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Healthcare provider burnout, a growing global concern, negatively impacts both the well-being of healthcare professionals and the quality of services. As healthcare systems grapple with rising patient expectations and the integration of new medical technologies, this multifaceted issue presents significant psychological and physiological challenges for providers. Urgent research and intervention are needed to ensure effective patient care and the health of providers.This brief review critically examines the relationship between provider burnout and the quality of healthcare services. It explores the psychological and physiological dimensions of burnout, emphasizing its effects on providers' interpersonal skills, clinical competencies, and overall well-being. Furthermore, the review discusses the implications of burnout for healthcare organizations and underscores the necessity for effective interventions at both individual and systemic levels to mitigate its impact.The review advocates for future research to enhance our understanding of this complex issue and its wide-reaching effects on the quality of healthcare services.

Abstract The wind resource assessment community has long had the goal of reducing the bias between wind plant pre‐construction energy yield assessment (EYA) and the observed annual energy production (AEP). This comparison is typically made between the 50% probability of exceedance (P50) value of the EYA and the long‐term corrected operational AEP (hereafter OA AEP) and is known as the P50 bias. The industry has critically lacked an independent analysis of bias investigated across multiple consultants to identify the greatest sources of uncertainty and variance in the EYA process and the best opportunities for uncertainty reduction. The present study addresses this gap by benchmarking consultant methodologies against each other and against operational data at a scale not seen before in industry collaborations. We consider data from 10 wind plants in North America and evaluate discrepancies between eight consultancies in the steps taken from estimates of gross to net energy. Consultants tend to overestimate the gross energy produced at the turbines and then compensate by further overestimating downstream losses, leading to a mean P50 bias near zero, still with significant variability among the individual wind plants. Within our data sample, we find that consultant estimates of all loss categories, except environmental losses, tend to reduce the project‐to‐project variability of the P50 bias. The disagreement between consultants, however, remains flat throughout the addition of losses. Finally, we find that differences in consultants' estimates of project performance can lead to differences up to $10/MWh in the levelized cost of energy for a wind plant.

Introduction: The ferritin–lymphocyte ratio (FLR) is a novel inflammatory biomarker for the assessment of acute COVID-19 patients. However, the prognostic value of FLR for predicting adverse clinical outcomes in COVID-19 remains unclear, which hinders its clinical translation. Methods: We characterised the prognostic value of FLR in COVID-19 patients, as compared to established inflammatory markers. Results: In 217 study patients (69 years [IQR: 55–82]; 60% males), FLR was weakly correlated with CRP (R = 0.108, p = 0.115) and white cell count (R = −0.144; p = 0.034). On ROC analysis, an FLR cut-off of 286 achieved a sensitivity of 86% and a specificity of 30% for predicting inpatient mortality (AUC 0.60, 95% CI: 0.53–0.67). The negative predictive values of FLR for ruling out mortality, non-invasive ventilation requirement and critical illness (intubation and/or ICU admission) were 86%, 85% and 93%, respectively. FLR performed similarly to CRP (AUC 0.60 vs. 0.64; p = 0.375) for predicting mortality, but worse than CRP for predicting non-fatal outcomes (all p < 0.05). On Kaplan–Meier analysis, COVID-19 patients with FLR values > 286 had worse inpatient survival than patients with FLR ≤ 286, p = 0.041. Conclusions: FLR has prognostic value in COVID-19 patients, and appears unrelated to other inflammatory markers such as CRP and WCC. FLR exhibits high sensitivity and negative predictive values for adverse clinical outcomes in COVID-19, and may be a good “rule-out” test. Further work is needed to improve the sensitivity of FLR and validate its role in prospective studies for guiding clinical management.

IntroductionAssessment of inpatient mortality risk in COVID-19 patients is important for guiding clinical decision-making. High sensitivity cardiac troponin T (hs-cTnT) is a biomarker of cardiac injury associated with a worse prognosis in COVID-19. We explored how hs-cTnT could potentially be used in clinical practice for ruling in and ruling out mortality in COVID-19.MethodWe tested the diagnostic value of hs-cTnT in laboratory-confirmed COVID-19 patients (≥18 years old) admitted to the Royal Berkshire Hospital (UK) between 1st March and 10th May 2020. A normal hs-cTnT was defined as a value within the 99th percentile of healthy individuals (≤14 ng/L), and an elevated hs-cTnT was defined as >14 ng/L. Adverse clinical outcome was defined as inpatient mortality related to COVID-19.ResultsA total of 191 COVID-19 patients (62% male; age 66±16 years) had hs-cTnT measured on admission. Of these patients, 124 (65%) had elevated hs-cTnT and 67 (35%) had normal hs-cTnT. On a group level, patients with elevated hs-cTnT had worse inpatient survival (p = 0.0014; Kaplan-Meier analysis) and higher risk of inpatient mortality (HR 5.84 [95% CI 1.29-26.4]; p = 0.02; Cox multivariate regression) compared to patients with normal hs-cTnT. On a per-patient level, a normal hs-cTnT had a negative predictive value of 94% (95% CI: 85-98%) for ruling out mortality, whilst an elevated hs-cTnT had a low positive predictive value of 38% (95% CI: 39-47%) for ruling in mortality.ConclusionsIn this study cohort of COVID-19 patients, the potential clinical utility of hs-cTnT appears to rest in ruling out inpatient mortality. This finding, if prospectively validated in a larger study, may allow hs-cTnT to become an important biomarker to facilitate admission-avoidance and early safe discharge.

Pulmonary carcinosarcomas are rare biphasic lung tumors comprised of malignant epithelial and malignant mesenchymal components. The most common heterologous sarcomatous elements are osteosarcoma, rhabdomyosarcoma, and chondrosarcoma; a heterologous angiosarcoma component in a pulmonary carcinosarcoma is exceedingly rare. We report a case of a pulmonary carcinosarcoma containing adenocarcinoma, squamous cell carcinoma, undifferentiated malignant spindle cell, and heterologous angiosarcoma components. The patient, a 64-year-old woman, had initially presented to medical attention with hemoptysis. Although the tumor was thought to be confined to the lung at resection (pT3N0), she developed multiple metastatic foci within 3 weeks of lobectomy and required the evacuation of an intraparenchymal left occipital hematoma secondary to a hemorrhagic intra-axial focus of metastatic carcinosarcoma. She died 6 weeks after her primary lung resection from rapidly progressive metastatic disease. We hope the description and discussion provided herein will further the medical community's understanding of this rare malignancy.

Background: CRB-65 (Confusion; Respiratory rate ≥ 30/min; Blood pressure ≤ 90/60 mmHg; age ≥ 65 years) is a risk score for prognosticating patients with COVID-19 pneumonia. However, a significant proportion of COVID-19 patients have normal chest X-rays (CXRs). The influence of CXR abnormalities on the prognostic value of CRB-65 is unknown, limiting its wider applicability. Methods: We assessed the influence of CXR abnormalities on the prognostic value of CRB-65 in COVID-19. Results: In 589 study patients (71 years (IQR: 57–83); 57% males), 186 (32%) had normal CXRs. On ROC analysis, CRB-65 performed similarly in patients with normal vs. abnormal CXRs for predicting inpatient mortality (AUC 0.67 ± 0.05 vs. 0.69 ± 0.03). In patients with normal CXRs, a CRB-65 of 0 ruled out mortality, NIV requirement and critical illness (intubation and/or ICU admission) with negative predictive values (NPVs) of 94%, 98% and 99%, respectively. In patients with abnormal CXRs, a CRB-65 of 0 ruled out the same endpoints with NPVs of 91%, 83% and 86%, respectively. Patients with low CRB-65 scores had better inpatient survival than patients with high CRB-65 scores, irrespective of CXR abnormalities (all p < 0.05). Conclusions: CRB-65, CXR and CRP are independent predictors of mortality in COVID-19. Adding CXR findings (dichotomised to either normal or abnormal) to CRB-65 does not improve its prognostic accuracy. A low CRB-65 score of 0 may be a good rule-out test for adverse clinical outcomes in COVID-19 patients with normal or abnormal CXRs, which deserves prospective validation.

Background: In COVID-19 patients, lymphocyte–CRP ratio (LCR) is a promising biomarker for predicting adverse clinical outcomes. How well LCR performs compared to conventional inflammatory markers for prognosticating COVID-19 patients remains unclear, which hinders the clinical translation of this novel biomarker. Methods: In a cohort of COVID-19 inpatients, we characterised the clinical applicability of LCR by comparing its prognostic value against conventional inflammatory markers for predicting inpatient mortality and a composite of mortality, invasive/non-invasive ventilation and intensive care unit admissions. Results: Of the 413 COVID-19 patients, 100 (24%) patients suffered inpatient mortality. On Receiver Operating Characteristics analysis, LCR performed similarly to CRP for predicting mortality (AUC 0.74 vs. 0.71, p = 0.049) and the composite endpoint (AUC 0.76 vs. 0.76, p = 0.812). LCR outperformed lymphocyte counts (AUC 0.74 vs. 0.66, p = 0.002), platelet counts (AUC 0.74 vs. 0.61, p = 0.003) and white cell counts (AUC 0.74 vs. 0.54, p < 0.001) for predicting mortality. On Kaplan–Meier analysis, patients with a low LCR (below a 58 cut-off) had worse inpatient survival than patients with other LCR values (p < 0.001). Conclusion: LCR appears comparable to CRP, but outperformed other inflammatory markers, for prognosticating COVID-19 patients. Further studies are required to improve the diagnostic value of LCR to facilitate clinical translation.