21 research outputs found

    Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

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    Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

    Current Data on and Clinical Insights into the Treatment of First Episode Nonaffective Psychosis: A Comprehensive Review

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    Implementing the most suitable treatment strategies and making appropriate clinical decisions about individuals with a first episode of psychosis (FEP) is a complex and crucial task, with relevant impact in illness outcome. Treatment approaches in the early stages should go beyond choosing the right antipsychotic drug and should also address tractable factors influencing the risk of relapse. Effectiveness and likely metabolic and endocrine disturbances differ among second-generation antipsychotics (SGAs) and should guide the choice of the first-line treatment. Clinicians should be aware of the high risk of cardiovascular morbidity and mortality in schizophrenia patients, and therefore monitoring weight and metabolic changes across time is mandatory. Behavioral and counseling interventions might be partly effective in reducing weight gain and metabolic disturbances. Ziprasidone and aripiprazole have been described to be least commonly associated with weight gain or metabolic changes. In addition, some of the SGAs (risperidone, amisulpride, and paliperidone) have been associated with a significant increase of plasma prolactin levels. Overall, in cases of FEP, there should be a clear recommendation of using lower doses of the antipsychotic medication. If no or minimal clinical improvement is found after 2 weeks of treatment, such patients may benefit from a change or augmentation of treatment. Clinicians should provide accurate information to patients and relatives about the high risk of relapse if antipsychotics are discontinued, even if patients have been symptom free and functionally recovered on antipsychotic treatment for a lengthy period of time.This review was carried out at the Hospital Marque´s de Valdecilla, University of Cantabria, Santander, Spain, with the following Grant support: Instituto de Salud Carlos III PI020499, PI050427, PI060507, Plan Nacional de Drugs Research Grant 2005-Orden sco/3246/2004, SENY Fundacio´ Research Grant CI 2005-0308007, Fundacio´n Marque´s de Valdecilla API07/011 and CIBERSAM
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