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Increased life expectancy leads to older and frailer surgical patients. Co-management between medical and surgical specialities has proven favourable in complex situations. Selection of patients for co-management is full of difficulties. The aim of this study was to develop a clinical decision support tool to select surgical patients for co-management.Clinical data was collected from patient electronic health records with an ICD-9 code for colorectal surgery from January 2012 to December 2015 at a hospital in Lisbon. The outcome variable consists in co-management signalling. A dataset from 344 patients was used to develop the prediction model and a second data set from 168 patients was used for external validation.Using logistic regression modelling the authors built a five variable (age, burden of comorbidities, ASA-PS status, surgical risk and recovery time) predictive referral model for co-management. This model has an area under the curve (AUC) of 0.86 (95% CI: 0.81 - 0.90), a predictive Brier score of 0.11, a sensitivity of 0.80, a specificity of 0.82 and an accuracy of 81.3%.Early referral of high-risk patients may be valuable to guide the decision on the best level of post-operative clinical care. We developed a simple bedside decision tool with a good discriminatory and predictive performance in order to select patients for comanagement.A simple bed-side clinical decision support tool of patients for co-management is viable, leading to potential improvement in early recognition and management of postoperative complications and reducing the 'failure to rescue'. Generalizability to other clinical settings requires adequate customization and validation.Introdução: O aumento da esperança média de vida leva a que a população cirúrgica seja cada vez mais velha e frágil. Os modelos colaborativos de co-gestão entre especialidades médicas e cirúrgicas têm demonstrado ser favoráveis em situações complexas. A selecção de doentes para co-gestão está repleta de dificuldades. O objectivo deste estudo foi construir uma ferramenta de apoio à decisão para selecionar doentes de submetidos a cirurgia colo-rectal para co-gestão. Material e Métodos: A informação clínica foi colhida dos processos clínicos electrónicos de doentes que tiveram um código ICD-9 de cirurgia colo-rectal no período de janeiro 2012 a dezembro 2015, num hospital em Lisboa. A variável resposta consiste na sinalização para co-gestão. Um conjunto de dados de 344 doentes foi usado para o desenvolvimento do modelo predictivo e, um segundo conjunto de dados de 168 doentes foi usado para a validação externa do modelo. Resultados: Os autores construíram um modelo predictivo, de regressão logística, com cinco variáveis clínicas (idade, carga de co-morbilidades, ASA-PS status, risco cirúrgico e tempo de recobro) para predizer a selecção de doentes para co-gestão. O modelo tem uma área sob a curva (AUC) de 0,86 (95% IC: 0,81 - 0,90), um score predictivo de Brier de 0,11, uma sensibilidade de 0,80, uma especificidade de 0,82 e uma precisão de classificação de 81,3%. Discussão: A sinalização precoce dos doentes de alto risco ajuda a definir o melhor nível de cuidados ao doente operado. Desenvolvemos uma ferramenta de apoio à decisão, simples, aplicável à cabeceira do doente com uma boa capacidade discriminativa e preditiva para seleccionar os doentes para co-gestão. Conclusão: A selecção de doentes para co-gestão entre a cirurgia e a medicina interna permite o reconhecimento e a correcção precoce de complicações pós-operatórias reduzindo o ‘failure to rescue’. A ferramenta, uma vez customizada e validada, poderá ser aplicada em outros cenários clínicos.

Funding: The work of A.L. Papoila and C. Geraldes is partially sponsored by national funds through Fundação Nacional para a Ciência e Tecnologia, Portugal—FCT under the project PEst-OE/MAT/UI0006/2014. The work of Cátia Salgado was supported by the PhD Scholarship SFRH/BD/121875/2016 from Portuguese Foundation for Science & Technology. S. M. Vieira acknowledges the support by Program Investigador FCT (IF/00833/2014) from FCT, co-funded by the European Social Fund (ESF) through the Operational Program Human Potential (POPH). Introduction: Increased life expectancy leads to older and frailer surgical patients. Co-management between medical and surgical specialities has proven favourable in complex situations. Selection of patients for co-management is full of difficulties. The aim of this study was to develop a clinical decision support tool to select surgical patients for co-management. Material and Methods: Clinical data was collected from patient electronic health records with an ICD-9 code for colorectal surgery from January 2012 to December 2015 at a hospital in Lisbon. The outcome variable consists in co-management signalling. A dataset from 344 patients was used to develop the prediction model and a second data set from 168 patients was used for external validation. Results: Using logistic regression modelling the authors built a five variable (age, burden of comorbidities, ASA-PS status, surgical risk and recovery time) predictive referral model for co-management. This model has an area under the curve (AUC) of 0.86 (95% CI: 0.81 - 0.90), a predictive Brier score of 0.11, a sensitivity of 0.80, a specificity of 0.82 and an accuracy of 81.3%. Discussion: Early referral of high-risk patients may be valuable to guide the decision on the best level of post-operative clinical care. We developed a simple bedside decision tool with a good discriminatory and predictive performance in order to select patients for comanagement. Conclusion: A simple bed-side clinical decision support tool of patients for co-management is viable, leading to potential improvement in early recognition and management of postoperative complications and reducing the ‘failure to rescue’. Generalizability to other clinical settings requires adequate customization and validation. publishersversion published

It has been a standard practice to perform mechanical bowel preparation (MBP) prior to colorectal surgery to reduce the risk of colorectal anastomotic leakages (CAL). The latest Cochrane systematic review suggests there is no benefit for MBP in terms of decreasing CAL, but new studies have been published. The aim of this systematic review and meta-analysis is to update current evidence for the effectiveness of preoperative MBP on CAL in patients undergoing colorectal surgery. Consequently, PubMed, MEDLINE, Embase, CENTRAL and CINAHL were searched from 2010 to March 2017 for randomised controlled trials (RCT) that compared the effects of MBP in colorectal surgery on anastomotic leakages. The outcome CAL was expressed in odds ratios and analysed with a fixed-effects analysis in a meta-analysis. Quality assessment was performed by the cochrane risk of bias tool and grades of recommendation, assessment, development and evaluation (GRADE) methodology. Eight studies (1065 patients) were included. The pooled odds ratio showed no significant difference of MBP in colorectal surgery on CAL (odds ratio (OR) = 1.15, 95% CI = 0.68–1.94). According to GRADE methodology, the quality of the evidence was low. To conclude, MBP for colorectal surgery does not lower the risk of CAL. These results should, however, be interpreted with caution due to the small sample sizes and poor quality. Moreover, the usefulness of MBP in rectal surgery is not clear due to the lack of stratification in many studies. Future research should focus on high-quality, adequately powered RCTs in elective rectal surgery to determine the possible effects of MBP.

Objective To compare the enhanced recovery after surgery (ERAS) protocol compliance and clinical outcomes depending on the weekday of surgery. Settings Cohort of consecutive non-selected patients undergoing elective colorectal surgery from January 2012 to March 2015. This retrospective analysis of our prospective database compared patients operated early in the week (Monday and Tuesday) with patients operated in the second half ( late : Thursday, Friday). Primary outcome measures Compliance with the ERAS protocol, functional recovery, complications and length of stay. Results Demographic and surgical details were similar between the early (n=352) and late groups (n=204). Overall compliance with the ERAS protocol was 78% vs 76% for the early and late groups, respectively (p=0.009). Significant differences were notably prolonged urinary drainage and intravenous fluid infusion in the late group. Complication rates and length of stay, however, were not different between surgery on Monday or Tuesday and surgery on Thursday or Friday. Conclusions Application of the ERAS protocol showed only minor differences for patients operated on early or late during the week, and clinical outcomes were similar. A fully implemented ERAS programme appears to work also over the weekend.