Descripción de las características sociodemográficas y clínicas de pacientes con litiasis renal

Contexto: los cálculos renales son cúmulos o depósitos de minerales que se forman en los cálices, la pelvis renal o el tracto urinario. Objetivo: describir las características sociodemográficas y clínicas de una muestra de pacientes con litiasis renal, mayores de 18 años. Metodología: estudio observacional descriptivo de pacientes atendidos en una consulta ambulatoria de Nefrología en Manizales en el periodo 2010-2020, donde se contaba con estudios en sangre, orina de 24 horas y estudio fisicoquímico del cálculo, además de datos sociodemográficos y clínicos relacionados. Se fragmentaron en grupos, de acuerdo con los hallazgos encontrados en los cálculos disponibles, dividiéndose en oxalato de calcio en su totalidad, calcio mixto con otro compuesto y el último grupo de cálculo no calcio. Resultados: se identificaron 54 pacientes con nefrolitiasis, de los cuales 14 de ellos fueron excluidos. Finalmente, 40 pacientes cumplieron con los criterios de inclusión. La mediana de edad fue 52,5 años, predominio del sexo masculino (55 %), donde se encontró en 20,5 % hiperuricemia, hipercalcemia en 17,6 %, hiperfosfatemia en 5 % e hipercaliemia en 7,5 %. En orina se encontró: hipocitraturia en el 71,1 %, seguido de hipercalciuria (12,5 %), hiperuricosuria (10 %) e hiperoxaluria (5 %). En 17 de los pacientes (42,5 %) se logró el estudio de la composición fisicoquímica del cálculo, en ellos la variedad de calcio mixto fue la más frecuente (55,5 %). Conclusiones: este estudio describe las características de pacientes con cálculos renales, mostrando que la mayoría tiene alteraciones metabólicas asociadas a nefrolitiasis, siendo la hipocitraturia el hallazgo más frecuente y que la mayoría de los cálculos tiene calcio en su composición.

Background: Kidney stones are accumulations or mineral deposits that form in the calyces, renal pelvis, or urinary tract. Purpose: To describe the sociodemographic and clinical characteristics of a sample of patients with kidney stones over 18 years of age. Methodology: Descriptive observational study. Patients treated in an outpatient nephrology and urology consultation in Manizales during the years 2010 to 2020, in which there were studies in blood, 24-hour urine, and a physicochemical study of the stone, as well as related sociodemographic and clinical data. They were divided into groups, according to the findings found in the available stones, dividing into calcium oxalate in its entirety, calcium mixed with another compound and the last group of non-calcium stone. Results: 54 patients with nephrolithiasis were identified, 14 of them were excluded. Finally, 40 patients met the inclusion criteria. Median age was 52.5 years, male predominance (55%), hyperuricemia was found in 20.5%, hypercalcemia in 17.6%, hyperphosphatemia in 5% and hyperkalemia in 7.5%. In urine, hypocitraturia was found in 71.1%, followed by hypercalciuria (12.5%), hyperuricosuria (10%), and hyperoxaluria (5%). In 17 patients (42.5%) there was a result of the physicochemical composition of the stone, in them the mixed calcium variety was the most frequent (55.5%). Conclusions: This study describes the characteristics of patients with kidney stones, showing that the majority have metabolic alterations associated with nephrolithiasis, hypocitraturia being the most frequent finding, and that most stones have calcium in their composition.

Improving classification based on physical surface tension-neural net for the prediction of psychosocial-risk level in public school teachers.

BACKGROUND: Psychosocial risks, also present in educational processes, are stress factors particularly critical in state-schools, affecting the efficacy, stress, and job satisfaction of the teachers. This study proposes an intelligent algorithm to improve the prediction of psychosocial risk, as a tool for the generation of health and risk prevention assistance programs. METHODS: The proposed approach, Physical Surface Tension-Neural Net (PST-NN), applied the theory of superficial tension in liquids to an artificial neural network (ANN), in order to model four risk levels (low, medium, high and very high psychosocial risk). The model was trained and tested using the results of tests for measurement of the psychosocial risk levels of 5,443 teachers. Psychosocial, and also physiological and musculoskeletal symptoms, factors were included as inputs of the model. The classification efficiency of the PST-NN approach was evaluated by using the sensitivity, specificity, accuracy and ROC curve metrics, and compared against other techniques as the Decision Tree model, Naïve Bayes, ANN, Support Vector Machines, Robust Linear Regression and the Logistic Regression Model. RESULTS: The modification of the ANN model, by the adaptation of a layer that includes concepts related to the theory of physical surface tension, improved the separation of the subjects according to the risk level group, as a function of the mass and perimeter outputs. Indeed, the PST-NN model showed better performance to classify psychosocial risk level on state-school teachers than the linear, probabilistic and logistic models included in this study, obtaining an average accuracy value of 97.31%. CONCLUSIONS: The introduction of physical models, such as the physical surface tension, can improve the classification performance of ANN. Particularly, the PST-NN model can be used to predict and classify psychosocial risk levels among state-school teachers at work. This model could help to early identification of psychosocial risk and to the development of programs to prevent it.

Are Strategies Favoring Pattern Matching a Viable Way to Improve Complexity Estimation Based on Sample Entropy?

It has been suggested that a viable strategy to improve complexity estimation based on the assessment of pattern similarity is to increase the pattern matching rate without enlarging the series length. We tested this hypothesis over short simulations of nonlinear deterministic and linear stochastic dynamics affected by various noise amounts. Several transformations featuring a different ability to increase the pattern matching rate were tested and compared to the usual strategy adopted in sample entropy (SampEn) computation. The approaches were applied to evaluate the complexity of short-term cardiac and vascular controls from the beat-to-beat variability of heart period (HP) and systolic arterial pressure (SAP) in 12 Parkinson disease patients and 12 age- and gender-matched healthy subjects at supine resting and during head-up tilt. Over simulations, the strategies estimated a larger complexity over nonlinear deterministic signals and a greater regularity over linear stochastic series or deterministic dynamics importantly contaminated by noise. Over short HP and SAP series the techniques did not produce any practical advantage, with an unvaried ability to discriminate groups and experimental conditions compared to the traditional SampEn. Procedures designed to artificially increase the number of matches are of no methodological and practical value when applied to assess complexity indexes.

Multiscale entropy analysis of heart rate variability in heart failure, hypertensive, and sinoaortic-denervated rats: classical and refined approaches.

The analysis of heart rate variability (HRV) by nonlinear methods has been gaining increasing interest due to their ability to quantify the complexity of cardiovascular regulation. In this study, multiscale entropy (MSE) and refined MSE (RMSE) were applied to track the complexity of HRV as a function of time scale in three pathological conscious animal models: rats with heart failure (HF), spontaneously hypertensive rats (SHR), and rats with sinoaortic denervation (SAD). Results showed that HF did not change HRV complexity, although there was a tendency to decrease the entropy in HF animals. On the other hand, SHR group was characterized by reduced complexity at long time scales, whereas SAD animals exhibited a smaller short- and long-term irregularity. We propose that short time scales (1 to 4), accounting for fast oscillations, are more related to vagal and respiratory control, whereas long time scales (5 to 20), accounting for slow oscillations, are more related to sympathetic control. The increased sympathetic modulation is probably the main reason for the lower entropy observed at high scales for both SHR and SAD groups, acting as a negative factor for the cardiovascular complexity. This study highlights the contribution of the multiscale complexity analysis of HRV for understanding the physiological mechanisms involved in cardiovascular regulation.

Sedation-analgesia with propofol and remifentanil: concentrations required to avoid gag reflex in upper gastrointestinal endoscopy.

BACKGROUND: The purpose of this study was to identify optimal target propofol and remifentanil concentrations to avoid a gag reflex in response to insertion of an upper gastrointestinal endoscope. METHODS: Patients presenting for endoscopy received target-controlled infusions (TCI) of both propofol and remifentanil for sedation-analgesia. Patients were randomized to 4 groups of fixed target effect-site concentrations: remifentanil 1 ng•mL (REMI 1) or 2 ng•mL (REMI 2) and propofol 2 µg•mL (PROP 2) or 3 µg•mL (PROP 3). For each group, the other drug (propofol for the REMI groups and vice versa) was increased or decreased using the "up-down" method based on the presence or absence of a gag response in the previous patient. A modified isotonic regression method was used to estimate the median effective Ce,50 from the up-down method in each group. A concentration-effect (sigmoid Emax) model was built to estimate the corresponding Ce,90 for each group. These data were used to estimate propofol bolus doses and remifentanil infusion rates that would achieve effect-site concentrations between Ce,50 and Ce,90 when a TCI system is not available for use. RESULTS: One hundred twenty-four patients were analyzed. To achieve between a 50% and 90% probability of no gag response, propofol TCIs were between 2.40 and 4.23 µg•mL (that could be achieved with a bolus of 1 mg•kg) when remifentanil TCI was fixed at 1 ng•mL, and target propofol TCIs were between 2.15 and 2.88 µg•mL (that could be achieved with a bolus of 0.75 mg•kg) when remifentanil TCI was fixed at 2 ng•mL. Remifentanil ranges were 1.00 to 4.79 ng•mL and 0.72 to 3.19 ng•mL when propofol was fixed at 2 and 3 µg•mL, respectively. CONCLUSIONS: We identified a set of propofol and remifentanil TCIs that blocked the gag response to endoscope insertion in patients undergoing endoscopy. Propofol bolus doses and remifentanil infusion rates designed to achieve similar effect-site concentrations can be used to prevent gag response when TCI is not available.

Prediction of Nociceptive Responses during Sedation by Linear and Non-Linear Measures of EEG Signals in High Frequencies.

The level of sedation in patients undergoing medical procedures evolves continuously, affected by the interaction between the effect of the anesthetic and analgesic agents and the pain stimuli. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. The purpose of this work is to improve the prediction of nociceptive responses with linear and non-linear measures calculated from EEG signal filtered in frequency bands higher than the traditional bands. Power spectral density and auto-mutual information function was applied in order to predict the presence or absence of the nociceptive responses to different stimuli during sedation in endoscopy procedure. The proposed measures exhibit better performances than the bispectral index (BIS). Values of prediction probability of Pk above 0.75 and percentages of sensitivity and specificity above 70% were achieved combining EEG measures from the traditional frequency bands and higher frequency bands.

Symbolic dynamics to discriminate healthy and ischaemic dilated cardiomyopathy populations: an application to the variability of heart period and QT interval.

Myocardial ischaemia is hypothesized to stimulate the cardiac sympathetic excitatory afferents and, therefore, the spontaneous changes of heart period (approximated as the RR interval), and the QT interval in ischaemic dilated cardiomyopathy (IDC) patients might reflect this sympathetic activation. Symbolic analysis is a nonlinear and powerful tool for the extraction and classification of patterns in time-series analysis, which implies a transformation of the original series into symbols and the construction of patterns with the symbols. The aim of this work was to investigate whether symbolic transformations of RR and QT cardiac series can provide a better separation between IDC patients and healthy control (HC) subjects compared with traditional linear measures. The variability of these cardiac series was studied during daytime and night-time periods and also during the complete 24 h recording over windows of short data sequences of approximately 5 min. The IDC group was characterized by an increase in the occurrence rate of patterns without variations (0 V%) and a reduction in the occurrence rate of patterns with one variation (1 V%) and two variations (2 V%). Concerning the RR variability during the daytime, the highest number of patterns had 0 V%, whereas the rates of 1 V% and 2 V% were lower. During the night, 1 V% and 2 V% increased at the expense of diminishing 0 V%. Patterns with and without variations between consecutive symbols were able to increase the separation between the IDC and HC groups, allowing accuracies higher than 80%. With regard to entropy measures, an increase in RR regularity was associated with cardiac disease described by accuracy >70% in the RR series and by accuracy >60% in the QTc series. These results could be associated with an increase in the sympathetic tone in IDC patients.

Interaction between EEG and drug concentration to predict response to noxious stimulation during sedation-analgesia: effect of the A118G genetic polymorphism.

The level of sedation in patients undergoing medical procedures is affected by the interaction between the effect of the anesthetic and analgesic agents and the pain stimuli. The presence of the A118G single nucleotide polymorphism (SNP) in the OPRM1 gene affects the requirements of opioids for patients undergoing sedation-analgesia. The purpose of this work is to evaluate the influence of the SNP A118G in OPRM1 on EEG measures for the prediction of the response to pain stimulation during endoscopy procedure. The proposed measures were based on power spectral density and auto-mutual information function. It was found that the statistical performances of the EEG measures improved when the presence of the SNP was taken into account (prediction probability Pk>0.9).

Role of innate immunity against human papillomavirus (HPV) infections and effect of adjuvants in promoting specific immune response.

During the early stages of human papillomavirus (HPV) infections, the innate immune system creates a pro-inflammatory microenvironment by recruiting innate immune cells to eliminate the infected cells, initiating an effective acquired immune response. However, HPV exhibits a wide range of strategies for evading immune-surveillance, generating an anti-inflammatory microenvironment. The administration of new adjuvants, such as TLR (Toll-like receptors) agonists and alpha-galactosylceramide, has been demonstrated to reverse the anti-inflammatory microenvironment by down-regulating a number of adhesion molecules and chemo-attractants and activating keratinocytes, dendritic (DC), Langerhans (LC), natural killer (NK) or natural killer T (NKT) cells; thus, promoting a strong specific cytotoxic T cell response. Therefore, these adjuvants show promise for the treatment of HPV generated lesions and may be useful to elucidate the unknown roles of immune cells in the natural history of HPV infection. This review focuses on HPV immune evasion mechanisms and on the proposed response of the innate immune system, suggesting a role for the surrounding pro-inflammatory microenvironment and the NK and NKT cells in the clearance of HPV infections.

Prediction of nociceptive responses during sedation by time-frequency representation.

The level of sedation in patients undergoing medical procedures evolves continuously, such as the effect of the anesthetic and analgesic agents is counteracted by pain stimuli. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. The purpose of this work is to analyze the capability of prediction of nociceptive responses based on the time-frequency representation (TFR) of EEG signal. Functions of spectral entropy, instantaneous power and instantaneous frequency were calculated in order to predict the presence or absence of the nociceptive responses to different stimuli during sedation in endoscopy procedure. Values of prediction probability of Pk above 0.75 and percentages of sensitivity and specificity above 70% and 65% respectively were achieved combining TFR functions with bispectral index (BIS) and with concentrations of propofol (CeProp) and remifentanil (CeRemi).

Refined multiscale entropy: application to 24-h Holter recordings of heart period variability in healthy and aortic stenosis subjects.

Multiscale entropy (MSE) was proposed to characterize complexity as a function of the time-scale factor tau. Despite its broad use, this technique suffers from two limitations: 1) the artificial MSE reduction due to the coarse graining procedure and 2) the introduction of spurious MSE oscillations due to the suboptimal procedure for the elimination of the fast temporal scales. We propose a refined MSE (RMSE), and we apply it to simulations and to 24-h Holter recordings of heart rate variability (HRV) obtained from healthy and aortic stenosis (AS) groups. The study showed that the refinement relevant to the elimination of the fast temporal scales was more helpful at short scales (spanning the range of short-term HRV oscillations), while that relevant to the procedure of coarse graining was more useful at large scales. In healthy subjects, during daytime, RMSE was smaller at short scales (i.e., tau = 1-2) and larger at longer scales (i.e., tau = 4-20) than during nighttime. In AS population, RMSE was smaller during daytime both at short and long time scales (i.e., tau = 1 -11) than during nighttime. RMSE was larger in healthy group than in AS population during both daytime (i.e., tau = 2 -9) and nighttime (i.e., tau = 2). RMSE overcomes two limitations of MSE and confirms the complementary information that can be derived by observing complexity as a function of the temporal scale.