Minimal shedding of the glycocalyx layer during abdominal hysterectomy

Funding Information: This project was funded by the Stockholm City Council, the Kleberg Foundation and Riga Stradins University. Publisher Copyright: © 2017 The Author(s).Background: Surgery with and without hypervolaemia may cause shedding (breakdown) of the endothelial glycocalyx layer, but the severity of this problem is unclear. Methods: In this preliminary report of a larger clinical trial, the plasma and urine concentrations of three biomarkers of glycocalyx shedding (syndecan-1, hyaluronic acid and heparan sulfate) were measured in seven patients before, during, and after open hysterectomy. The fluid therapy consisted of 25ml/kg (approximately 2l) of Ringer's lactate, which was infused over 30min when the surgery started. The resulting plasma volume expansion at the end of the infusion was estimated from the haemodilution. Results: The mean plasma concentration of syndecan-1 was 21.7ng/ml before surgery and averaged 19.7ng/ml during and after the surgery. The plasma concentration of hyaluronic acid decreased from 38.0 to 27.7ng/ml (P<0.05), while heparan sulfate increased from 3.4 to 5.5μg/ml (P<0.05). The urine concentrations of syndecan-1 decreased significantly, while they increased for hyaluronic acid and heparan sulfate. Despite the vigorous fluid load, the urine flow did not exceed 1ml/min. Conclusions: No clear evidence was found for shedding of the endothelial glycocalyx layer when 2l of Ringer's lactate was infused over 30min during abdominal hysterectomy. Urine analyses yielded patterns of changes that differed from those in plasma. Trial registration:ISRCTN81005631. Registered May 17, 2016.publishersversionPeer reviewe

Fibrinolytic system changes in liver surgery : A pilot observational study

Publisher Copyright: © 2018 Ozolina, Nemme, Ozolins, Bjertnæs, Vanags, Gardovskis, Viksna and Krumina.Introduction: Bleeding occurs frequently in liver surgery. Unbalance between tissue plasminogen activator (t-PA) and plasminogen activator inhibitor-1 (PAI-1) concentrations might increase bleeding. Our aim was to analyze perioperative fibrinolytic changes during liver surgery. Materials and Methods: We evaluated 15 patients for inclusion into a prospective pilot study of liver surgery. We assessed fibrinolysis by plasma PAI-1 and t-PA: before surgery (T1), before Pringle maneuver (PM;T2), at the end of surgery (T3) and 24 h postoperatively (T4), and registered demographic and laboratory data, extent and duration of surgery, hemodynamic parameters, blood loss, and transfused volumes of blood products. Data presented as mean ± SD. Significance at P < 0.05. Results: After exclusion of six patients only undergoing biopsies, we included six women and three men aged 49.1 ± 19.6 years; two patients with liver metastases of colorectal cancer and hepatocellular carcinoma, respectively, two with focal nodular hyperplasia, two with hepatic hemangioma, and one with angiomyolipoma. Six patients underwent PM. PAI-1 plasma concentration (n = 9) rose from 6.25 ± 2.25 at T1 through 17.30 ± 14.59 ng/ml at T2 and 28.74 ± 20.4 (p = 0.007) and 22.5 ± 16.0 ng/ml (p = 0.04), respectively, at T3 and T4. Correspondingly, t-PA plasma concentration (n = 9) increased from 4.76 ± 3.08 ng/ml at T1 through 8.00 ± 5.10 ng/ml (p = 0.012) at T2 and decreased to 4.25 ± 2.29 ng/ml and 3.04 ± 3.09 at T3 and T4, respectively. Plasma t-PA level at T2 was significantly different from those at T1, T3, and T4 (p < 0.004). In PM patients, t-PA levels increased from T1, peaked at T2 (p = 0.001), and subsequently decreased at T3 and T4 (p = 0.011 and p = 0.037), respectively. Mean blood loss was 1,377.7 ± 1,062.8 ml; seven patients received blood products. Patients with higher PAI-1 levels at T3 received more fresh frozen plasma (r = 0.79; p = 0.01) and red blood cells (r = 0.88; p = 0.002). Conclusions: During liver surgery, fibrinolysis increased, as evidenced by rises in plasma PAI-1and t-PA, especially after start of surgery and following PM. Transfused volumes of blood products correlated with higher plasma concentrations of PAI-1. Confirming this tendency requires a larger cohort of patients.publishersversionPeer reviewe

Development of a prediction model for postoperative pneumonia A multicentre prospective observational study

BACKGROUND Postoperative pneumonia is associated with increased morbidity, mortality and costs. Prediction models of pneumonia that are currently available are based on retrospectively collected data and administrative coding systems. OBJECTIVE To identify independent variables associated with the occurrence of postoperative pneumonia. DESIGN A prospective observational study of a multicentre cohort (Prospective Evaluation of a RIsk Score for postoperative pulmonary COmPlications in Europe database). SETTING Sixty-three hospitals in Europe. PATIENTS Patients undergoing surgery under general and/or regional anaesthesia during a 7-day recruitment period. MAIN OUTCOME MEASURE The primary outcome was postoperative pneumonia. Definition: the need for treatment with antibiotics for a respiratory infection and at least one of the following criteria: new or changed sputum; new or changed lung opacities on a clinically indicated chest radiograph; temperature more than 38.3 degrees C; leucocyte count more than 12 000 mu l(-1). RESULTS Postoperative pneumonia occurred in 120 out of 5094 patients (2.4%). Eighty-two of the 120 (68.3%) patients with pneumonia required ICU admission, compared with 399 of the 4974 (8.0%) without pneumonia (P < 0.001). We identified five variables independently associated with postoperative pneumonia: functional status [odds ratio (OR) 2.28, 95% confidence interval (CI) 1.58 to 3.12], pre-operative SpO(2) values while breathing room air (OR 0.83, 95% CI 0.78 to 0.84), intra-operative colloid administration (OR 2.97, 95% CI 1.94 to 3.99), intra-operative blood transfusion (OR 2.19, 95% CI 1.41 to 4.71) and surgical site (open upper abdominal surgery OR 3.98, 95% CI 2.19 to 7.59). The model had good discrimination (c-statistic 0.89) and calibration (Hosmer-Lemeshow P = 0.572). CONCLUSION We identified five variables independently associated with postoperative pneumonia. The model performed well and after external validation may be used for risk stratification and management of patients at risk of postoperative pneumonia