13 research outputs found

    Türkiye'de koroner yoğun bakım ünitelerindeki hastane içi mortalite (MORCOR-TURK) çalışmasında hasta temel karakteristikleri ve öngördürücüleri

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    OBJECTIVE: The MORtality in CORonary Care Units in Türkiye (MORCOR-TURK) trial is a national registry evaluating predictors and rates of in-hospital mortality in coronary care unit (CCU) patients in Türkiye. This report describes the baseline demographic characteristics of patients recruited for the MORCOR-TURK trial. METHODS: The study is a multicenter, cross-sectional, prospective national registry that included 50 centers capable of 24-hour CCU service, selected from all seven geographic regions of Türkiye. All consecutive patients admitted to CCUs with cardiovascular emergencies between September 1-30, 2022, were prospectively enrolled. Baseline demographic characteristics, admission diagnoses, laboratory data, and cardiovascular risk factors were recorded. RESULTS: A total of 3,157 patients with a mean age of 65 years (range: 56-73) and 2,087 (66.1%) males were included in the analysis. Patients with arterial hypertension [1,864 patients (59%)], diabetes mellitus (DM) [1,184 (37.5%)], hyperlipidemia [1,120 (35.5%)], and smoking [1,093 (34.6%)] were noted. Non-ST elevation myocardial infarction (NSTEMI) was the leading cause of admission [1,187 patients (37.6%)], followed by ST elevation myocardial infarction (STEMI) in 742 patients (23.5%). Other frequent diagnoses included decompensated heart failure (HF) [339 patients (10.7%)] and arrhythmia [272 patients (8.6%)], respectively. Atrial fibrillation (AF) was the most common pathological rhythm [442 patients (14%)], and chest pain was the most common primary complaint [2,173 patients (68.8%)]. CONCLUSION: The most common admission diagnosis was acute coronary syndrome (ACS), particularly NSTEMI. Hypertension and DM were found to be the two leading risk factors, and AF was the most commonly seen pathological rhythm in all hospitalized patients. These findings may be useful in understanding the characteristics of patients admitted to CCUs and thus in taking precautions to decrease CCU admissions

    Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

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    Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

    Forecasting long-term world annual natural gas production by machine learning

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    The goal of this study is to model the global annual natural gas production using a variety of machine learning models in order to predict future production and determine a peak production date. World gross domestic product (GDP) based on purchasing power parities (at PPPs), inflation percentage, Henry Hub Price, Eum Price, cumulative natural gas resources, and annually discovered new resources were taken as descriptor variables, and Shapley analysis was conducted to observe the importance of features on the dataset. It was revealed according to this analysis that, Henry Hub price, inflation percentage, and newly discovered resources had minor effects on natural gas production, so they were left out. Then, a variety of machine learning algorithms were employed and the one with the highest prediction ability was found to be the stochastic gradient descent (SGD) algorithm. Next, this model was tested under four different scenarios, each with different GDP and natural gas price projections. Finally, natural gas production was found to reach its peak sometime between 2034 and 2046. It was then concluded that rather than relying on a traditional approach based on the Hubbert Curve, a machine learning model that takes into account all relevant factors can be used to accurately forecast natural gas production and its peak time, allowing governments and policymakers to make the necessary preparations.Istanbul Bilgi University [AK 85 073]The financial support provided by Istanbul Bilgi University Research Fund Project AK 85 073 is gratefully acknowledged

    Efficacy of subsequent treatments in patients with hormone-positive advanced breast cancer who had disease progression under CDK 4/6 inhibitor therapy

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    Abstract Background There is no standard treatment recommended at category 1 level in international guidelines for subsequent therapy after cyclin-dependent kinase 4/6 inhibitor (CDK4/6) based therapy. We aimed to evaluate which subsequent treatment oncologists prefer in patients with disease progression under CDKi. In addition, we aimed to show the effectiveness of systemic treatments after CDKi and whether there is a survival difference between hormonal treatments (monotherapy vs. mTOR-based). Methods A total of 609 patients from 53 centers were included in the study. Progression-free-survivals (PFS) of subsequent treatments (chemotherapy (CT, n:434) or endocrine therapy (ET, n:175)) after CDKi were calculated. Patients were evaluated in three groups as those who received CDKi in first-line (group A, n:202), second-line (group B, n: 153) and ≥ 3rd-line (group C, n: 254). PFS was compared according to the use of ET and CT. In addition, ET was compared as monotherapy versus everolimus-based combination therapy. Results The median duration of CDKi in the ET arms of Group A, B, and C was 17.0, 11.0, and 8.5 months in respectively; it was 9.0, 7.0, and 5.0 months in the CT arm. Median PFS after CDKi was 9.5 (5.0–14.0) months in the ET arm of group A, and 5.3 (3.9–6.8) months in the CT arm (p = 0.073). It was 6.7 (5.8–7.7) months in the ET arm of group B, and 5.7 (4.6–6.7) months in the CT arm (p = 0.311). It was 5.3 (2.5–8.0) months in the ET arm of group C and 4.0 (3.5–4.6) months in the CT arm (p = 0.434). Patients who received ET after CDKi were compared as those who received everolimus-based combination therapy versus those who received monotherapy ET: the median PFS in group A, B, and C was 11.0 vs. 5.9 (p = 0.047), 6.7 vs. 5.0 (p = 0.164), 6.7 vs. 3.9 (p = 0.763) months. Conclusion Physicians preferred CT rather than ET in patients with early progression under CDKi. It has been shown that subsequent ET after CDKi can be as effective as CT. It was also observed that better PFS could be achieved with the subsequent everolimus-based treatments after first-line CDKi compared to monotherapy ET. </jats:sec

    Efficacy of subsequent treatments in patients with hormone-positive advanced breast cancer who had disease progression under CDK 4/6 inhibitor therapy.

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    Background There is no standard treatment recommended at category 1 level in international guidelines for subsequent therapy after cyclin-dependent kinase 4/6 inhibitor (CDK4/6) based therapy. We aimed to evaluate which subsequent treatment oncologists prefer in patients with disease progression under CDKi. In addition, we aimed to show the effectiveness of systemic treatments after CDKi and whether there is a survival difference between hormonal treatments (monotherapy vs. mTOR-based). Methods A total of 609 patients from 53 centers were included in the study. Progression-free-survivals (PFS) of subsequent treatments (chemotherapy (CT, n:434) or endocrine therapy (ET, n:175)) after CDKi were calculated. Patients were evaluated in three groups as those who received CDKi in first-line (group A, n:202), second-line (group B, n: 153) and >= 3rd-line (group C, n: 254). PFS was compared according to the use of ET and CT. In addition, ET was compared as monotherapy versus everolimus-based combination therapy. Results The median duration of CDKi in the ET arms of Group A, B, and C was 17.0, 11.0, and 8.5 months in respectively; it was 9.0, 7.0, and 5.0 months in the CT arm. Median PFS after CDKi was 9.5 (5.0-14.0) months in the ET arm of group A, and 5.3 (3.9-6.8) months in the CT arm (p = 0.073). It was 6.7 (5.8-7.7) months in the ET arm of group B, and 5.7 (4.6-6.7) months in the CT arm (p = 0.311). It was 5.3 (2.5-8.0) months in the ET arm of group C and 4.0 (3.5-4.6) months in the CT arm (p = 0.434). Patients who received ET after CDKi were compared as those who received everolimus-based combination therapy versus those who received monotherapy ET: the median PFS in group A, B, and C was 11.0 vs. 5.9 (p = 0.047), 6.7 vs. 5.0 (p = 0.164), 6.7 vs. 3.9 (p = 0.763) months. Conclusion Physicians preferred CT rather than ET in patients with early progression under CDKi. It has been shown that subsequent ET after CDKi can be as effective as CT. It was also observed that better PFS could be achieved with the subsequent everolimus-based treatments after first-line CDKi compared to monotherapy ET
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