ABSTRACT Purpose: To evaluate the predictive value of initial intraocular pressure difference of the detached and fellow eyes of patients with complex rhegmatogenous retinal detachment on postoperative persistent ocular hypotony. Methods: This retrospective observational study included 538 eyes of 538 unilateral complex rhegmatogenous retinal detachment patients with a proliferative vitreoretinopathy grade of C-1 or higher, treated with silicone oil endotamponade following pars plana vitrectomy. The patients were divided into Group A (patients having silicone oil removal without ocular hypotony; n=504) and Group B (patients with persistent ocular hypotony following silicone oil removal [n=8, 23.5%] and with retained silicone oil [n=26, 76.5%] due to the risk of persistent ocular hypotony; total n=34). Ocular hypotony was defined as an intraocular pressure of <6 mmHg on two or more occasions. Patients’ demographics, including age, sex, and follow-up time, and ocular characteristics, including ocular surgical and trauma history, initial and final best-corrected visual acuity, intraocular pressure and initial intraocular pressure difference of the detached and fellow eyes, and anatomical success rates and postoperative complications, were retrospectively collected from the electronic patient files. Results: The initial intraocular pressure was significantly lower in the detached eyes of Group B than in Group A (8.3 ± 3.5 vs. 12.9 ± 3.3, p<0.001). Also, the initial intraocular pressure difference was significantly higher in Group B than in Group A (8.9 ± 3.2 vs. 2.2 ± 2.7mmHg, p<0.001). The receiver operating characteristic curve analysis showed that the cutoff value of the initial intraocular pressure difference was 7.5mmHg for the risk of persistent ocular hypotony. The most influential factors on postoperative persistent ocular hypotony in the binary logistic regression analysis were the initial intraocular pressure difference and the need for a retinectomy. Conclusion: In eyes with complex rhegmatogenous retinal detachment treated with pars plana vitrectomy and silicone oil tamponade, the initial intraocular pressure difference could be of value in predicting postoperative persistent ocular hypotony and could guide surgeons on the decision of silicone oil removal. Purpose Methods 53 C1 C 1 C- n=504 n504 n 504 n=8, n8 8 [n=8 23.5% 235 23 5 n=26, n26 26 [n=26 76.5% 765 76 n=34. n34 n=34 . 34 n=34) 6 < occasions Patients demographics age sex followup follow up time characteristics history bestcorrected best corrected acuity complications files Results 8.3 83 3 (8. 35 3. vs 129 12 9 12. 33 3.3 p<0.001. p0001 p p<0.001 0 001 p<0.001) Also 8.9 89 32 2 22 2. 27mmHg 7mmHg 2.7mmHg 75mmHg 7 5mmHg retinectomy Conclusion tamponade n=50 n50 50 n=8 [n= 23.5 n=26 n2 [n=2 76.5 n3 n=3 8. (8 p000 p<0.00 00 n=5 n5 n= [n 23. n=2 76. ( p00 p<0.0 p0 p<0. p<0 p<

The inhibition of the fatty acid amide hydrolase (FAAH), an endocannabinoid system component, emerged as a potentially new therapeutic target for a range of clinical disorders such as acute and chronic pain. Some α-ketoheterocycle derivatives demonstrated interesting analgesic and anti-inflammatory activities in vitro. Ligand-Based Drug Design techniques such as knowledge graph convolutional networks (kGCN) and hologram quantitative structure-activity relationship (HQSAR) using α-ketoheterocycle derivatives from five different datasets were generated to discover the relation between the chemical structures and the inhibition activity. Meanwhile, structure-based drug design simulations as interaction fields (MIF), molecular docking, and ligand sites studies (LSI) from FAAH were performed using Autogrid software and FTmap/FTsite servers. The results of both studies were merged to propose predictive models. The resulting kGCN model demonstrated adequate accuracy area under the curve by receiver operating characteristic (AUC-ROC 0.7922). From contribution maps of the Ligand-Based Drug Design (LBDD) models and the generated probes using MIF and LSI, it was observed that the oxazole ring, the ketone group, and the apolar chain present in the structures of the inhibitors are important, besides the evidence of the Cys269 and Val270 residues importance for the potential interaction, confirmed by carried docking studies. These fragments and structural information can be used to carry out new FAAH potential inhibitors studies and report kGCN as an accurate classification technique. FAAH, , (FAAH) component pain αketoheterocycle α ketoheterocycle antiinflammatory anti inflammatory vitro LigandBased Ligand Based (kGCN structureactivity structure activity HQSAR (HQSAR Meanwhile structurebased based MIF, (MIF) LSI (LSI FTmapFTsite FTmap FTsite servers AUCROC AUC ROC 0.7922. 07922 0.7922 . 0 7922 0.7922) LBDD (LBDD ring group important Cys Cys26 Val Val27 technique (FAAH (MIF 0792 0.792 792 Cys2 Val2 079 0.79 79 07 0.7 7 0.

ABSTRACT Objective: To evaluate the predictive validity and cut-off point of heart rate and blood pressure on heart rate variability (HRV) changes in children with and without obesity. Methods: This study included 125 children, of whom 41 were normal weight and 84 were obese. Anthropometry, blood pressure, heart rate, and HRV were measured using an electronic scale and stadiometer, a sphygmomanometer, and HRV monitor. In addition, the receiver operating characteristic (ROC) curve was obtained by statistical analysis of the data. Results: Heart rate proved to be a good predictor for changes in the square root of the mean of the square of the differences between consecutive NN intervals (RMSSD) parameter in students of both sexes for the normal-weight group (ROC 0.89; 95%CI 0.77–1.00) and obesity (ROC 0.90; 95%CI 0.83–0.97). In addition, the heart rate cut-off point for alterations in the RMSSD parameter for normal-weight boys was 93 bpm (sensitivity 100.00% and specificity 87.50%) and for boys with obesity, the established cut-off point was 91 bpm (sensitivity 94.74% and specificity 63.64%). Heart rate also proved to be a good predictor considering low-frequency/high-frequency ratio (LF/HF) and standard deviation of long-term continuous NN intervals /standard deviation of the instantaneous variability of continuous NN intervals in the Poincaré graph ratio (SD2/SD1). Systolic and diastolic blood pressures were good predictors in more specific stratifications and, therefore, can be used in some cases. Conclusions: The predictive validity of heart rate was shown to be at a good level, with high sensitivity and acceptable specificity for the cut-off points according to the different analyses stratified by gender and nutritional status. In this sense, health professionals will be able to use heart rate to estimate cardiovascular risk in children of different sexes and nutritional status. Objective cutoff cut off (HRV Methods 12 4 8 obese Anthropometry stadiometer sphygmomanometer monitor addition ROC data Results (RMSSD normalweight 0.89 089 0 89 95CI CI 95 0.77–1.00 077100 77 1 00 0.90 090 90 0.83–0.97. 083097 0.83–0.97 . 83 97 0.83–0.97) 9 10000 100 100.00 87.50% 8750 87 50 9474 94 74 94.74 63.64%. 6364 63.64% 63 64 63.64%) lowfrequency/highfrequency lowfrequencyhighfrequency low frequency/high frequency LF/HF LFHF LF HF (LF/HF longterm long term SD2/SD1. SD2SD1 SDSD SD2/SD1 SD2 SD1 SD (SD2/SD1) therefore cases Conclusions level status sense 0.8 08 0.77–1.0 07710 7 0.9 09 08309 0.83–0.9 1000 10 100.0 87.50 875 5 947 94.7 636 63.64 6 lowfrequency highfrequency frequencyhigh SD2SD SD2/SD (SD2/SD1 0. 0.77–1. 0771 0830 0.83–0. 100. 87.5 94. 63.6 (SD2/SD 0.77–1 077 083 0.83–0 87. 63. 0.77– 07 0.83– 0.77 0.83 0.7

RESUMO Objetivo: Avaliar a validade preditiva e o ponto de corte da frequência cardíaca e da pressão arterial nas alterações da variabilidade da frequência cardíaca (VFC) em crianças com e sem obesidade. Métodos: Foram incluídas 125 crianças neste estudo, sendo 41 com peso normal e 84 com obesidade. Antropometria, pressão arterial, frequência cardíaca e VFC foram medidas por meio de balança eletrônica e estadiômetro, esfigmomanômetro e monitor de VFC. Além disso, a curva característica de operação do receptor (ROC) foi obtida pela análise estatística dos dados. Resultados: A frequência cardíaca mostrou-se um bom preditor de alterações no parâmetro de raiz quadrada da média do quadrado das diferenças entre os intervalos NN consecutivos (RMSSD) em escolares de ambos os sexos para o grupo de peso normal (ROC 0,89; IC95% 0,77–1,00) e obesidade (ROC 0,90; IC95% 0,83–0,97). Além disso, o ponto de corte da frequência cardíaca para alterações no parâmetro RMSSD para meninos com peso normal foi de 93 bpm (sensibilidade 100,00% e especificidade 87,50%), e para meninos com obesidade, o ponto de corte estabelecido foi de 91 bpm (sensibilidade 94,74% e especificidade 63,64%). A frequência cardíaca também se mostrou um bom preditor considerando os índices da relação baixa frequência/alta frequência (LF/HF) e razão desvio padrão de intervalos NN contínuos de longo prazo/desvio padrão da variabilidade instantânea de intervalos NN contínuos na relação gráfica de Poincaré (SD2/SD1). As pressões arteriais sistólicas e diastólicas foram bons preditores em estratificações mais específicas e, portanto, podem ser utilizadas em alguns casos. Conclusões: A validade preditiva da frequência cardíaca mostrou-se em bom nível, com alta sensibilidade e especificidade aceitável para os pontos de corte, conforme as diferentes análises estratificadas por sexo e estado nutricional. Desta forma, os profissionais de saúde poderão utilizar a frequência cardíaca para estimar o risco cardiovascular em crianças de diferentes sexos e estado nutricional. Objetivo (VFC Métodos 12 estudo 4 8 Antropometria estadiômetro disso ROC dados Resultados mostrouse (RMSSD 0,89 089 0 89 IC95 IC 0,77–1,00 077100 77 1 00 0,90 090 90 0,83–0,97. 083097 0,83–0,97 . 83 97 0,83–0,97) 9 10000 100 100,00 87,50%, 8750 87,50% , 87 50 87,50%) 9474 94 74 94,74 63,64%. 6364 63,64% 63 64 63,64%) frequênciaalta LF/HF LFHF LF HF (LF/HF prazodesvio prazo SD2/SD1. SD2SD1 SDSD SD2/SD1 SD2 SD1 SD (SD2/SD1) portanto casos Conclusões nível nutricional forma 0,8 08 IC9 0,77–1,0 07710 7 0,9 09 08309 0,83–0,9 1000 10 100,0 875 87,50 5 947 94,7 636 63,64 6 SD2SD SD2/SD (SD2/SD1 0, 0,77–1, 0771 0830 0,83–0, 100, 87,5 94, 63,6 (SD2/SD 0,77–1 077 083 0,83–0 87, 63, 0,77– 07 0,83– 0,77 0,83 0,7

SUMMARY OBJECTIVE: The aim of this study was to demonstrate the effect of coronavirus disease 2019 on the cardiovascular autonomic system using heart rate variability in young individuals. METHODS: The study was designed retrospectively by scanning the 24-h Holter electrocardiography records of patients who applied to the Ankara Abdurrahman Yurtaslan Oncology Education and Research Hospital Cardiology outpatient clinic. The study group consisted of 492 patients under the age of 40 years, who did not have additional comorbidities or medication use and had prolonged symptoms after coronavirus disease 2019 during the pandemic. The control group, including 401 patients, was determined during the pre-pandemic period (before December 2019). Heart rate variability parameters were evaluated by scanning the 24-h Holter electrocardiography records of the patients and compared with the non-coronavirus disease 2019 group. RESULTS: The median age of participants was 30 years. Standard deviation of normal RR intervals (SDNN) ≤100 ms was more prevalent in the study group (27 (6.7%) vs 73 (14.8%), p<0.001). In univariate logistic regression analysis, the presence of coronavirus disease 2019 [(OR 2.41, 95%CI 1.52–3.83), p<0.001] and age [(OR 1.04, 95%CI 1.01–1.07), p=0.016] had a significant effect on the probability of SDNN≤100. In multivariate logistic regression analysis, the presence of coronavirus disease 2019 [(OR 2.42, 95%CI 1.52–3.85), p<0.001] and age [(OR 2.42, 95%CI 1.52–3.85), p=0.016] had a significant effect on the probability of SDNN≤100. Frequency domain measures such as, high-frequency values were significantly higher in the study group (p=0.029). The study group’s low-frequency/high frequency ratio was significantly lower (p=0.019). The low-frequency/high-frequency ratio’s cut-off value was ≤2.77. for determining the differentiation between coronavirus disease 2019 positive and negative cases in the receiver operating characteristic analysis. The sensitivity rate was 80.7%. The area under the curve value is 0.546 (p=0.019). CONCLUSION: This study showed that coronavirus disease 2019 causes reduced heart rate variability and increased parasympathetic activity in young patients. This may explain the prolonged symptoms after coronavirus disease 2019 infection. OBJECTIVE 201 individuals METHODS 24h h 24 clinic 49 4 years pandemic prepandemic pre before 2019. . 2019) noncoronavirus non RESULTS 3 SDNN (SDNN 100 ≤10 27 (2 6.7% 67 6 7 (6.7% 14.8%, 148 14.8% , 14 8 (14.8%) p<0.001. p0001 p p<0.001 0 001 p<0.001) analysis OR 241 2 41 2.41 95CI CI 95 1.52–3.83, 152383 1.52–3.83 1 52 83 1.52–3.83) 104 04 1.04 1.01–1.07, 101107 1.01–1.07 01 07 1.01–1.07) p=0.016 p0016 016 SDNN100 SDNN≤100 242 42 2.42 1.52–3.85, 152385 1.52–3.85 85 1.52–3.85) as highfrequency high p=0.029. p0029 p=0.029 029 (p=0.029) groups s lowfrequency/high lowfrequencyhigh low frequency/high p=0.019. p0019 p=0.019 019 (p=0.019) lowfrequency/highfrequency lowfrequencyhighfrequency ratios cutoff cut off 277 77 ≤2.77 807 80 80.7% 0546 546 0.54 CONCLUSION infection 20 10 ≤1 ( 6.7 (6.7 14.8 (14.8% p000 p<0.00 00 2.4 9 15238 1.52–3.8 5 1.0 10110 1.01–1.0 p=0.01 p001 SDNN10 SDNN≤10 p002 p=0.02 02 (p=0.029 lowfrequency frequencyhigh (p=0.019 ≤2.7 80.7 054 54 0.5 ≤ 6. (6. 14. (14.8 p00 p<0.0 2. 1523 1.52–3. 1. 1011 1.01–1. p=0.0 SDNN1 SDNN≤1 (p=0.02 (p=0.01 ≤2. 80. 05 0. (6 (14. p0 p<0. 152 1.52–3 101 1.01–1 p=0. SDNN≤ (p=0.0 ≤2 (14 p<0 15 1.52– 1.01– p=0 (p=0. (1 p< 1.52 1.01 p= (p=0 1.5 (p= (p

SUMMARY OBJECTIVE: The aim of this study was to investigate the role of systemic immune-inflammation index, neutrophil–lymphocyte ratio, lymphocyte–monocyte ratio, and platelet–lymphocyte ratios calculated in the first trimester as inflammatory markers in predicting gestational diabetes mellitus diagnosis. METHODS: This study was conducted retrospectively at a tertiary center between January 2020 and June 2023. A total of 111 pregnant women with gestational diabetes and 378 pregnant women in the control group were included in the study. Systemic immune-inflammation index, neutrophil–lymphocyte ratio, lymphocyte–monocyte ratio, and platelet–lymphocyte ratios values were compared between the gestational diabetes mellitus group patients and the healthy group. Receiver operating characteristic analysis curve was used for predicting gestational diabetes mellitus using systemic immune-inflammation index and lymphocyte–monocyte ratio. RESULTS: In pregnant women in the first trimester, systemic immune-inflammation index and lymphocyte–monocyte ratio values based on routine complete blood count parameters were found to be statistically significantly higher in gestational diabetes mellitus patients compared to healthy patients, while neutrophil–lymphocyte ratio and platelet–lymphocyte ratios values were found to be similar (p=0.033, p=0.005, p=0.211, and p=0.989). For predicting gestational diabetes mellitus, a cut-off value of 655.75 for systemic immune-inflammation index resulted in 80.2% sensitivity and 34.4% specificity, and a cut-off value of 3.62 for lymphocyte–monocyte ratio resulted in 56.8% sensitivity and 63.2% specificity, indicating good discriminatory ability. CONCLUSION: We believe that systemic immune-inflammation index and lymphocyte–monocyte ratio values measured in the first-trimester complete blood count parameters are effective in predicting gestational diabetes mellitus but are not effective in determining insulin requirement. OBJECTIVE immuneinflammation immune inflammation neutrophillymphocyte neutrophil lymphocyte lymphocytemonocyte monocyte plateletlymphocyte platelet diagnosis METHODS 202 2023 11 37 RESULTS p=0.033, p0033 p 0 033 (p=0.033 p0005 005 p=0.005 p0211 211 p=0.211 p=0.989. p0989 p=0.989 . 989 p=0.989) cutoff cut off 65575 655 75 655.7 802 80 2 80.2 344 34 4 34.4 specificity 362 3 62 3.6 568 56 8 56.8 632 63 63.2 ability CONCLUSION firsttrimester requirement 20 1 p=0.033 p003 03 (p=0.03 p000 00 p=0.00 p021 21 p=0.21 p098 p=0.98 98 6557 65 7 655. 80. 34. 36 6 3. 5 56. 63. p=0.03 p00 (p=0.0 p=0.0 p02 p=0.2 p09 p=0.9 9 p0 (p=0. p=0. (p=0 p=0 (p= p= (p

SUMMARY OBJECTIVE: The aim of our study was to determine the role of serum glucose–potassium ratio in predicting inhospital mortality in coronary care unit patients. METHODS: This study used data from the MORtality in CORonary Care Units in Turkey study, a national, observational, multicenter study that included all patients admitted to coronary care units between September 1, 2022, and September 30, 2022. Statistical analyses assessed the independent predictors of mortality. Two models were created. Model 1 included age, history of heart failure, chronic kidney disease, hypertension, diabetes mellitus, and coronary artery disease. Model 2 included glucose–potassium ratio in addition to these variables. Multivariate regression and receiver operating characteristic analysis were performed to compare Model 1 and Model 2 to identify if the glucose–potassium ratio is an independent predictor of inhospital mortality. RESULTS: In a study of 3,157 patients, the mortality rate was 4.3% (n=137). Age (p=0.002), female gender (p=0.004), mean blood pressure (p<0.001), serum creatinine (p<0.001), C-reactive protein (p=0.002), white blood cell (p=0.002), and glucose–potassium ratio (p<0.001) were identified as independent predictors of mortality through multivariate regression analysis. The receiver operating characteristic analysis indicated that Model 2 had a statistically higher area under the curve than Model 1 (area under the curve 0.842 vs area under the curve 0.835; p<0.001). A statistically significant correlation was found between the inhospital mortality and glucose–potassium ratio (OR 1.015, 95%CI 1.006–1.024, p<0.001). CONCLUSION: Our study showed that the glucose–potassium ratio may be a significant predictor of inhospital mortality in coronary care unit patients. OBJECTIVE glucosepotassium glucose potassium METHODS national observational 2022 30 created age failure disease hypertension mellitus variables RESULTS 3157 3 157 3,15 43 4 4.3 n=137. n137 n n=137 . 137 (n=137) p=0.002, p0002 p p=0.002 , 0 002 (p=0.002) p=0.004, p0004 p=0.004 004 (p=0.004) p<0.001, p0001 p<0.001 001 Creactive C reactive (p<0.001 0842 842 0.84 0.835 0835 835 p<0.001. p<0.001) OR 1015 015 1.015 95CI CI 95 10061024 006 024 1.006–1.024 CONCLUSION 202 315 15 3,1 4. n13 n=13 13 (n=137 p000 p=0.00 00 (p=0.002 (p=0.004 p<0.00 (p<0.00 084 84 0.8 0.83 083 83 101 01 1.01 9 1006102 02 1.006–1.02 20 31 3, n1 n=1 (n=13 p00 p=0.0 (p=0.00 p<0.0 (p<0.0 08 8 0. 10 1.0 100610 1.006–1.0 n= (n=1 p0 p=0. (p=0.0 p<0. (p<0. 1. 10061 1.006–1. (n= p=0 (p=0. p<0 (p<0 1006 1.006–1 (n p= (p=0 p< (p< 100 1.006– (p= (p 1.006 1.00

SUMMARY OBJECTIVE: The objective of this study was to investigate serum Metrnl levels in pregnant women with gestational diabetes mellitus and compare them with pregnant women without gestational diabetes mellitus. METHODS: The gestational diabetes mellitus group consisted of 87 pregnant women diagnosed with gestational diabetes mellitus, and the control group consisted of 93 healthy pregnant women without gestational diabetes mellitus. Serum Metrnl levels were determined by the enzyme-linked immunosorbent assay method. RESULTS: The two groups were similar in terms of demographic features. The median serum Metrnl level was found to be 1.16 ng/mL in the gestational diabetes mellitus group, while it was determined as 2.2 ng/mL in the control group (p=0.001). The two groups were divided into two subgroups based on participants’ body mass index, normal weight and overweight. The lowest median Metrnl level was detected in the normal weight gestational diabetes mellitus group, followed by the overweight gestational diabetes mellitus group, normal weight control group, and overweight control group (1.1, 1.2, 2, and 2.4 ng/mL, respectively). Receiver operating curve analysis was performed to determine the value of the serum Metrnl level in terms of predicting gestational diabetes mellitus. The area under the curve analysis of serum Metrnl for gestational diabetes mellitus estimation was 0.768 (p=0.000, 95%CI 0.698–0.839). The optimal cutoff value for serum Metrnl level was determined as 1.53 ng/mL with 69% sensitivity and 70% specificity. CONCLUSION: Serum Metrnl levels in pregnant women with gestational diabetes mellitus were found to be significantly lower than in pregnant women without gestational diabetes mellitus. The mechanisms underlying the decrease in serum Metrnl levels in gestational diabetes mellitus remain unclear for now, and future studies will reveal the role of Metrnl in the pathophysiology of gestational diabetes mellitus. OBJECTIVE METHODS 8 9 enzymelinked enzyme linked method RESULTS features 116 1 16 1.1 ngmL ng mL 22 2 2. p=0.001. p0001 p p=0.001 . 0 001 (p=0.001) participants index 1.1, 11 (1.1 12 1.2 24 4 respectively. respectively respectively) 0768 768 0.76 p=0.000, p0000 000 (p=0.000 95CI CI 95 0.698–0.839. 06980839 0.698–0.839 698 839 0.698–0.839) 153 53 1.5 69 70 specificity CONCLUSION now 1. p000 p=0.00 00 (p=0.001 (1. 076 76 0.7 p=0.000 (p=0.00 0698083 0.698–0.83 83 15 5 6 7 p00 p=0.0 (1 07 0. (p=0.0 069808 0.698–0.8 p0 p=0. ( (p=0. 06980 0.698–0. p=0 (p=0 0698 0.698–0 p= (p= 069 0.698– (p 06 0.698 0.69 0.6

Abstract Objective Platelet to albumin ratio (PAR) and prognostic nutritional index (PNI) are potential indicators for evaluating nutritional and inflammatory status. This study aimed to examine the relationship between PAR and PNI and the acute complicated course of acute hematogenous osteomyelitis (AHO). Methods AHO patients were divided into the simple course group and the acute complicated course group. The patient's gender, age, site of infection, body temperature, laboratory results, and pathogen culture results were collected and compared. Multivariate logistic regression analysis was used to determine the independent risk factors of the acute complicated course group. The receiver operating characteristic curve was applied to determine the optimal cut-off value. Results In total, 101 AHO patients with a median age of 7.58 years were included. There were 63 cases (62.4 %) in the simple course group and 38 cases (37.6 %) in the complicated course group. Binary logistic regression analysis revealed that PAR and PNI were independent risk factors for predicting the acute complicated course of AHO (p = 0.004 and p < 0.001, respectively). Receiver operating characteristic curve analysis demonstrated that the combination of PAR and PNI had an area under the curve of 0.777 (95 % CI: 0.680-0.873, p < 0.001) with a cut-off value of 0.51. Conclusions The incidence of acute complicated courses was significantly higher in patients with high PAR and low PNI. A combined factor greater than 0.51, derived from PAR and PNI measurements within 24 h of admission, may be useful for predicting AHO patients who are likely to develop severe disease. (PAR (PNI status AHO. . (AHO) patient s gender infection temperature compared cutoff cut off total 10 758 7 58 7.5 included 6 62.4 624 62 4 (62. 3 37.6 376 37 (37. 0004 0 004 0.00 0001 001 0.001 respectively. respectively respectively) 0777 777 0.77 95 (9 CI 0.6800.873, 06800873 0.680 0.873, 680 873 0.680-0.873 051 51 0.51 2 admission disease (AHO 1 75 5 7. 62. (62 37. (37 000 00 0.0 077 77 0.7 9 ( 6800 0.6800.873 0680087 0680 0.68 0873 0.873 68 87 0.680-0.87 05 0.5 (6 (3 0. 07 0.6800.87 068008 068 0.6 087 0.87 8 0.680-0.8 0.6800.8 06800 06 08 0.8 0.680-0. 0.6800. 0.680-0 0.6800 0.680-

Resumen La carretera Puyo-Tena es propensa a deslizamientos de tierra debido a la geodinámica, geomorfología y materiales geológicos de la zona (afloramientos y estratos inestables). En los últimos años, este problema ha provocado de forma persistente la inutilización parcial o total de la carretera en numerosas ocasiones. El objetivo de la investigación fue generar un modelo cartográfico de susceptibilidad a deslizamientos a partir de variables como la pendiente, las formaciones geológicas, la cobertura y uso de la tierra, así como las distancias a fallas, carretera y ríos. El grado de incidencia de deslizamientos se estimó como la combinación lineal de las variables ponderadas mediante el proceso de jerarquía analítica. La importancia de este método semicuantitativo radica en su capacidad para desagregar un problema de decisión complejo en un modelo de decisión más simple y coherente. El modelo cartográfico resultante se reclasificó en cinco categorías de susceptibilidad: muy baja, baja, moderada, alta y muy alta. Los resultados mostraron que 17 km de los 80 km de la carretera Puyo-Tena tienen una alta probabilidad a deslizamientos, lo que equivale a 21,25% de la carretera. Además, dentro de este porcentaje, se determinó que existen quince regiones con alta probabilidad de deslizamientos debido a su ubicación en zonas con fuertes pendientes, litología porosa y permeable, gran cantidad de ríos y suelos agrícolas. Para la verificación del modelo se utilizó el área bajo la curva (en inglés AUC) de la característica operativa del receptor (en inglés ROC). Los resultados de la verificación mostraron que el modelo cartográfico para el área de estudio tiene un valor de precisión de 83,7%. El modelo cartográfico de susceptibilidad a deslizamientos permitirá tomar las decisiones pertinentes para mitigar eventos potenciales que puedan poner en peligro a transportistas, bienes materiales y residentes de la zona.

Abstract The Puyo-Tena roadway is prone to landslides due to the geodynamics, geomorphology, and geological materials of the area (unstable outcrops and strata). In recent years, this problem has persistently caused the road to be partially or completely disabled on numerous occasions. The objective of the research was to generate a cartographic model of landslides susceptibility based on variables such as slope, geological formations, land cover and land use, as well as distances to faults, road, and rivers. The degree of landslides incidence was estimated as the linear combination of the weighted variables using the analytic hierarchy process. The importance of this semi-quantitative method lies in its ability to break down a complex decision problem into a simpler and more coherent decision model. The resulting cartographic model was classified into five susceptibility categories: very low, low, moderate, high, and very high. The results showed that 17 km out of the 80 km of the Puyo-Tena roadway have a high probability of landslides, which is equivalent to 21.25% of the road. Furthermore, within this percentage, it was determined that there are fifteen regions with a high probability of landslides due to their location in areas with steep slopes, porous and permeable lithology, a large number of rivers, and agricultural soils. The area under the curve (AUC) of the receiver operating characteristic (ROC) was used for model verification. The verification results showed that the cartographic model for the study area has an accuracy value of 83.7%. The cartographic model of landslide susceptibility will enable relevant decisions to be made to mitigate potential hazards that may endanger transporters, material goods, and residents of the area.

Abstract Background Heart rate (HR) has shown prognostic value in patients with heart failure with reduced ejection fraction (HFrEF) and sinus rhythm. However, the method of measurement is debated in the literature. Objectives To compare HR on Holter with 3 resting electrocardiograms (ECG1, ECG2, and ECG3) in patients with HFrEF and sinus rhythm. Methods This was a cross-sectional study with 135 patients with heart failure with ejection fraction ≤ 40% and sinus rhythm. HR was assessed by ECG and Holter. Analyses included intraclass correlation coefficient (ICC), robust regression, root mean squared error, Bland-Altman, and area under the receiver operating characteristic (ROC) curve. A significance level of 0.05 and Bonferroni-Holm adjustment were adopted to minimize type I errors. Results The median [interquartile range] age and ejection fraction were 65 years [16] and 30% [11], respectively. The ICC of the 3 ECGs was 0.922 (95% confidence interval: 0.892; 0.942). The robust regression coefficients for ECG1 and ECG3 were 0.20 (95% confidence interval: 0.12; 0.29) and 0.21 (95% confidence interval: 0.06; 0.36). The robust R2 was 0.711 (95% confidence interval: 0.628; 0.76). In the Bland-Altman agreement analysis, the limits of agreement were −17.0 (95% confidence interval: −19.0; −15.0) and 32.0 (95% confidence interval: 30.0; 34.0). The area under the ROC curve was 0.896 (95% confidence interval: 0.865; 0.923). Conclusion The HR on ECG showed high agreement with the HR on Holter, validating its clinical use in patients with HFrEF and sinus rhythm. However, agreement was suboptimal in one third of patients with HR below 70 bpm on ECG; thus, 24-hour Holter monitoring should be considered in this context. (HR (HFrEF rhythm However literature ECG1, (ECG1 ECG2 crosssectional cross sectional 13 40 ICC, , (ICC) error BlandAltman, BlandAltman Bland Altman, Altman (ROC 005 0 05 0.0 BonferroniHolm Bonferroni Holm errors interquartile range 6 16 [16 30 11, 11 [11] respectively 0922 922 0.92 95% 95 (95 interval 0.892 0892 892 0.942. 0942 0.942 . 942 0.942) 020 20 0.2 0.12 012 12 0.29 029 29 021 21 0.06 006 06 0.36. 036 0.36 36 0.36) R 0711 711 0.71 0.628 0628 628 0.76. 076 0.76 76 0.76) analysis 170 17 −17. −19.0 190 19 −15.0 150 15 320 32 32. 30.0 300 34.0. 340 34.0 34 34.0) 0896 896 0.89 0.865 0865 865 0.923. 0923 0.923 923 0.923) 7 thus 24hour hour 24 context (ECG 1 4 (ICC 00 0. [1 [11 092 92 0.9 9 (9 089 89 094 0.94 94 02 2 0.1 01 03 0.3 071 71 0.7 0.62 062 62 07 −17 −19. −15. 30. 34. 0.8 0.86 086 86 [ 09 ( 08 8 0.6 −1 −19 −15 −

Resumo Fundamento A frequência cardíaca (FC) na insuficiência cardíaca com fração de ejeção reduzida (ICFEr) e ritmo sinusal apresenta valor prognóstico. Entretanto, o método de mensuração é debatido na literatura. Objetivos Comparar em pacientes com ICFEr e ritmo sinusal a FC no Holter com três eletrocardiogramas de repouso: ECG1, ECG2 e ECG3. Metodologia Estudo transversal com 135 pacientes portadores de insuficiência cardíaca com fração de ejeção ≤ 40% e ritmo sinusal. A FC foi avaliada por ECG e Holter. Análises incluíram o coeficiente de correlação intraclasse (CCI), regressão robusta, raiz do erro quadrático médio, Bland-Altman e a área sobre a curva ROC. Adotou-se nível de significância de 0,05 e o ajuste de Bonferroni-Holm para minimizar erros tipo I. Resultados As medianas [intervalo interquartil] de idade e fração de ejeção foram de 65 anos [16] e 30% [11], respectivamente. O CCI dos 3 ECG foi de 0,922 (intervalo de confiança de 95%: 0,892; 0,942). Os coeficientes de regressão robusta para ECG1 e ECG3 foram 0,20 (intervalo de confiança de 95%: 0,12; 0,29) e 0,21 (intervalo de confiança de 95%: 0,06; 0,36). O R2 robusto foi de 0,711 (intervalo de confiança de 95%: 0,628; 0,76). Na análise de concordância de Bland-Altman, os limites de concordância foram de −17,0 (intervalo de confiança de 95%: −19,0; −15,0) e 32,0 (intervalo de confiança de 95%: 30,0; 34,0). A área sob a curva ROC foi de 0,896 (intervalo de confiança de 95%: 0,865; 0,923). Conclusão A FC do ECG mostrou alta concordância com a FC do Holter, validando seu uso clínico em pacientes com ICFEr e ritmo sinusal. Contudo, a concordância foi subótima em um terço dos pacientes com FC inferior a 70 bpm pelo ECG, devendo ser considerada a realização de Holter neste contexto. (FC (ICFEr prognóstico Entretanto literatura repouso 13 40 CCI, , (CCI) médio BlandAltman Bland Altman Adotouse Adotou se 005 0 05 0,0 BonferroniHolm Bonferroni Holm I intervalo interquartil 6 16 [16 30 11, 11 [11] respectivamente 0922 922 0,92 95% 95 0,892 0892 892 0,942. 0942 0,942 . 942 0,942) 020 20 0,2 0,12 012 12 0,29 029 29 021 21 0,06 006 06 0,36. 036 0,36 36 0,36) R 0711 711 0,71 0,628 0628 628 0,76. 076 0,76 76 0,76) BlandAltman, Altman, 170 17 −17, −19,0 190 19 −15,0 150 15 320 32 32, 30,0 300 34,0. 340 34,0 34 34,0) 0896 896 0,89 0,865 0865 865 0,923. 0923 0,923 923 0,923) Contudo 7 contexto 1 4 (CCI 00 0, [1 [11 092 92 0,9 9 089 89 094 0,94 94 02 2 0,1 01 03 0,3 071 71 0,7 0,62 062 62 07 −17 −19, −15, 30, 34, 0,8 0,86 086 86 [ 09 08 8 0,6 −1 −19 −15 −

ABSTRACT Purpose The clinical outcomes of kidney transplantation from deceased donors have seen significant improvements with the use of machine perfusion (MP), now a standard practice in transplant centers. However, the use of perfusate biomarkers for assessing organ quality remains a subject of debate. Despite this, some centers incorporate them into their decision-making process for donor kidney acceptance. Recent studies have indicated that lactate dehydrogenase (LDH), glutathione S-transferase, interleukin-18, and neutrophil gelatinase-associated lipocalin (NGAL) could predict post-transplant outcomes. Materials and Methods Between August 2016 and June 2017, 31 deceased-donor after brain death were included and stroke was the main cause of death. Pediatric patients, hypersensitized recipients were excluded. 43 kidneys were subjected to machine perfusion. Perfusate samples were collected just before the transplantation and stored at -80ºC. Kidney transplant recipients have an average age of 52 years, 34,9% female, with a BMI 24,6±3,7. We employed receiver operating characteristic analysis to investigate associations between these perfusate biomarkers and two key clinical outcomes: delayed graft function and primary non-function. Results The incidence of delayed graft function was 23.3% and primary non-function was 14%. A strong association was found between NGAL concentration and DGF (AUC=0.766, 95% CI, P=0.012), and between LDH concentration and PNF (AUC=0.84, 95% CI, P=0.027). Other perfusate biomarkers did not show significant correlations with these clinical outcomes. Conclusion The concentrations of NGAL and LDH during machine perfusion could assist transplant physicians in improving the allocation of donated organs and making challenging decisions regarding organ discarding. Further, larger-scale studies are required. MP, MP , (MP) However debate this decisionmaking decision acceptance LDH, (LDH) Stransferase, Stransferase S transferase, transferase S-transferase interleukin18, interleukin18 interleukin 18, 18 interleukin-18 gelatinaseassociated gelatinase associated (NGAL posttransplant post 201 2017 3 deceaseddonor patients excluded 4 80ºC. 80ºC ºC -80ºC 5 years 349 34 9 34,9 female 24637 24 6 7 24,6±3,7 nonfunction. nonfunction non function. 233 23 23.3 14 14% AUC=0.766, AUC0766 AUC 0 766 (AUC=0.766 95 CI P=0.012, P0012 P P=0.012 012 P=0.012) AUC=0.84, AUC084 84 (AUC=0.84 P=0.027. P0027 P=0.027 . 027 P=0.027) discarding Further largerscale larger scale required (MP (LDH interleukin1 1 interleukin-1 20 34, 2463 2 24,6±3, 23. AUC=0.766 AUC076 76 (AUC=0.76 P001 P=0.01 01 AUC=0.84 AUC08 8 (AUC=0.8 P002 P=0.02 02 interleukin- 246 24,6±3 AUC=0.76 AUC07 (AUC=0.7 P00 P=0.0 AUC=0.8 AUC0 (AUC=0. 24,6± AUC=0.7 P0 P=0. AUC=0. (AUC=0 24,6 P=0 AUC=0 (AUC= 24, P= AUC= (AUC

Abstract Objective: Ovarian torsion (OT) represents a severe gynecological emergency in female pediatric patients, necessitating immediate surgical intervention to prevent ovarian ischemia and preserve fertility. Prompt diagnosis is, therefore, paramount. This retrospective study set out to assess the utility of combined clinical, ultrasound, and laboratory features in diagnosing OT. Methods: The authors included 326 female pediatric patients aged under 14 years who underwent surgical confirmation of OT over a five-year period. Logistic regression analysis was employed to pinpoint factors linked with OT, and the authors compared clinical presentation, laboratory results, and ultrasound characteristics between patients with OT (OT group) and without OT (N-OT group). The authors conducted receiver operating characteristic (ROC) curve analysis to gauge the predictive capacity of the combined features. Results: Among 326, OTwas confirmed in 24.23 % (79 cases) of the patients. The OT group had a higher incidence of prenatal ovarian masses than the N-OT (22 cases versus 7 cases) (p < 0.0001). Similarly, the authors observed significant differences in the presence of lower abdominal pain, suspected torsion on transabdominal ultrasound, and a high neutrophil-lymphocyte ratio (NLR > 3) between the OTand non-OT groups (p < 0.05). Furthermore, when these parameters were combined, the resulting area under the curve (AUC) was 0.868, demonstrating their potential utility in OT diagnosis. Conclusion: This study demonstrates a prediction model integrating clinical, laboratory, and ultrasound findings that can support the preoperative diagnosis of ovarian torsion, thereby enhancing diagnostic precision and improving patient management. Future prospective studies should concentrate on developing clinical predictive models for OTin pediatric patients. Objective fertility is therefore paramount Methods 32 1 fiveyear five year period presentation results NOT N group. . ROC (ROC Results 2423 24 23 24.2 79 (7 22 (2 p 0.0001. 00001 0.0001 0 0001 0.0001) Similarly pain neutrophillymphocyte neutrophil lymphocyte NLR 3 nonOT non 0.05. 005 0.05 05 0.05) Furthermore AUC (AUC 0868 868 0.868 Conclusion management 242 2 24. ( 0000 0.000 000 00 0.0 086 86 0.86 0.00 0. 08 8 0.8

The past decade has seen a renewed possibility of using machine learning algorithms to solve a large collection of problems in several fields. Data acquisition for mining operations has increased with the growth in sensor-based technologies, and therefore the amount of information available for mining applications has dramatically increased. Ore sorting equipment is available for separating ore from waste based on differences in physical properties detected by a real-time analyser. The separation efficiency depends on the contrast in these properties. In this study we investigate the application of machine learning models trained using data from the output of a dual-energy X-ray ore sorting apparatus at a gold mine. The particles were first hand-sorted into ore and gangue classes based on their mineralogical composition. Classification models were then used to help decide the balance between the number of true and false positives for ore in the concentrate, with a view to economic parameters, using their receiver operator characteristic (ROC) curves. The results showed AUC (area under the ROC curve) scores of up to 0.85 for the classification models and a maximum reward condition Fp r/Tp r around 0.5/0.9 for a simplified economic model.

ABSTRACT Purpose: To create a nomogram to predict the absence of clinically significant prostate cancer (CSPCa) in males with non-suspicion multiparametric magnetic resonance imaging (mpMRI) undergoing prostate biopsy (PBx). Materials and Methods: We identified consecutive patients who underwent 3T mpMRI followed by PBx for suspicion of PCa or surveillance follow-up. All patients had Prostate Imaging Reporting and Data System score 1-2 (negative mpMRI). CSPCa was defined as Grade Group ≥2. Multivariate logistic regression analysis was performed via backward elimination. Discrimination was evaluated with area under the receiver operating characteristic (AUROC). Internal validation with 1,000x bootstrapping for estimating the optimism corrected AUROC. Results: Total 327 patients met inclusion criteria. The median (IQR) age and PSA density (PSAD) were 64 years (58-70) and 0.10 ng/mL2 (0.07-0.15), respectively. Biopsy history was as follows: 117 (36%) males were PBx-naive, 130 (40%) had previous negative PBx and 80 (24%) had previous positive PBx. The majority were White (65%); 6% of males self-reported Black. Overall, 44 (13%) patients were diagnosed with CSPCa on PBx. Black race, history of previous negative PBx and PSAD ≥0.15ng/mL2 were independent predictors for CSPCa on PBx and were included in the nomogram. The AUROC of the nomogram was 0.78 and the optimism corrected AUROC was 0.75. Conclusions: Our nomogram facilitates evaluating individual probability of CSPCa on PBx in males with PIRADS 1-2 mpMRI and may be used to identify those in whom PBx may be safely avoided. Black males have increased risk of CSPCa on PBx, even in the setting of PIRADS 1-2 mpMRI Purpose (CSPCa nonsuspicion non (mpMRI . (PBx) Methods T followup. followup follow up. up follow-up 12 1 2 1- mpMRI. mpMRI) ≥2 elimination (AUROC) 1000x x 000x Results 32 criteria IQR (IQR (PSAD 6 5870 58 70 (58-70 010 0 10 0.1 ngmL2 ngmL ng mL2 mL ng/mL 0.070.15, 007015 0.07 0.15 , 07 15 (0.07-0.15) respectively follows 11 36% 36 (36% PBxnaive, PBxnaive naive, naive PBx-naive 13 40% 40 (40% 8 24% 24 (24% 65% 65 (65%) selfreported self reported Overall 4 13% (13% race 015ngmL2 15ng ≥0.15ng/mL 078 78 0.7 075 75 0.75 Conclusions avoided (PBx ≥ (AUROC 3 587 5 7 (58-7 01 0. 070 0.070.15 00701 007 0.0 015 (0.07-0.15 (36 (40 (24 (65% (13 015ngmL (58- 0.070.1 0070 00 (0.07-0.1 (3 (4 (2 (65 (1 (58 0.070. (0.07-0. ( (6 (5 0.070 (0.07-0 (0.07- (0.07 (0.0 (0. (0

Abstract Objective: Reliably prediction models for coronary artery abnormalities (CAA) in children aged > 5 years with Kawasaki disease (KD) are still lacking. This study aimed to develop a nomogram model for predicting CAA at 4 to 8 weeks of illness in children with KD older than 5 years. Methods: A total of 644 eligible children were randomly assigned to a training cohort (n = 450) and a validation cohort (n = 194). The least absolute shrinkage and selection operator (LASSO) analysis was used for optimal predictors selection, and multivariate logistic regression was used to develop a nomogram model based on the selected predictors. Area under the receiver operating characteristic curve (AUC), calibration curves, Hosmer-Lemeshow test, Brier score, and decision curve analysis (DCA) were used to assess model performance. Results: Neutrophil to lymphocyte ratio, intravenous immunoglobulin resistance, and maximum baseline z-score ≥ 2.5 were identified by LASSO as significant predictors. The model incorporating these variables showed good discrimination and calibration capacities in both training and validation cohorts. The AUC of the training cohort and validation cohort were 0.854 and 0.850, respectively. The DCA confirmed the clinical usefulness of the nomogram model. Conclusions: A novel nomogram model was established to accurately assess the risk of CAA at 4–8 weeks of onset among KD children older than 5 years, which may aid clinical decisionmaking. Objective (CAA (KD lacking Methods 64 n 450 194. 194 . 194) (LASSO AUC, , (AUC) curves HosmerLemeshow Hosmer Lemeshow test score (DCA performance Results ratio resistance zscore z 25 2 2. cohorts 0854 0 854 0.85 0850 850 0.850 respectively Conclusions 48 4– decisionmaking 6 45 19 (AUC 085 85 0.8 1 08 0.