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Case Presentation: A 75-year-old man with a history of asbestosis presented to the emergency department with sudden-onset dyspnea and hemoptysis, triggered by coughing. The patient was hemodynamically unstable and in respiratory distress. Computed tomography revealed a massive hemothorax on the left side and compression of the descending thoracic aorta. He underwent emergency surgical exploration after decompression by chest tube insertion. The hemothorax was caused by tears in the pleural adhesions due to asbestosis and induced by coughing.Discussion: Spontaneous hemothorax is a rare subtype of hemothorax. There have been only a few case reports of spontaneous tension hemothorax. In addition to its typical findings, compression of the thoracic descending aorta was observed in our patient. We hypothesize that severely diminished pulmonary compliance contributed to the extremely high intrathoracic pressure, which led to this unusual finding.

Background The challenging clinical dilemma of detecting pulmonary embolism (PE) in suspected patients is encountered in a variety of healthcare settings. We hypothesized that the optimal diagnostic approach to detect these patients in terms of safety and efficiency depends on underlying PE prevalence, case mix, and physician experience, overall reflected by the type of setting where patients are initially assessed. The objective of this study was to assess the capability of ruling out PE by available diagnostic strategies across all possible settings. Methods and findings We performed a literature search (MEDLINE) followed by an individual patient data (IPD) meta-analysis (MA; 23 studies), including patients from self-referral emergency care (n = 12,612), primary healthcare clinics (n = 3,174), referred secondary care (n = 17,052), and hospitalized or nursing home patients (n = 2,410). Multilevel logistic regression was performed to evaluate diagnostic performance of the Wells and revised Geneva rules, both using fixed and adapted D-dimer thresholds to age or pretest probability (PTP), for the YEARS algorithm and for the Pulmonary Embolism Rule-out Criteria (PERC). All strategies were tested separately in each healthcare setting. Following studies done in this field, the primary diagnostic metrices estimated from the models were the 'failure rate' of each strategy-i.e., the proportion of missed PE among patients categorized as 'PE excluded' and 'efficiency'-defined as the proportion of patients categorized as 'PE excluded' among all patients. In self-referral emergency care, the PERC algorithm excludes PE in 21% of suspected patients at a failure rate of 1.12% (95% confidence interval [CI] 0.74 to 1.70), whereas this increases to 6.01% (4.09 to 8.75) in referred patients to secondary care at an efficiency of 10%. In patients from primary healthcare and those referred to secondary care, strategies adjusting D-dimer to PTP are the most efficient (range: 43% to 62%) at a failure rate ranging between 0.25% and 3.06%, with higher failure rates observed in patients referred to secondary care. For this latter setting, strategies adjusting D-dimer to age are associated with a lower failure rate ranging between 0.65% and 0.81%, yet are also less efficient (range: 33% and 35%). For all strategies, failure rates are highest in hospitalized or nursing home patients, ranging between 1.68% and 5.13%, at an efficiency ranging between 15% and 30%. The main limitation of the primary analyses was that the diagnostic performance of each strategy was compared in different sets of studies since the availability of items used in each diagnostic strategy differed across included studies; however, sensitivity analyses suggested that the findings were robust. Conclusions The capability of safely and efficiently ruling out PE of available diagnostic strategies differs for different healthcare settings. The findings of this IPD MA help in determining the optimum diagnostic strategies for ruling out PE per healthcare setting, balancing the trade-off between failure rate and efficiency of each strategy., Author(s): Geert-Jan Geersing 1,*, Toshihiko Takada 1,2, Frederikus A. Klok 3, Harry R. Büller 4, D. Mark Courtney 5, Yonathan Freund 6, Javier Galipienzo 7, Gregoire Le Gal 8, Waleed [...]

Background: Mentorship is a dynamic, reciprocal relationship in which an advanced careerist (mentor) encourages the growth of a novice (mentee). Mentorship may protect the mental health of residents at risk for depression and burnout, yet despite its frequent use and known benefits, limited reports exist regarding the prevalence and mental effects of mentorship on residents in Japan. Methods: We conducted a cross‐sectional study involving postgraduate year 1 and 2 (PGY‐1 and PGY‐2) residents in Japan who took the General Medicine In‐Training Examination (GM‐ITE) at the end of the 2021 academic year. Data on mentorship were collected using surveys administered immediately following GM‐ITE completion. The primary outcome was the Patient Health Questionaire‐2 (PHQ‐2), which consisted depressed mood and loss of interest. A positive response for either item indicated PHQ‐2 positive. We examined associations between self‐reported mentorship and PHQ‐2 by multi‐level analysis. Results: Of 4929 residents, 3266 (66.3%) residents reported having at least one mentor. Compared to residents without any mentor, those with a mentor were associated with a lower likelihood of a positive PHQ‐2 response (adjusted odds ratio [aOR] 0.75; 95% confidence interval [95% CI] 0.65–0.86). Mentor characteristic significantly associated with negative PHQ‐2 response was a formal mentor (aOR; 0.68; 95% CI 0.55–0.84). Conclusions: A mentor‐based support system was positively associated with residents' mental health. Further research is needed to determine the quality of mentorship during clinical residency in Japan. [ABSTRACT FROM AUTHOR]

Aims Risk stratification is used for decisions regarding need for imaging in patients with clinically suspected acute pulmonary embolism (PE). The aim was to develop a clinical prediction model that provides an individualized, accurate probability estimate for the presence of acute PE in patients with suspected disease based on readily available clinical items and D-dimer concentrations. Methods and results An individual patient data meta-analysis was performed based on sixteen cross-sectional or prospective studies with data from 28 305 adult patients with clinically suspected PE from various clinical settings, including primary care, emergency care, hospitalized and nursing home patients. A multilevel logistic regression model was built and validated including ten a priori defined objective candidate predictors to predict objectively confirmed PE at baseline or venous thromboembolism (VTE) during follow-up of 30 to 90 days. Multiple imputation was used for missing data. Backward elimination was performed with a P -value <0.10. Discrimination (c-statistic with 95% confidence intervals [CI] and prediction intervals [PI]) and calibration (outcome:expected [O:E] ratio and calibration plot) were evaluated based on internal-external cross-validation. The accuracy of the model was subsequently compared with algorithms based on the Wells score and D-dimer testing. The final model included age (in years), sex, previous VTE, recent surgery or immobilization, haemoptysis, cancer, clinical signs of deep vein thrombosis, inpatient status, D-dimer (in µg/L), and an interaction term between age and D-dimer. The pooled c-statistic was 0.87 (95% CI, 0.85–0.89; 95% PI, 0.77–0.93) and overall calibration was very good (pooled O:E ratio, 0.99; 95% CI, 0.87–1.14; 95% PI, 0.55–1.79). The model slightly overestimated VTE probability in the lower range of estimated probabilities. Discrimination of the current model in the validation data sets was better than that of the Wells score combined with a D-dimer threshold based on age (c-statistic 0.73; 95% CI, 0.70–0.75) or structured clinical pretest probability (c-statistic 0.79; 95% CI, 0.76–0.81). Conclusion The present model provides an absolute, individualized probability of PE presence in a broad population of patients with suspected PE, with very good discrimination and calibration. Its clinical utility needs to be evaluated in a prospective management or impact study. Registration PROSPERO ID 89366. [ABSTRACT FROM AUTHOR]