Social deprivation aggravates post-operative morbidity in carcinologic colorectal surgery: Results of the COINCIDE multicenter study

Alvès, Arnaud; Civet, Alexandre; Laurent, Alexis; Parc, Yann; Penna, Christophe; Msika, Simon; Hirsch, M.; Pocard, Marc; Coincide, Groupe

doi:10.1016/j.jviscsurg.2020.07.007

Cited by 9 publications

(6 citation statements)

References 43 publications

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“…Age is recognized as a nonmodifiable independent risk factor for poor surgical outcomes owing to the inevitable sequelae of sarcopenia, which decreases physical and functional reserves 9,10 . In populations of older people, physiological reserves are further diminished with other comorbidities, such as ischemic heart disease or chronic kidney disease.…”

Section: Introductionmentioning

confidence: 99%

“…7,8 Age is recognized as a nonmodifiable independent risk factor for poor surgical outcomes owing to the inevitable sequelae of sarcopenia, which decreases physical and functional reserves. 9,10 In populations of older people, physiological reserves are further diminished with other comorbidities, such as ischemic heart disease or chronic kidney disease. This deficit in reserves not only predisposes aged patients to having an increased risk of surgical and anesthetic complications but also results in them taking a much longer time to recover from uncomplicated surgeries.…”

Section: Introductionmentioning

confidence: 99%

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Structured presurgery prehabilitation for aged patients undergoing elective surgery significantly improves surgical outcomes and reduces cost: A nonrandomized sequential comparative prospective cohort study

et al. 2021

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Background With increasing global life expectancy, the number of major surgeries performed on aged adults invariably increases. This study aimed to examine the effectiveness of a structured prehabilitative program for aged colorectal cancer patients in improving short‐term surgical outcomes. Methods A prospective philanthropically sponsored Programme for Enhanced Elderly Recovery at Sengkang General Hospital (PEERS) was initiated in February 2017 for patients ≥70‐years‐old who were due to undergo elective colectomies. These patients were put through a 2‐ to 4‐week‐long program before surgery, which included geriatric assessment, nutrition supplementation, and resistance training. They were compared with patients from a similar age group before PEERS was introduced (non‐PEERS). Results Fifty‐eight patients, with a median age of 78.5 (70–93) years, were recruited from a single institution to undergo PEERS. Baseline characteristics between the groups were similar. There was no significant improvement of anthropometric and functional characteristics before and after PEERS. Duration of hospitalization was shorter in the PEERS group (9 vs 11 days, P = 0.01). Both groups had similar 30‐days’ morbidity rates (8.6% vs 17.4%, P = 0.26). The PEERS group had significant improvement in their median EuroQol‐5 Dimension score (0.70 presurgery to 0.80 6‐months’ postsurgery, P = 0.01). After multivariate analysis, the average duration of hospitalization in the PEERS group was 6.8 days shorter (P = 0.018; CI, 1.2–12.4) after adjusting for modality of surgery and complications. This represented a cost saving of USD$11,838.80. Conclusion A standardized prehabilitation program for aged adults reduced the duration of hospitalization, improved the quality of life after surgery, and reduced costs.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structured presurgery prehabilitation for aged patients undergoing elective surgery significantly improves surgical outcomes and reduces cost: A nonrandomized sequential comparative prospective cohort study

et al. 2021

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“…Q-Finder was applied in the field of diabetes to many other research questions, such as the detection of patient profiles that benefit the most of SGLT2i compared to DDP4i in terms of renal function preservation, using Electronic Health Record data (Zhou al., 2018;Zhou et al, 2019); the identification of profiles of patients who better control their blood sugar, using data from pooled observational studies (Rollot, 2019, "Reali project"); and the discovery of new predictors of diabetic ketoacidosis (DKA), a serious complication of type 1 diabetes, using data from a national diabetes registry (Ibald-Mulli et al, 2019). Q-Finder was also successfully applied in the context of several other pathologies such as hypophosphatasia, using SNPs data (Mornet et al, 2020), dry eye disease using prospective clinical trials data (Amrane et al, 2015), and cancer using clinical data from RCTs (Nabholtz, 2012;Dumontet et al, 2016;Dumontet et al, 2018;Alves et al, 2020) or transcriptomic data from a research cohort (Adam et al, 2016). The Q-Finder approach is indeed generic by design and can be applied to any pathology and research questions, as can many SD algorithms, provided that the data can be represented in tabular form.…”

Section: Generalization To Other Pathologies or Research Questionsmentioning

confidence: 99%

“…For further details, an in-depth discussion of Q-Finder is also proposed in Section 14 of supplementary materials. This approach has been applied in several therapeutic areas, with published examples available ( Nabholtz, 2012 ; Eveno, 2014 ; Amrane et al, 2015 ; Adam et al, 2016 ; Dumontet et al, 2016 ; Gaston-Mathe, 2017 ; Dumontet et al, 2018 ; Rollot, 2019 ; Zhou et al, 2018 ; Ibald-Mulli, 2019 ; Zhou et al, 2019 ; Alves et al, 2020 ; Mornet, 2020 ).…”

Section: Q-finder’s Pipeline To Increase Credible Findings Generationmentioning

confidence: 99%

Q-Finder: An Algorithm for Credible Subgroup Discovery in Clinical Data Analysis — An Application to the International Diabetes Management Practice Study

Esnault¹,

Gadonna²,

Queyrel

et al. 2020

Front. Artif. Intell.

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Addressing the heterogeneity of both the outcome of a disease and the treatment response to an intervention is a mandatory pathway for regulatory approval of medicines. In randomized clinical trials (RCTs), confirmatory subgroup analyses focus on the assessment of drugs in predefined subgroups, while exploratory ones allow a posteriori the identification of subsets of patients who respond differently. Within the latter area, subgroup discovery (SD) data mining approach is widely used—particularly in precision medicine—to evaluate treatment effect across different groups of patients from various data sources (be it from clinical trials or real-world data). However, both the limited consideration by standard SD algorithms of recommended criteria to define credible subgroups and the lack of statistical power of the findings after correcting for multiple testing hinder the generation of hypothesis and their acceptance by healthcare authorities and practitioners. In this paper, we present the Q-Finder algorithm that aims to generate statistically credible subgroups to answer clinical questions, such as finding drivers of natural disease progression or treatment response. It combines an exhaustive search with a cascade of filters based on metrics assessing key credibility criteria, including relative risk reduction assessment, adjustment on confounding factors, individual feature’s contribution to the subgroup’s effect, interaction tests for assessing between-subgroup treatment effect interactions and tests adjustment (multiple testing). This allows Q-Finder to directly target and assess subgroups on recommended credibility criteria. The top-k credible subgroups are then selected, while accounting for subgroups’ diversity and, possibly, clinical relevance. Those subgroups are tested on independent data to assess their consistency across databases, while preserving statistical power by limiting the number of tests. To illustrate this algorithm, we applied it on the database of the International Diabetes Management Practice Study (IDMPS) to better understand the drivers of improved glycemic control and rate of episodes of hypoglycemia in type 2 diabetics patients. We compared Q-Finder with state-of-the-art approaches from both Subgroup Identification and Knowledge Discovery in Databases literature. The results demonstrate its ability to identify and support a short list of highly credible and diverse data-driven subgroups for both prognostic and predictive tasks.

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“…For further details, an in-depth discussion of Q-Finder is also proposed in Section 14 of supplementary materials. This approach has been applied in several therapeutic areas, with published examples available (Nabholtz, 2012;Eveno, 2014;Amrane et al, 2015;Adam et al, 2016;Dumontet et al, 2016;Gaston-Mathe, 2017;Dumontet et al, 2018;Rollot, 2019;Zhou et al, 2018;Ibald-Mulli, 2019;Zhou et al, 2019;Alves et al, 2020;Mornet, 2020).…”

Section: Q-finder's Pipeline To Increase Credible Findings Generationmentioning

confidence: 99%

datasheet1.pdf

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Social deprivation aggravates post-operative morbidity in carcinologic colorectal surgery: Results of the COINCIDE multicenter study

Cited by 9 publications

References 43 publications

Structured presurgery prehabilitation for aged patients undergoing elective surgery significantly improves surgical outcomes and reduces cost: A nonrandomized sequential comparative prospective cohort study

Structured presurgery prehabilitation for aged patients undergoing elective surgery significantly improves surgical outcomes and reduces cost: A nonrandomized sequential comparative prospective cohort study

Q-Finder: An Algorithm for Credible Subgroup Discovery in Clinical Data Analysis — An Application to the International Diabetes Management Practice Study

datasheet1.pdf

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