Can we predict patients that will not benefit from invasive mechanical ventilation? A novel scoring system in intensive care: the IMV mortality prediction score (IMPRES)

KUCUK, Ahmet Oguzhan/0000-0002-6993-0519; Kirakli, Cenk/0000-0001-6013-7330; KUCUK, Mehtap PEHLIVANLAR/0000-0003-2247-4074; Aksoy, Iskender/0000-0002-4426-3342WOS: 000504051300010PubMed: 31655511Background/aim: The present study aimed to define the clinical and laboratory criteria for predicting patients that will not benefit from invasive mechanical ventilation (IMV) treatment and determine the prediction of mortality and prognosis of these critical ill patients. Materials and methods: The study was designed as an observational, multicenter, prospective, and cross-sectional clinical study. It was conducted by 75 researchers at 41 centers in intensive care units (ICUs) located in various geographical areas of Turkey. It included a total of 1463 ICU patients who were receiving invasive mechanical ventilation (IMV) treatment. A total of 158 parameters were examined via logistic regression analysis to identify independent risk factors for mortality; using these data, the IMV Mortality Prediction Score (IMPRES) scoring system was developed. Results: The following cut-off scores were used to indicate mortality risk: 8, very high risk. There was a 26.8% mortality rate among the 254 patients who had a total IMPRES score of lower than 2. The mortality rate was 93.3% for patients with total 1M PRES scores of greater than 8 (P < 0.001). Conclusion: The present study included a large number of patients from various geographical areas of the country who were admitted to various types of ICUs, had diverse diagnoses and comorbidities, were intubated with various indications in either urgent or elective settings, and were followed by physicians from various specialties. Therefore, our data are more general and can be applied to a broader population. This study devised a new scoring system for decision-making for critically ill patients as to whether they need to be intubated or not and presents a rapid and accurate prediction of mortality and prognosis prior to ICU admission using simple clinical data

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P &lt; 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)