Spontaneous subdural hematoma associated to Duret hemorrhage

AbstractSubdural hematoma (SH) is a neurosurgical emergency, usually caused by head trauma. Non-traumatic causes include aneurysm or arterial–venous malformation rupture, coagulopathy and others. We report the case of a 66year-old man who developed apparently unprovoked signs of increased intracranial pressure. Brain computed tomography scan showed an acute spontaneous SH, surgically treated. Throughout surgery, a ruptured cortical artery with intensive bleeding appeared and was cauterized. After surgery, patient remained comatose and a new CT demonstrated Duret hemorrhage at the brainstem. Acute spontaneous SH of arterial origin is rare and highly lethal, in which a good prognosis relies on early diagnosis and treatment

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured

Measurement of the inclusive jet cross-section in proton-proton collisions at √s=7 TeV using 4.5 fb−1 of data with the ATLAS detector

The inclusive jet cross-section is measured in proton-proton collisions at a centre-of-mass energy of 7 TeV using a data set corresponding to an integrated luminosity of 4.5 fb−1 collected with the ATLAS detector at the Large Hadron Collider in 2011. Jets are identified using the anti-kt algorithm with radius parameter values of 0.4 and 0.6. The double-differential cross-sections are presented as a function of the jet transverse momentum and the jet rapidity, covering jet transverse momenta from 100 GeV to 2 TeV. Next-to-leading-order QCD calculations corrected for non-perturbative effects and electroweak effects, as well as Monte Carlo simulations with next-to-leading-order matrix elements interfaced to parton showering, are compared to the measured cross-sections. A quantitative comparison of the measured cross-sections to the QCD calculations using several sets of parton distribution functions is performed

Anesthesia preoperative evaluation clinic (APEC) restructuring plan for improving the quality of surgical patient flow

Introduction: Anesthesia preoperative evaluation clinics (APECs) are useful for high-risk surgical patient care, as they improve perioperative outcomes and optimize patient care flow. At Hospital de Clínicas de Porto Alegre, APEC assesses 20% of all patients undergoing surgery, showing the importance of implementing strategies to improve outpatient clinic efficiency by prioritizing high-risk patients.Methods: Using a specific quality management tool for process improvement (PDCA, which stands for Plan/Do/Check/Act), new protocols were developed for patient referral and preoperative evaluation. Clinical staff was trained in the new routines, and an electronic screening system for patient referral was adopted. Data on patient profiles, referring surgical specialties, type of surgery, and waiting times for appointment and surgical procedure were compared before and after the intervention.Results: APEC performed 1,286 appointments between 2013 and 2016, including 733 pre-intervention and 553 post-intervention. There was a significant decrease in the appointments for patients undergoing minor surgery and an increase in the appointments for those undergoing major surgery.  The waiting time between referral to APEC and first APEC appointment reduced from 46 to 16 days. In addition, there was an increase in vascular, orthopedic, and urology referrals, as well as a reduction in ophthalmology and general surgery referrals. Conclusion: The PDCA method assisted with conceiving, executing, and monitoring the implemented strategies for changing the profile of patients evaluated at APEC.  The major challenge is to measure the long-term impact of this intervention and expand care through specific strategies for surgical specialties and procedures. KEYWORDS: Preanesthesia evaluation; preoperative evaluation; preoperative stratification; risk stratification Introduction: Anesthesia preoperative evaluation clinics (APECs) are useful for high-risk surgical patient care, as they improve perioperative outcomes and optimize patient care flow. At Hospital de Clínicas de Porto Alegre, APEC assesses 20% of all patients undergoing surgery, showing the importance of implementing strategies to improve outpatient clinic efficiency by prioritizing high-risk patients. Methods: Using a specific quality management tool for process improvement (PDCA, which stands for Plan/Do/Check/Act), new protocols were developed for patient referral and preoperative evaluation. Clinical staff was trained in the new routines, and an electronic screening system for patient referral was adopted. Data on patient profiles, referring surgical specialties, type of surgery, and waiting times for appointment and surgical procedure were compared before and after the intervention. Results: APEC performed 1,286 appointments between 2013 and 2016, including 733 pre-intervention and 553 post-intervention. There was a significant decrease in the appointments for patients undergoing minor surgery and an increase in the appointments for those undergoing major surgery.  The waiting time between referral to APEC and first APEC appointment reduced from 46 to 16 days. In addition, there was an increase in vascular, orthopedic, and urology referrals, as well as a reduction in ophthalmology and general surgery referrals.  Conclusion: The PDCA method assisted with conceiving, executing, and monitoring the implemented strategies for changing the profile of patients evaluated at APEC.  The major challenge is to measure the long-term impact of this intervention and expand care through specific strategies for surgical specialties and procedures. KEYWORDS: Preanesthesia evaluation; preoperative evaluation; preoperative stratification; risk stratification

Anesthesia preoperative evaluation clinic (APEC) restructuring plan for improving the quality of surgical patient flow

Introduction: Anesthesia preoperative evaluation clinics (APECs) are useful for high-risk surgical patient care, as they improve perioperative outcomes and optimize patient care flow. At Hospital de Clínicas de Porto Alegre, APEC assesses 20% of all patients undergoing surgery, showing the importance of implementing strategies to improve outpatient clinic efficiency by prioritizing high-risk patients.Methods: Using a specific quality management tool for process improvement (PDCA, which stands for Plan/Do/Check/Act), new protocols were developed for patient referral and preoperative evaluation. Clinical staff was trained in the new routines, and an electronic screening system for patient referral was adopted. Data on patient profiles, referring surgical specialties, type of surgery, and waiting times for appointment and surgical procedure were compared before and after the intervention.Results: APEC performed 1,286 appointments between 2013 and 2016, including 733 pre-intervention and 553 post-intervention. There was a significant decrease in the appointments for patients undergoing minor surgery and an increase in the appointments for those undergoing major surgery.  The waiting time between referral to APEC and first APEC appointment reduced from 46 to 16 days. In addition, there was an increase in vascular, orthopedic, and urology referrals, as well as a reduction in ophthalmology and general surgery referrals. Conclusion: The PDCA method assisted with conceiving, executing, and monitoring the implemented strategies for changing the profile of patients evaluated at APEC.  The major challenge is to measure the long-term impact of this intervention and expand care through specific strategies for surgical specialties and procedures. KEYWORDS: Preanesthesia evaluation; preoperative evaluation; preoperative stratification; risk stratification Introduction: Anesthesia preoperative evaluation clinics (APECs) are useful for high-risk surgical patient care, as they improve perioperative outcomes and optimize patient care flow. At Hospital de Clínicas de Porto Alegre, APEC assesses 20% of all patients undergoing surgery, showing the importance of implementing strategies to improve outpatient clinic efficiency by prioritizing high-risk patients. Methods: Using a specific quality management tool for process improvement (PDCA, which stands for Plan/Do/Check/Act), new protocols were developed for patient referral and preoperative evaluation. Clinical staff was trained in the new routines, and an electronic screening system for patient referral was adopted. Data on patient profiles, referring surgical specialties, type of surgery, and waiting times for appointment and surgical procedure were compared before and after the intervention. Results: APEC performed 1,286 appointments between 2013 and 2016, including 733 pre-intervention and 553 post-intervention. There was a significant decrease in the appointments for patients undergoing minor surgery and an increase in the appointments for those undergoing major surgery.  The waiting time between referral to APEC and first APEC appointment reduced from 46 to 16 days. In addition, there was an increase in vascular, orthopedic, and urology referrals, as well as a reduction in ophthalmology and general surgery referrals.  Conclusion: The PDCA method assisted with conceiving, executing, and monitoring the implemented strategies for changing the profile of patients evaluated at APEC.  The major challenge is to measure the long-term impact of this intervention and expand care through specific strategies for surgical specialties and procedures. KEYWORDS: Preanesthesia evaluation; preoperative evaluation; preoperative stratification; risk stratification