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The generation of a substantial amount of construction waste (CW) poses significant challenges to the green transition of highway construction projects. However, the construction industry lacks integration of construction waste management (CWM) practices into the construction process. This paper aims to develop a calculation for assessing the performance of CWM to monitor its effectiveness in highway construction. Initially, this study utilizes the Site waste management plan (SWMP) as a foundation and develops a Construction Waste Management Performed Assessment Method (CWMPAM). The extension of CWM is incorporated into earned value management (EVM) to manage costs, schedules, and the performance of CWM within a unified framework. The functionality and sensitivity of CWMPAM and CWM-embedded EVM are validated through pilot testing and scenario analysis. The research results are computerized into a calculator to facilitate the practical application of CWM, and its validity is tested using random cases. CWMPAM and CWM-embedded EVM prove satisfactory in assessing and monitoring the execution and performance of CWM. The developed calculator simplifies the practical application of the outcomes. Essentially, the developed calculator represents a groundbreaking integration of CWM and construction management, enabling project managers to monitor and compare the CWM performance across different segments of highway construction. Not only does this contribute to the green transformation of highway projects, it also promotes high quality and sustainable development in the construction industry.

To develop and validate prediction models for obstetric anal sphincter injury (OASI) in three birth scenarios (first vaginal delivery, vaginal birth after cesarean section and second vaginal delivery). Antenatal and intrapartal predictors were included in the models to construct a web-based, interactive, easy-to-use calculator. All 45 maternity units in Sweden participated in the study, with 609,916 first and second deliveries in gestational week ≥37 + 0 with singleton pregnancies and cephalic presentations between 2009 and 2017. The outcome was OASI, defined as a third- or fourth-degree perineal injury involving the external or internal anal sphincter muscles, or both. We analyzed the relative contribution of predictors with Nagelkerke's R2 (R2N) after minimization of the Bayesian Information Criterion for the predictor selection in a logistic regression with OASI as the binary outcome. Model performance was evaluated according to overall measures, discriminative ability, and calibration, with optimism-correction by a bootstrap procedure. OASI occurred in 25,245 women (4.1%). There were 54 relevant, possible predictors, and 47 predictors were kept as candidates for the final models. We included 28, 40, and 46 predictors for the three scenarios, respectively. Infant birth weight was identified as the primary predictor, contributing 31%–45% of the R2N in the full prediction models, which had R2N values of 9.3%, 7.4%, and 12.9% for each scenario. In two-para women, obstetric information from the first birth was important at the second birth, accounting for 50% of the total predictive information. A sphincter injury in the first vaginal delivery strongly predicted a repeat injury (R2N, 40%). Vacuum delivery in the first and second vaginal delivery contributed 33% and 29% of R2N, respectively. By incorporating information on fetal biometry and labor events, the performance of the models increased substantially (eg, R2N increased from 1.7% to 9.3% in the first scenario). An online calculator was developed (www.sphinctercalc.com). Fetal birth weight is the crucial predictor of sphincter injury, supporting efforts to assess fetal biometrics through imaging techniques. This also applies to obstetric interventions, particularly vacuum delivery, provided that there are alternatives to act upon. The proposed online calculator requires further international validation and refinement before it can be widely used clinically and for women's shared decision-making. A third- or fourth-degree vaginal tear (also known as obstetric anal sphincter injury) occurs in about six in 100 women having their first vaginal birth and may lead to loss of bowel control or holding in wind. This study analyzed existing data from thousands of women who had already delivered 1 or 2 children to build a prediction model that can be used prospectively by health-care professionals and pregnant women to assess a woman's individual risk of having a third- or fourth-degree tear to be able to prevent it occurring. [Display omitted] •Prospective high-quality registry data for predicting anal sphincter injury.•Antenatal and intrapartum predictors were key to the dynamic model.•Emphasizing the vital role of fetal biometry and labor interventions.•Our findings support efforts to promote antenatal access to fetal biometrics.•Interactive calculator for personalized risk assessment www.sphinctercalc.com.

The ACS-NSQIP Surgical Risk Calculator (SRC) is used to predict surgical outcomes, but its accuracy in gastrectomy has been questioned.1,2 We investigated if adding hypoalbuminemia enhances its predictive ability in gastrectomy. We identified gastrectomy patients from the ACS-NSQIP database from 2005 to 2019. We constructed pairs of logistic regression models: one with the existing 21 preoperative risk factors from the SRC and another with the addition of hypoalbuminemia. We evaluated improvement using Likelihood Ratio Test (LRT), Brier scores, and c-statistics. Of 18,070 gastrectomy patients, 34.5 ​% had hypoalbuminemia. Hypoalbuminemia patients had 2.34 higher odds of mortality and 1.79 higher odds of morbidity. Adding hypoalbuminemia to the RC model statistically improved predictions for mortality, cumulative morbidity, pulmonary, renal, and wound complications (LRT p ​< ​0.001). It did not improve predictions for cardiac complications (LRT p ​= ​0.11) Hypoalbuminemia should be considered as an additional variable to the ACS-NSQIP SRC for gastrectomy. •Hypoalbuminemia linked to higher morbidity, mortality in gastrectomy.•Hypoalbuminemia improves NSQIP risk calculator predictions in gastrectomy.•Improved mortality, morbidity, wound, renal, pulmonary complications predictions.•Most measures did not show improvements in predicting cardiac complications.

BackgroundEarly-onset gastric cancer (EOGC, ≤45 years old) is characterized with increasing incidence and more malignant phenotypes compared with late-onset gastric cancer, which exhibits remarkable immune cell infiltration and is potential immunotherapeutic population. Till now, restricted survival information of EOGC is available due to limited case numbers. This study established a novel nomogram to help evaluate cancer-specific survival (CSS) of EOGC patients who underwent gastrectomy, and may provide evidence for predicting patients’ survival.MethodsWe retrospectively enrolled a cohort containing 555 EOGC cases from five independent medical centers in China, among which 388 cases were randomly selected into a training set while the other 167 cases were assigned into the internal validation set. Asian or Pacific Islander (API) patients diagnosed with EOGC during 1975-2016 were retrieved from the SEER database (n=299) and utilized as the external validation cohort. Univariate and multivariate analyses were conducted to test prognostic significances of clinicopathological factors in the training set. Accordingly, two survival nomogram models were established and compared by concordance index (C-index), calibration curve, receiver operating characteristics (ROC) curves and decision curve analyses (DCA).ResultsThe 5-year CSS rate of training cohort was 61.3% with a median survival time as 97.2 months. High consistency was observed on calibration curves in all three cohorts. Preferred nomogram was selected due to its better performance on ROC and DCA results. Accordingly, a novel predicative risk model was introduced to better stratify high-risk EOGC patients with low-risk patients. In brief, the 5-year CSS rates for low-risk groups were 92.9% in training set, 83.1% in internal validation set, 89.9% in combined NQSQS cohort, and 85.3% in SEER-API cohort. In contrast, the 5-year CSS rates decreased to 38.5%, 44.3%, 40.5%, and 36.9% in the high-risk groups of the four cohorts above, respectively. The significant survival difference between high-risk group (HRG) and low-risk group (LRG) indicated the precise accuracy of our risk model. Furthermore, the risk model was validated in patients with different TNM stages, respectively. Finally, an EOGC web-based survival calculator was established with public access, which can help predict prognosis.ConclusionsOur data provided a precise nomogram on predicting CSS of EOGC patients with potential clinical applicability.

This review discusses the most recent evidence for currently available risk stratification tools in the detection of clinically significant prostate cancer (csPCa), and evaluates diagnostic strategies that combine these tools. Novel blood biomarkers, such as the Prostate Health Index (PHI) and 4Kscore, show similar ability to predict csPCa. Prostate cancer antigen 3 (PCA3) is a urinary biomarker that has inferior prediction of csPCa compared to PHI, but may be combined with other markers like TMPRSS2-ERG to improve its performance. Original risk calculators (RCs) have the advantage of incorporating easy to retrieve clinical variables and being freely accessible as a web tool/mobile application. RCs perform similarly well as most novel biomarkers. New promising risk models including novel (genetic) markers are the SelectMDx and Stockholm-3 model (S3M). Prostate magnetic resonance imaging (MRI) has evolved as an appealing tool in the diagnostic arsenal with even stratifying abilities, including in the initial biopsy setting. Merging biomarkers, RCs and MRI results in higher performances than their use as standalone tests. In the current era of prostate MRI, the way forward seems to be multivariable risk assessment based on blood and clinical parameters, potentially extended with information from urine samples, as a triaging test for the selection of candidates for MRI and biopsy.

HMEs (heat and moisture exchangers) are employed in clinical practice to humidify the inspired air in intubated patients. We aimed to develop and experimentally validate a mass based model describing the water input-output equilibrium in the presence of HMEs. The model should serve as a universally applicable basis for the evaluation of the fundamental HME humidification properties performance (mg reversibly stored per breath) and efficiency. A plug flow model was designed using three different locations (gas inlet, moisture benefit and water output) for inspiratory-expiratory flow and humidity measurements. We developed a complete set of algorithms for the calculation of all relevant metrics. Measurements also assessed humidity dependent volume changes. We proved the concept through the validation of humidity predictions without HME in the test setup at target humidities of 37 and 44 mg/l respectively with the inspiratory volume of 0.25, 0.50 and 0.75 l. The concept was applied in the evaluation of a random sample of HMEs. Differences between prediction and measurements ranged between − 1.89 and 2.24 mg/l. For moisture benefit a mean difference of 0.15 mg/l (sd 0.69) was found and for water output of -0.48 mg/l (sd 0.98). Humidification caused a significant volume increase up to 6.6% with respect to the inspired dry air. HME performance results of five HME brands ranged from 5 to 30 mg overall. Performance results derived from moisture benefit and water output agreed within 5% of the common mean. Efficiency results can be above 80% over the whole measurement range or below 20% at high water load depending on the HME brand. Thus, HMEs can be sorted by registering efficiency at the upper bound of the tidal volume range. HMEs for laryngectomized patients (LE-HMEs) showed much lower performances between 2 and 5 mg per breath due to their small size. A novel comprehensive research environment, both theoretical and experimental, enables the assessment of HME properties and gives qualitative and quantitative definitions of HME performance and efficiency for clinical use.

Aims The American College of Surgeons Surgical Risk Calculator (ACS-NSQIP SRC) was designed to predict morbidity and mortality in order to help providing informed consent. This study evaluated its performance in the field of plastic and reconstructive surgery for patients undergoing body contouring and breast reconstruction procedures. Methods A retrospective analysis of patients undergoing body contouring and breast reconstruction procedures from January 1, 2022 to November 1, 2024 was performed. Results The ACS-NSQIP SRC showed good prediction only for severe complications in patients undergoing breast reconstruction with DIEP flap (AUC = 0.727); overall prediction and calibration for the remaining 15 subgroups was poor. The incidence of overall and general complications, as well as length of hospital stay was underestimated. Conclusions The overall performance of the ACS-NSQIP SRC was poor, a finding that underlines the importance of individual decision-making, also considering the surgeon’s expertise and patient-specific characteristics.

Risk prediction models including the Prostate Health Index (phi) for prostate cancer have been well established and evaluated in the Western population. The aim of this study is to build phi-based risk calculators in a prostate biopsy population and evaluate their performance in predicting prostate cancer (PCa) and high-grade PCa (Gleason score ≥7) in the Chinese population. We developed risk calculators based on 635 men who underwent initial prostate biopsy. Then, we validated the performance of prostate-specific antigen (PSA), phi, and the risk calculators in an additional observational cohort of 1045 men. We observed that the phi-based risk calculators (risk calculators 2 and 4) outperformed the PSA-based risk calculator for predicting PCa and high-grade PCa in the training cohort. In the validation study, the area under the receiver operating characteristic curve (AUC) for risk calculators 2 and 4 reached 0.91 and 0.92, respectively, for predicting PCa and high-grade PCa, respectively; the AUC values were better than those for risk calculator 1 (PSA-based model with an AUC of 0.81 and 0.82, respectively) (all P < 0.001). Such superiority was also observed in the stratified population with PSA ranging from 2.0 ng ml to 10.0 ng ml . Decision curves confirmed that a considerable proportion of unnecessary biopsies could be avoided while applying phi-based risk calculators. In this study, we showed that, compared to risk calculators without phi, phi-based risk calculators exhibited superior discrimination and calibration for PCa in the Chinese biopsy population. Applying these risk calculators also considerably reduced the number of unnecessary biopsies for PCa.

To evaluate the effectiveness and safety of the AcrySof IQ PanOptix toric intraocular lens (IOL) with cylinder power of 1.0 D (TFNT20) in a Japanese population with low corneal astigmatism and compare with historical control data for nontoric IOLs. Tokyo Dental College Suidobashi Hospital, Tokyo, Japan. Prospective, single-center study. Patients ≥20 years old received TFNT20 IOL in at least 1 eye based on Alcon Toric calculator (Holladay Total surgically induced astigmatism). Effectiveness endpoints included the percentage of eyes with refractive cylinder ≤0.25 D at 30-60 days after surgery, which was compared with a historical control threshold rate of 29.2% for nontoric IOLs and refractive cylinder ≤0.50 D. Monocular uncorrected distance visual acuity (UDVA; 5 m), uncorrected intermediate visual acuity (UIVA; 60 cm), uncorrected near visual acuity (UNVA; 40 cm), and adverse events were evaluated. Of 41 eyes implanted with TFNT20 IOLs, 37 eyes (90%) achieved refractive cylinder ≤0.25 D at 30-60 days after surgery, demonstrating the superiority of TFNT20 compared with historical data ( <0.0001). Refractive cylinder of ≤0.50 D was achieved by 41 eyes (100%). At 30-60 days, mean ± SD monocular CDVA was -0.15 ± 0.07 logMAR, UDVA was -0.09 ± 0.09 logMAR, UIVA was -0.00 ± 0.07 logMAR, and UNVA was 0.03 ± 0.07 logMAR. Six eyes (15%) had elevated postoperative intraocular pressure, which returned to normal and was not device-related. TFNT20 IOLs successfully reduced postoperative refractive cylinder and provided good distance, intermediate, and near uncorrected VAs in Japanese patients with low corneal astigmatism.

The work in the technological sewing process is carried out on machine systems characterised by machine–hand work, where the worker and the machine work simultaneously. Such a work system requires a high level of responsibility in terms of quality, quantity, and the correct and timely execution of work, which requires workers to have fast and accurate reflexes, as well as exceptionally good psychomotor and visual skills. By applying the basic movements of the Methods-Time Measurement (MTM) system, the elaborated standard sets of hand sub-operations included in technological sewing operations, and the method of determining normal times for straight seams (RAV) and curved seams (ZAK), it is possible to determine the working method and time norm of individual technological sewing operations. The MTM Calculator software was developed to facilitate the determination of working methods and time norms on the basis of the MTM system. It can be used to quickly calculate the production time for a technological sewing operation.