Pooled analysis of WHO Surgical Safety Checklist use and mortality after emergency laparotomy

Background The World Health Organization (WHO) Surgical Safety Checklist has fostered safe practice for 10 years, yet its place in emergency surgery has not been assessed on a global scale. The aim of this study was to evaluate reported checklist use in emergency settings and examine the relationship with perioperative mortality in patients who had emergency laparotomy. Methods In two multinational cohort studies, adults undergoing emergency laparotomy were compared with those having elective gastrointestinal surgery. Relationships between reported checklist use and mortality were determined using multivariable logistic regression and bootstrapped simulation. Results Of 12 296 patients included from 76 countries, 4843 underwent emergency laparotomy. After adjusting for patient and disease factors, checklist use before emergency laparotomy was more common in countries with a high Human Development Index (HDI) (2455 of 2741, 89.6 per cent) compared with that in countries with a middle (753 of 1242, 60.6 per cent; odds ratio (OR) 0.17, 95 per cent c.i. 0.14 to 0.21, P <0001) or low (363 of 860, 422 per cent; OR 008, 007 to 010, P <0.001) HDI. Checklist use was less common in elective surgery than for emergency laparotomy in high-HDI countries (risk difference -94 (95 per cent c.i. -11.9 to -6.9) per cent; P <0001), but the relationship was reversed in low-HDI countries (+121 (+7.0 to +173) per cent; P <0001). In multivariable models, checklist use was associated with a lower 30-day perioperative mortality (OR 0.60, 0.50 to 073; P <0.001). The greatest absolute benefit was seen for emergency surgery in low- and middle-HDI countries. Conclusion Checklist use in emergency laparotomy was associated with a significantly lower perioperative mortality rate. Checklist use in low-HDI countries was half that in high-HDI countries.Peer reviewe

In silico ordinary differential equation/partial differential equation hemodialysis model estimates methadone removal during dialysis

Oscar A Linares,1 William E Schiesser,2 Jeffrey Fudin,3&ndash;6 Thien C Pham,6 Jeffrey J Bettinger,6 Roy O Mathew,6 Annemarie L Daly7 1Translational Genomic Medicine Lab, Plymouth Pharmacokinetic Modeling Study Group, Plymouth, MI, 2Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA, 3University of Connecticut School of Pharmacy, Storrs, CT, 4Western New England College of Pharmacy, Springfield, MA, 5Albany College of Pharmacy and Health Sciences, Albany, NY, 6Stratton VA Medical Center, Albany, NY, 7Grace Hospice of Ann Arbor, Ann Arbor, MI, USA Background: There is a need to have a model to study methadone&rsquo;s losses during hemodialysis to provide informed methadone dose recommendations for the practitioner. Aim: To build a one-dimensional (1-D), hollow-fiber geometry, ordinary differential equation (ODE) and partial differential equation (PDE) countercurrent hemodialyzer model (ODE/PDE model). Methodology: We conducted a cross-sectional study in silico that evaluated eleven hemodialysis patients. Patients received a ceiling dose of methadone hydrochloride 30 mg/day. Outcome measures included: the total amount of methadone removed during dialysis; methadone&rsquo;s overall intradialytic mass transfer rate coefficient, km; and, methadone&rsquo;s removal rate, jME. Each metric was measured at dialysate flow rates of 250 mL/min and 800 mL/min. Results: The ODE/PDE model revealed a significant increase in the change of methadone&rsquo;s mass transfer with increased dialysate flow rate, %&Delta; km=18.56, P=0.02, N=11. The total amount of methadone mass transferred across the dialyzer membrane with high dialysate flow rate significantly increased (0.042&plusmn;0.016 versus 0.052&plusmn;0.019 mg/kg, P=0.02, N=11). This was accompanied by a small significant increase in methadone&rsquo;s mass transfer rate (0.113&plusmn;0.002 versus 0.014&plusmn;0.002 mg/kg/h, P=0.02, N=11). The ODE/PDE model accurately predicted methadone&rsquo;s removal during dialysis. The absolute value of the prediction errors for methadone&#39;s extraction and throughput were less than 2%. Conclusion: ODE/PDE modeling of methadone&rsquo;s hemodialysis is a new approach to study methadone&rsquo;s removal, in particular, and opioid removal, in general, in patients with end-stage renal disease on hemodialysis. ODE/PDE modeling accurately quantified the fundamental phenomena of methadone&rsquo;s mass transfer during hemodialysis. This methodology may lead to development of optimally designed intradialytic opioid treatment protocols, and allow dynamic monitoring of outflow plasma opioid concentrations for model predictive control during dialysis in humans. Keywords: methadone, hemodialysis, renal failure, modelin

In silico ordinary differential equation/partial differential equation hemodialysis model estimates methadone removal during dialysis

Oscar A Linares,1 William E Schiesser,2 Jeffrey Fudin,3&ndash;6 Thien C Pham,6 Jeffrey J Bettinger,6 Roy O Mathew,6 Annemarie L Daly7 1Translational Genomic Medicine Lab, Plymouth Pharmacokinetic Modeling Study Group, Plymouth, MI, 2Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA, 3University of Connecticut School of Pharmacy, Storrs, CT, 4Western New England College of Pharmacy, Springfield, MA, 5Albany College of Pharmacy and Health Sciences, Albany, NY, 6Stratton VA Medical Center, Albany, NY, 7Grace Hospice of Ann Arbor, Ann Arbor, MI, USA Background: There is a need to have a model to study methadone&rsquo;s losses during hemodialysis to provide informed methadone dose recommendations for the practitioner. Aim: To build a one-dimensional (1-D), hollow-fiber geometry, ordinary differential equation (ODE) and partial differential equation (PDE) countercurrent hemodialyzer model (ODE/PDE model). Methodology: We conducted a cross-sectional study in silico that evaluated eleven hemodialysis patients. Patients received a ceiling dose of methadone hydrochloride 30 mg/day. Outcome measures included: the total amount of methadone removed during dialysis; methadone&rsquo;s overall intradialytic mass transfer rate coefficient, km; and, methadone&rsquo;s removal rate, jME. Each metric was measured at dialysate flow rates of 250 mL/min and 800 mL/min. Results: The ODE/PDE model revealed a significant increase in the change of methadone&rsquo;s mass transfer with increased dialysate flow rate, %&Delta; km=18.56, P=0.02, N=11. The total amount of methadone mass transferred across the dialyzer membrane with high dialysate flow rate significantly increased (0.042&plusmn;0.016 versus 0.052&plusmn;0.019 mg/kg, P=0.02, N=11). This was accompanied by a small significant increase in methadone&rsquo;s mass transfer rate (0.113&plusmn;0.002 versus 0.014&plusmn;0.002 mg/kg/h, P=0.02, N=11). The ODE/PDE model accurately predicted methadone&rsquo;s removal during dialysis. The absolute value of the prediction errors for methadone&#39;s extraction and throughput were less than 2%. Conclusion: ODE/PDE modeling of methadone&rsquo;s hemodialysis is a new approach to study methadone&rsquo;s removal, in particular, and opioid removal, in general, in patients with end-stage renal disease on hemodialysis. ODE/PDE modeling accurately quantified the fundamental phenomena of methadone&rsquo;s mass transfer during hemodialysis. This methodology may lead to development of optimally designed intradialytic opioid treatment protocols, and allow dynamic monitoring of outflow plasma opioid concentrations for model predictive control during dialysis in humans. Keywords: methadone, hemodialysis, renal failure, modelin

Citizen science to monitor the distribution of the Egyptian mongoose in southern Spain: who provide the most reliable information?

The Egyptian mongoose (Herpestes ichneumon L.) is a medium-size carnivore widely distributed in Africa and in a small part of southern Europe, the Iberian Peninsula, where mongoose populations have recently expanded. The mongoose is relatively easily detectable because of its diurnal habits and because it is the only species of Herpestidae occurring in the Iberian Peninsula. Therefore, its distribution could be monitored through citizen science. In this sense, information provided by stakeholders that make frequent use of natural environments, including hunters, landowners, or wildlife rangers, would be potentially very valuable. Nevertheless, the accuracy of the information provided by these stakeholders as regards mongoose occurrence has never been tested. To do so, we compared mongoose occurrences gathered through field transects (i.e., 2-km walking surveys in which direct observations and indirect signs were recorded) carried out in 218 Andalusian municipalities during 2010–2015 with those obtained through questionnaires conducted in 2016 to hunters (n = 251), landowners (n = 116), and wildlife rangers (n = 133). We did not find any significant difference between mongoose distribution estimated by the reference method (i.e., field surveys) and by questionnaire to wildlife rangers. In contrast, mongoose occurrences reported by hunters and landowners were significantly correlated among them, but not with those collected in field transects (nor with those provided by the rangers). This suggests that a participatory network for monitoring mongoose distribution could rely on the information provided by wildlife rangers. Previous studies showed that hunters can provide useful information from less accessible areas like private estates where official data are not collected. In this sense, our results suggest that further effort is needed to incorporate hunters and landowners in a participatory network to monitor mongoose distribution, and this could include collaborative actions to promote their involvement in addition to increasing their skills in mongoose detection.This study is framed within the projects INIA-CON15-189, RTI2018-096348-RC21, and SBPLY/17/180501/000184