Scientific reports
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Multicenter Study Historical Article
Improvement in fast-track hip and knee arthroplasty: a prospective multicentre study of 36,935 procedures from 2010 to 2017.
"Fast-track" protocols has improved surgical care with a reduction in length of hospital stay (LOS) in total hip (THA) and knee arthroplasty (TKA). However, the effects of continuous refinement of perioperative care lack detailed assessment. We studied time-related changes in LOS and morbidity after THA and TKA within a collaboration with continuous scientific refinement of perioperative care. ⋯ LOS declined from three [two to three] days in 2010 to one [one to two] day in 2017. LOS > 4 days due to "medical" or "surgical" complications, and "with no recorded morbidity" declined from 4.4 to 2.7%, 1.5 to 0.6%, and 3.8 to 1.3%, respectively. 90-days readmission rate declined from 8.6 to 7.7%. Our multicentre study in a socialized healthcare setting was associated with a continuous reduction in LOS and morbidity after THA and TKA.
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Although both pre- and postoperative myocardial injuries are strongly associated with an increased postoperative mortality, no study has directly compared the effects of pre- and postoperative myocardial injuries on 30-day mortality after non-cardiac surgery. Therefore, we evaluated and compared the effects of pre- and postoperative myocardial injury on 30-day mortality after non-cardiac surgery. From January 2010 to December 2016, patients undergoing non-cardiac surgery were stratified into either the normal (n = 3182), preoperative myocardial injury (n = 694), or postoperative myocardial injury (n = 756) groups according to the peak cardiac troponin value. ⋯ In patients undergoing non-cardiac surgery, preoperative myocardial injury also increased postoperative 30-day mortality to a similar degree of postoperative myocardial injury. Further studies on the importance of preoperative myocardial injury are needed. Clinical trial number and registry URL: KCT0004348 ( www.cris.nih.go.kr ).
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The current outbreak of coronavirus disease 2019 (COVID-19) has recently been declared as a pandemic and spread over 200 countries and territories. Forecasting the long-term trend of the COVID-19 epidemic can help health authorities determine the transmission characteristics of the virus and take appropriate prevention and control strategies beforehand. Previous studies that solely applied traditional epidemic models or machine learning models were subject to underfitting or overfitting problems. ⋯ The prediction results for five other countries suggested the external validity of our model. The integrated approach of epidemic and machine learning models could accurately forecast the long-term trend of the COVID-19 outbreak. The model parameters also provided insights into the analysis of COVID-19 transmission and the effectiveness of interventions in China.
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This study designed to evaluate the effect of nutraceutical supplementation on pain intensity and physical function in patients with knee/hip OA. The MEDLINE, Web of Science, Cochrane Library, Scopus, EMBASE, Google Scholar, Science direct, and ProQuest in addition to SID, Magiran, and Iranmedex were searched up to March 2020. Records (n = 465) were screened via the PICOS criteria: participants were patients with hip or knee OA; intervention was different nutritional supplements; comparator was any comparator; the outcome was pain intensity (Visual analogue scale [VAS]) and physical function (Western Ontario and McMaster Universities Arthritis [WOMAC] index); study type was randomized controlled trials. ⋯ Nutritional supplementation were found to improve total WOMAC index (SMD = - 0.23, 95% CI - 0.37 to - 0.08), WOMAC pain (SMD = - 0.36, 95% CI - 0.62 to - 0.10) and WOMAC stiffness (SMD = - 0.47, 95% CI - 0.71 to - 0.23) subscales and VAS (SMD = - 0.79, 95% CI - 1.05 to - 0.05). Results of subgroup analysis according to the supplementation duration showed that the pooled effect size in studies with < 10 months, 10-20 months and > 20 months supplementation duration were 0.05, 0.27, and 0.36, respectively for WOMAC total score, 0.14, 0.55 and 0.05, respectively for WOAMC pain subscale, 0.59, 0.47 and 0.41, respectively for WOMAC stiffness subscale, 0.05, 0.57 and 0.53, respectively for WOMAC physical function subscale and 0.65, 0.99 and 0.12, respectively for VAS pain. The result suggested that nutraceutical supplementation of patients with knee/hip OA may lead to an improvement in pain intensity and physical function.
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Early and accurate prediction of the need for intubation may provide more time for preparation and increase safety margins by avoiding high risk late intubation. This study evaluates whether machine learning can predict the need for intubation within 24 h using commonly available bedside and laboratory parameters taken at critical care admission. We extracted data from 2 large critical care databases (MIMIC-III and eICU-CRD). ⋯ Random forest model had sensitivity of 0.88 (95% CI 0.86-0.90) and specificity of 0.66 (95% CI 0.63-0.69), with good calibration throughout the range of intubation risks. The results showed that machine learning could predict the need for intubation in critically ill patients using commonly collected bedside clinical parameters and laboratory results. It may be used in real-time to help clinicians predict the need for intubation within 24 h of intensive care unit admission.