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Postbariatric loss of muscle tissue could negatively affect long-term health due to its role in various bodily processes, such as metabolism and functional capacity. This meta-analysis aimed to unravel time-dependent changes in the magnitude and progress of lean body mass (LBM), fat-free mass (FFM), and skeletal muscle mass (SMM) loss following bariatric surgery. A systematic literature search was conducted in Pubmed, Embase, and Web of Science. Fifty-nine studies assessed LBM (n = 37), FFM (n = 20), or SMM (n = 3) preoperatively and ≥1 time points postsurgery. Random-effects meta-analyses were performed to determine pooled loss per outcome parameter and follow-up time point. At 12-month postsurgery, pooled LBM loss was ?8.13 kg [95%CI ?9.01; ?7.26]. FFM loss and SMM loss were ?8.23 kg [95%CI ?10.74; ?5.73] and ?3.18 kg [95%CI ?5.64; ?0.71], respectively. About 55% of 12-month LBM loss occurred within 3-month postsurgery, followed by a more gradual decrease up to 12 months. Similar patterns were seen for FFM and SMM. In conclusion, >8 kg of LBM and FFM loss was observed within 1-year postsurgery. LBM, FFM, and SMM were predominantly lost within 3-month postsurgery, highlighting that interventions to mitigate such losses should be implemented perioperatively.  相似文献   
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Maternal and Child Health Journal - Early life exposures can have an impact on a child’s developmental trajectory and children born late preterm (34–36 weeks gestational age)...  相似文献   
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BackgroundWhile studies have demonstrated favorable outcomes in utilization of primary total shoulder arthroplasty (TSA) for the treatment of glenohumeral osteoarthritis (OA), adverse events such as infections can still occur. Periprosthetic joint infections (PJIs) are associated with worse outcomes and patient morbidity. The purpose of this study was to: (1) compare patient demographics amongst TSA patients with and without PJIs following primary TSA; and (2) identify patient-related risk factors for PJIs following primary TSA.MethodsPatients undergoing primary TSA for the treatment of glenohumeral OA were identified using the Mariner administrative claims database by CPT code 23,472. Laterality modifiers were utilized to ensure PJIs were developing in the correct laterality as those patients undergoing primary TSA. Inclusion for the study group consisted of patients who developed PJIs within 2-years after the index procedure, whereas patients who did not develop PJIs served as the comparison cohort. Primary outcomes analyzed included patient demographics and patient-related risk factors for PJIs following primary TSA. A stepwise backwards elimination multivariate binomial logistic regression analyses was performed to determine the odds (OR) of PJIs in patients undergoing primary TSA. A P value less than .05 was considered statistically significant.ResultsThe query yielded 15,396 patients who underwent primary TSA for glenohumeral OA, of which 191 patients developed PJIs and 15,205 did not develop PJIs. The study found statistically significant differences amongst patients who did and did not develop PJIs following primary TSA with respect to age, sex, and presence of comorbid conditions. Risk factors associated with developing PJIs following primary TSA included: pathologic weight loss (OR: 2.06, P < .0001), obesity (OR: 1.56, P = .0001), male sex (OR: 1.52, P = .007), and peripheral vascular disease (OR: 1.46, P = .022).ConclusionAs the number of primary TSAs for the treatment of glenohumeral OA increase worldwide, identifying modifiable risk-factors to reduce the incidence of infection is critical. The study found various modifiable and non-modifiable risk factors associated with developing PJIs following primary TSA. This study is valuable to orthopedists in order to identify and risk-stratify patients with regard to PJI in the setting of primary TSA for OA.Level of EvidenceLevel III; Case-Control Study  相似文献   
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A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume–outcome relationship into minimum volume regulation (MVR) to increase the quality of care—yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accordingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure’s complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR’s intended benefit: concentrating treatment delivery to improve the quality of care.

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Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.  相似文献   
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Tobacco smoking is associated with a substantially increased risk of postoperative complications. The peri-operative period offers a unique opportunity to support patients to stop tobacco smoking, avoid complications and improve long-term health. This systematic review provides an up-to-date summary of the evidence for tobacco cessation interventions in surgical patients. We conducted a systematic search of randomised controlled trials of tobacco cessation interventions in the peri-operative period. Quantitative synthesis of the abstinence outcomes data was by random-effects meta-analysis. The primary outcome of the meta-analysis was abstinence at the time of surgery, and the secondary outcome was abstinence at 12 months. Thirty-eight studies are included in the review (7310 randomised participants) and 26 studies are included in the meta-analysis (5969 randomised participants). Studies were pooled for subgroup analysis in two ways: by the timing of intervention delivery within the peri-operative period and by the intensity of the intervention protocol. We judged the quality of evidence as moderate, reflecting the degree of heterogeneity and the high risk of bias. Overall, peri-operative tobacco cessation interventions increased successful abstinence both at the time of surgery, risk ratio (95%CI) 1.48 (1.20–1.83), number needed to treat 7; and 12 months after surgery, risk ratio (95%CI) 1.62 (1.29–2.03), number needed to treat 9. More work is needed to inform the design and optimal delivery of interventions that are acceptable to patients and that can be incorporated into contemporary elective and urgent surgical pathways. Future trials should use standardised outcome measures.  相似文献   
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