Current Acute Coronary Syndromes (ACS) rule-out algorithms rely on a combination of clinical assessment and measuring troponin levels. It can take several hours for troponin levels to rise after a myocardial infarction, so initial testing may not show detectable levels of troponin. In order to rule out a false negative result, troponin levels are typically tested again several hours later to look for rising values meaning patients are admitted for observation which has a large resource implication. We developed a machine learning model aimed at improving early discharge at initial assessment. The study was conducted using data from the National Institute for Health Research Health Informatics Collaborative Cardiovascular dataset.(1,2) We trained and tuned a machine learning model (Rapid-RO) using patient data from two separate hospitals to rule-out ACS with simple routine demographic or clinical measurements. The model was then tested for its predictive accuracy in cohorts of patients at four different hospitals from separate time periods. The model was assessed against troponin threshold guided management as recommended by the European Society of Cardiology clinical guidelines. The patient cohorts of the six derived datasets are presented in Figure 1. On the left side are the training and tuning cohorts and the right side are the cohorts from which the derived model was tested. The Rapid-RO machine learning model included input from 11 inputs that had the highest feature importance, including troponin, age, C-reactive protein, urea, platelet count, eGFR, white cell count, haemoglobin, heart failure, diabetes, and hypertension. The Rapid-RO model identified 12037 (35.69%) very low risk patients on top of standard clinical assessment who could have been discharged early, compared with 8967 (26.58%) identified by a troponin threshold approach alone (Figure 2), with significantly fewer missed ACS cases (27 (0.22%) vs. 108 (1.20%)) and similar mortality rates (2 (0.02%) vs. 4 (0.04%) at 30 days). The Rapid-RO model demonstrated a consistently higher rule-out rate for ACS with a lower missed ACS rate across patient subsets, including patients with and without chest pain or COVID-19. The Rapid-RO machine learning model, which uses patient history and initial blood tests, offers a significant advancement in the risk stratification process, presenting a reliable tool for clinicians to rapidly rule out ACS and potentially reduce unnecessary hospital admissions. Its robust performance in diverse patient groups across different time periods, underscores its potential utility in a real-world clinical setting.Figure 1 Figure 2

Enzymatic dissolution of haemothorax is highly effective in the evacuation of proteinaceous material from the pleural space. Its use in postcardiotomy haemothorax has not been described. We report the case of a 4-year-old girl with Fallot's Tetralogy diagnosed at birth. She underwent a total correction of Fallot's Tetralogy at 4 years of age. Chest X-ray taken post-operatively showed a large pleural collection in her right haemithorax. Repeated intraplueral infusion of purified streptokinase into the right upper pleural chest tube greatly reduced the extent of the right haemothorax. Enzymatic dissolution of haemothorax by purified streptokinase has proven to be a rapid and successful method of therapy. It has provided an alternative which is less invasive and has a low morbidity.

Traumatic bronchial rupture is a rare entity. The severity of the trauma often causes lethal injury to other thoracic organs. The incidence in patients with blunt chest trauma admitted to the hospital ranges from 1.5% to 3%. As a rule, early diagnosis and surgical treatment are important to facilitate successful repair of the disruption. We describe an unusual case of bronchial rupture which was diagnosed 15 days after blunt chest trauma and was treated by bronchial stenting. The success of this case involving the left main bronchial rupture provides a feasible alternative to the repair of partial airway disruption and greatly reduces the morbidity.

Video-assisted thoracoscopic surgical interruption (VTSI) of patent ductus arteriosus (PDA) is a relatively new technique when compared to surgical closure and transcatheter endovascular closure. Besides its minimally invasive nature, VTSI is the best option for neonates. Surgical approach may lead to late scoliosis in neonates and the vessels of neonates are too small for the transcatheter approach. VTSI potentially may prove to have lower morbidity and mortality than classic surgical closure of PDA. This article reviews the successful videothoracoscopic ligation of PDA in a 13-year-old girl.