A Clinical Decision Tool for Risk Stratifying Patients with Systemic Sclerosis-Related Pulmonary Hypertension.

We devised a scoring system to identify patients with systemic sclerosis (SSc) at risk for pulmonary hypertension (PH) and predict all-cause mortality. Using 7 variables obtained via pulmonary function testing, echocardiography, and computed tomographic chest imaging, we applied the score to a retrospective cohort of 117 patients with SSc. There were 60 (51.3%) who were diagnosed with PH by right heart catheterization. Using a scoring threshold ≥ 0, our decision tool predicted PH with a sensitivity, specificity, and accuracy of 0.87 (95% CI 0.75, 0.94), 0.74 (95% CI 0.60, 0.84), and 0.80 (95% CI 0.72, 0.87), respectively. When adjusted for age at PH diagnosis, sex, and receipt of pulmonary arterial vasodilators, each one-point score increase was associated with an adjusted HR of 1.19 (95% CI 1.05, 1.34) for all-cause mortality. With further validation in external cohorts, our simplified clinical decision tool may better streamline earlier detection of PH in SSc.

Addressing clinician moral distress: Implications from a mixed methods evaluation during Covid-19.

Clinician moral distress has been documented over the past several decades as occurring within numerous healthcare disciplines, often in relation to clinicians' involvement in patients' end-of-life decision-making. The resulting harms impact clinician well-being, patient well-being, and healthcare system functioning. Given Covid-19's catastrophic death toll and associated demands on end-of-life decision-making processes, the pandemic represents a particularly important context within which to understand clinician moral distress. Thus, we conducted a convergent mixed methods study to examine its prevalence, associations with clinicians' demographic and professional characteristics, and contributing circumstances among Veterans Health Administration (VA) clinicians. The study, conducted in April 2021, consisted of a cross-sectional on-line survey of VA clinicians at 20 VA Medical Centers with professional jurisdiction to place life-sustaining treatment orders working who were from a number of select specialties. The survey collected quantitative data on respondents' demographics, clinical practice characteristics, attitudes and behaviors related to goals of care conversations, intensity of moral distress during "peak-Covid," and qualitative data via an open-ended item asking for respondents to describe contributing circumstances if they had indicated any moral distress. To understand factors associated with heightened moral distress, we analyzed quantitative data using bivariate and multivariable regression analyses and qualitative data using a hybrid deductive/inductive thematic approach. Mixed methods analysis followed, whereby we compared the quantitative and qualitative datasets and integrated findings at the analytic level. Out of 3,396 eligible VA clinicians, 323 responded to the survey (9.5% adjusted response rate). Most respondents (81%) reported at least some moral distress during peak-Covid. In a multivariable logistic regression, female gender (OR 3.35; 95% CI 1.53-7.37) was associated with greater odds of moral distress, and practicing in geriatrics/palliative care (OR 0.40; 95% CI 0.18-0.87) and internal medicine/family medicine/primary care (OR 0.46; 95% CI 0.22-0.98) were associated with reduced odds of moral distress compared to medical subspecialties. From the 191 respondents who completed the open-ended item, five qualitative themes emerged as moral distress contributors: 1) patient visitation restrictions, 2) anticipatory actions, 3) clinical uncertainty related to Covid, 4) resource shortages, and 5) personal risk of contracting Covid. Mixed methods analysis found that quantitative results were consistent with these last two qualitative themes. In sum, clinician moral distress was prevalent early in the pandemic. This moral distress was associated with individual-, system-, and situation-level contributors. These identified contributors represent leverage points for future intervention to mitigate clinician moral distress and its negative outcomes during future healthcare crises and even during everyday clinical care.

A Multimodal Prediction Model for Diagnosing Pulmonary Hypertension in Systemic Sclerosis.

OBJECTIVE: Diagnosis of pulmonary hypertension (PH) in systemic sclerosis (SSc) requires an invasive right heart catheterization (RHC), often based on an elevated estimated pulmonary artery systolic pressure on screening echocardiography. However, because of the poor specificity of echocardiography, a greater number of patients undergo RHC than necessary, exposing patients to potentially avoidable complication risks. The development of improved prediction models for PH in SSc may inform decision-making for RHC in these patients. METHODS: We conducted a retrospective study of 130 patients with SSc; 66 (50.8%) were diagnosed with PH by RHC. We used data from pulmonary function testing, electrocardiography, echocardiography, and computed tomography to identify and compare the performance characteristics of 3 models predicting the presence of PH: 1) random forest, 2) classification and regression tree, and 3) logistic regression. For each model, we generated receiver operating curves and calculated sensitivity and specificity. We internally validated models using a train-test split of the data. RESULTS: The random forest model performed best with an area under the curve of 0.92 (95% confidence interval [95% CI] 0.83-1.00), sensitivity of 0.95 (95% CI 0.75-1.00), and specificity of 0.80 (95% CI 0.56-0.94). The 2 most important variables in our random forest model were pulmonary artery diameter on chest computed tomography and diffusing capacity for carbon monoxide on pulmonary function testing. CONCLUSIONS: In patients with SSc, a random forest model can aid in the detection of PH with high sensitivity and specificity and may allow for better patient selection for RHC, thereby minimizing patient risk.

Prognostic Value of Cardiac Axis Deviation in Systemic Sclerosis-Related Pulmonary Hypertension.

OBJECTIVE: Systemic sclerosis-related pulmonary hypertension (SSc-PH) is a common complication of SSc associated with accelerated mortality. The present study was undertaken to investigate whether cardiac axis deviation indicates abnormalities in cardiac function allowing for prognostication of disease severity and mortality. METHODS: This was a retrospective study in which electrocardiograms (ECGs) were reviewed for cardiac axis deviation and their association with echocardiography and cardiopulmonary hemodynamics on right-sided heart catheterization. The primary outcome observed was all-cause mortality from the time of PH diagnosis. RESULTS: ECG results were reviewed from 169 patients with SSc-PH. Right axis deviation (RAD) and left axis deviation (LAD) occurred in 28.4% and 30.8% of patients with SSc-PH, respectively. Compared to those without RAD, patients with RAD exhibited predominantly right-sided cardiac disease on echocardiography and increased PH severity by cardiopulmonary hemodynamics including a greater mean ± SD pulmonary artery pressure (42.0 ± 12.5 mm Hg versus 29.8 ± 7.0 mm Hg) and mean ± SD pulmonary vascular resistance (645.6 ± 443.2 dynes · seconds/cm5 versus 286.3 ± 167.7 dynes · seconds/cm5 ). LAD was associated with predominantly left-sided cardiac disease on echocardiography but was not associated with PH severity on cardiopulmonary hemodynamics. Both RAD (hazard ratio 10.36 [95% confidence interval 4.90-21.93], P < 0.001) and LAD (hazard ratio 2.94 [95% confidence interval 1.53-5.68], P = 0.001) were associated with an increased hazard for all-cause mortality. CONCLUSION: RAD and LAD reflect structural cardiac abnormalities and are associated with poor prognosis in patients with SSc-PH. These findings support the importance of electrocardiography, an inexpensive, widely available noninvasive test, in risk stratification.