with IC. METHODS: Data were accessed from the Virginia All Payers Claims Database. We identified female patients diagnosed with IC from 2011 to 2016 using International Classification of Disease codes. A patient identifier was used to link diagnoses with outpatient prescription claims for opioids using generic product identifiers. We then analyzed opioid prescriptions within 30 days of a claim with a diagnosis of IC. RESULTS: A total of 6,884 patients with an IC diagnosis were identified. The median number of IC claims per patient was 2 (IQR 1 to 4). Mean patient age was 47.8. Twenty-eight percent of patients received at least 1 opioid prescription, with a median of 2 (IQR 1, 4) per patient. Among those receiving opioids, 185 (9.5%) had more than 10 opioid prescriptions, with a maximum of 129. The most common prescriptions were hydrocodone (n = 2,641, 32.3%), oxycodone (n = 2,545, 31.2%), and tramadol (n = 1,195, 14.6%). There was a decline in opioid prescriptions per month for IC, although the rate per IC diagnosis remained stable. CONCLUSIONS: A significant number of patients with IC are treated with opioids. Although the overall number of opioid prescriptions associated with IC had declined, the prescription rate per IC diagnosis had not. As part of the national initiative to reduce opioid use, our data suggest that IC treatment strategies should be examined.

Analysis of Online Urologist Ratings: Are Rating Differences Associated With Subspecialty?

Patients are increasingly using online rating websites to obtain information about physicians and to provide feedback. We performed an analysis of urologist online ratings, with specific focus on the relationship between overall rating and urologist subspecialty. We conducted an analysis of urologist ratings on Healthgrades.com. Ratings were sampled across 4 US geographical regions, with focus across 3 practice types (large and small private practice, academic) and 7 urologic subspecialties. Statistical analysis was performed to assess for differences among subgroup ratings. Data were analyzed for 954 urologists with a mean age of 53 (±10) years. The median overall urologist rating was 4.0 [3.4-4.7]. Providers in an academic practice type or robotics/oncology subspecialty had statistically significantly higher ratings when compared to other practice settings or subspecialties (P < 0.001). All other comparisons between practice types, specialties, regions, and sexes failed to demonstrate statistically significant differences. In our study of online urologist ratings, robotics/oncology subspecialty and academic practice setting were associated with higher overall ratings. Further study is needed to assess reasons underlying this difference.

Online Ratings of Urologists: Comprehensive Analysis.

BACKGROUND: Physician-rating websites are being increasingly used by patients to help guide physician choice. As such, an understanding of these websites and factors that influence ratings is valuable to physicians. OBJECTIVE: We sought to perform a comprehensive analysis of online urology ratings information, with a specific focus on the relationship between number of ratings or comments and overall physician rating. METHODS: We analyzed urologist ratings on the Healthgrades website. The data retrieval focused on physician and staff ratings information. Our analysis included descriptive statistics of physician and staff ratings and correlation analysis between physician or staff performance and overall physician rating. Finally, we performed a best-fit analysis to assess for an association between number of physician ratings and overall rating. RESULTS: From a total of 9921 urology profiles analyzed, there were 99,959 ratings and 23,492 comments. Most ratings were either 5 ("excellent") (67.53%, 67,505/99,959) or 1 ("poor") (24.22%, 24,218/99,959). All physician and staff performance ratings demonstrated a positive and statistically significant correlation with overall physician rating (P<.001 for all analyses). Best-fit analysis demonstrated a negative relationship between number of ratings or comments and overall rating until physicians achieved 21 ratings or 6 comments. Thereafter, a positive relationship was seen. CONCLUSIONS: In our study, a dichotomous rating distribution was seen with more than 90% of ratings being either excellent or poor. A negative relationship between number of ratings or comments and overall rating was initially seen, after which a positive relationship was demonstrated. Combined, these data suggest that physicians can benefit from understanding online ratings and that proactive steps to encourage patient rating submissions may help optimize overall rating.