Challenges for eGFR equations in the developing world.

The populations in countries that have the highest number of individuals with chronic kidney disease (CKD) are the low and middle-income countries which are ethnically diverse. The regional and international data highlighting the need for continuous monitoring of renal function warrants that such countries use equations that give the best estimates of glomerular filtration rate for their settings. While chronic disease conditions such as diabetes and hypertension are the main conditions associated with CKD in adult populations and complicated urinary tract infections and congenital anomalies in the kidney and the urinary tract in the young, the management of patients with CKD at any age can be impacted by medical and non-biological factors. This communication seeks to posit issues that may be germane to consider when using the CKD-EPI 2021 equations in the adult and young adult populations. These equations, by excluding the race factor, have put the spotlight on the relevance of the cultural and economic context concerning the management of renal patents. The social determinants of health, how an individual defines their gender, the cultural acceptance of such or the lack thereof, factors influencing the choice of the test, communication, and technology among others may all affect renal care. These issues together may have a greater impact on renal patient care and outcome than racial disparity. While the racial divide may have been a driver for differential treatment in developed nations with different ethnic groups they may be less so when compared with more homogenous populations.

Differences in percentage predicted spirometric values obtained with thirteen reference equations applied to healthy children.

BACKGROUND: There is limited information on the discrepancy between the spirometric values calculated with diverse spirometric prediction equations in normal children. OBJECTIVE: To determine the differences in percentage predicted (PP) values calculated through thirteen prediction equations (PEs) in healthy Chilean children. METHODS: We compared the PP values for FVC, FEV1, FEF25-75% and FEV1/FVC obtained by applying thirteen PEs, using GLI-2012 as a gold standard reference equation and including race neutral GLI-2022 in the analysis; PP values are from a group of 208 healthy Chilean children aged 7 to 17 years. RESULTS: In boys, the range of differences for FVC between PEs compared to the reference group went from -5.47% to 20.82% and from -6.4% to 19.74% in girls. For FEV1, in girls, the range of differences went from -5.96% to 18.01% and from -5,04% to 20.67% in boys. Significant differences between GLI-2012 PPs and the other PEs were observed more frequently in girls than in boys (p < 0.001). CONCLUSIONS: There is a wide difference between the spirometric PPs values by different PEs, including race neutral GLI-2022. Our findings, especially given the potential interpretative and clinical implications, might suggest the need for conducting standardized, multicenter studies in Latin America to determine which PEs would better fit pediatric populations in this region.

Exploring Limit Cycles of Differential Equations through Information Geometry Unveils the Solution to Hilbert's 16th Problem.

The detection of limit cycles of differential equations poses a challenge due to the type of the nonlinear system, the regime of interest, and the broader context of applicable models. Consequently, attempts to solve Hilbert's sixteenth problem on the maximum number of limit cycles of polynomial differential equations have been uniformly unsuccessful due to failing results and their lack of consistency. Here, the answer to this problem is finally obtained through information geometry, in which the Riemannian metrical structure of the parameter space of differential equations is investigated with the aid of the Fisher information metric and its scalar curvature R. We find that the total number of divergences of |R| to infinity provides the maximum number of limit cycles of differential equations. Additionally, we demonstrate that real polynomial systems of degree n≥2 have the maximum number of 2(n-1)(4(n-1)-2) limit cycles. The research findings highlight the effectiveness of geometric methods in analyzing complex systems and offer valuable insights across information theory, applied mathematics, and nonlinear dynamics. These insights may pave the way for advancements in differential equations, presenting exciting opportunities for future developments.

Dynamic survival analysis: Modelling the hazard function via ordinary differential equations.

The hazard function represents one of the main quantities of interest in the analysis of survival data. We propose a general approach for parametrically modelling the dynamics of the hazard function using systems of autonomous ordinary differential equations (ODEs). This modelling approach can be used to provide qualitative and quantitative analyses of the evolution of the hazard function over time. Our proposal capitalises on the extensive literature on ODEs which, in particular, allows for establishing basic rules or laws on the dynamics of the hazard function via the use of autonomous ODEs. We show how to implement the proposed modelling framework in cases where there is an analytic solution to the system of ODEs or where an ODE solver is required to obtain a numerical solution. We focus on the use of a Bayesian modelling approach, but the proposed methodology can also be coupled with maximum likelihood estimation. A simulation study is presented to illustrate the performance of these models and the interplay of sample size and censoring. Two case studies using real data are presented to illustrate the use of the proposed approach and to highlight the interpretability of the corresponding models. We conclude with a discussion on potential extensions of our work and strategies to include covariates into our framework. Although we focus on examples of Medical Statistics, the proposed framework is applicable in any context where the interest lies in estimating and interpreting the dynamics of the hazard function.

Comparison between the Friedewald, Martin and Sampson Equations and LDL-C Quantification by Ultracentrifugation in a Mexican Population.

Low-density lipoprotein cholesterol (LDL-C), which makes up about 70% of the cholesterol in the blood, is critical in the formation of arteriosclerotic plaques, increasing the risk of heart disease. LDL-C levels are estimated using Friedewald, Martin and Sampson equations, though they have limitations with high triglycerides. Our aim is to compare the effectiveness of these equations versus the ultracentrifugation technique in individuals with and without dyslipidemia and identify precision. There were 113 participants, 59 healthy controls and 54 dyslipidemic patients. Samples were collected after fasting. LDL-C was estimated using the Friedewald, Martin and Sampson equations. The purified LDL-C, ultracentrifugated and dialysized control group without dyslipidemia vs. patients with coronary artery disease (CAD) showed differences in age, HDL-C, triglycerides and glucose non-HDL-C (p = 0.001 in all). There were correlations in CGWD between ultracentrifugation and Sampson R-squared (R2) = 0.791. In the dyslipidemia control group, ultracentrifugation and Friedewald R2 = 0.911. In patients with CAD, correlation between ultracentrifugation and Sampson R2 = 0.892; Bland-Altman confirmed agreement in controls without dyslipidemia. The Martin and Sampson equations are interchangeable with ultracentrifugation. Conclusion: The role of LDL analysis using precise techniques is necessary to obtain better control of disease outcomes after the use of precise therapies and suggests verifying its importance through clinical trials.

Influence of sustainability in the positioning of the university brand: Study in universities in Medellín-Colombia.

The implementation of university sustainability affects brand perceptions by conferring attributes related to commitment and reputation, especially by students. The proper management of sustainability is related to an improvement in the university brand perceived by its stakeholders, including students. For this reason, this research aims to analyse whether university sustainability positively affects brand positioning among university students. For this purpose, a theoretical and quantitative mixed-method investigation is proposed that allows the establishment of a structural model in which the relationships between the dimensions of university sustainability with the dimensions of brand positioning are evident. The empirical analysis found that some dimensions of university sustainability, such as the institutional framework, campus operations and some dimensions of the substantive functions, positively affect brand positioning in university students and generate commitment to the university from both the prestige and reputation of the brand.

Adequacy of basal metabolic rate prediction equations in individuals with severe obesity: A systematic review and meta-analysis.

The determination of energy requirements in clinical practice is based on basal metabolic rate (BMR), frequently predicted by equations that may not be suitable for individuals with severe obesity. This systematic review and meta-analysis examined the accuracy and precision of BMR prediction equations in adults with severe obesity. Four databases were searched in March 2021 and updated in May 2023. Eligible studies compared BMR prediction equations with BMR measured by indirect calorimetry. Forty studies (age: 28-55 years, BMI: 40.0-62.4 kg/m2) were included, most of them with a high risk of bias. Studies reporting bias (difference between estimated and measured BMR) were included in the meta-analysis (n = 20). Six equations were meta-analyzed: Harris & Benedict (1919); WHO (weight) (1985); Owen (1986); Mifflin (1990); Bernstein (1983); and Cunningham (1980). The most accurate and precise equations in the overall analysis were WHO (-12.44 kcal/d; 95%CI: -81.4; 56.5 kcal/d) and Harris & Benedict (-18.9 kcal/d; 95%CI -73.2; 35.2 kcal/d). All the other equations tended to underestimate BMR. Harris & Benedict and WHO were the equations with higher accuracy and precision in predicting BMR in individuals with severe obesity. Additional analyses suggested that equations may perform differently according to obesity BMI ranges, which warrants further investigation.

Prediction of fat-free mass from body surface area in young basketball players.

BACKGROUND: Fat Free Mass (FFM) is an important and essential indicator in various sports populations, since greater muscle and bone mass generates greater strength, endurance and speed in athletes. OBJECTIVE: The purpose of the study was to validate Body Surface Area (BSA) as an anthropometric indicator to estimate FFM in young basketball players. METHODS: A descriptive cross-sectional study was carried out in 105 male basketball players of the Brazilian Basketball Confederation of Sao Paulo (Campinas), Brazil. The age range was 11 to 15 years. Weight and height were evaluated. BSA, body mass index (BMI) and maturity status (MS) were calculated. Total body scanning was performed by dual X-ray absorptiometry (DXA). The components were extracted: Fat mass (FM), Fat free mass (FFM), percentage of fat mass (%FM) and bone mass (BM). The data were analyzed using the correlation coefficient of concordance (CCC) in terms of precision and accuracy. RESULTS: Three regression equations were generated: equation 1 had age and body weight as predictors [FFM= -30.059+(2.926*age)+(0.625*Weight)] (R2 = 92%, precision = 0.96 and accuracy = 0.99), equation 2 used age and BSA [FFM=-45.719+(1.934*age)+(39.388*BSA)] (R2 = 94%, precision = 0.97 and accuracy = 0.99) and equation 3 was based on APHV and BSA [FFM=-15.284+(1.765*APHV)+(37.610*(BSA)] (R2 = 94%, precision = 0.96 and accuracy = 0.99). CONCLUSIONS: The results suggest the use of anthropometric equation using decimal age and BSA to estimate FFM in young basketball players. This new method developed can be used to design, evaluate and control training programs and monitor the weight status of athletes.

On a deterministic mathematical model which efficiently predicts the protective effect of a plant extract mixture in cirrhotic rats.

In this work, we propose a mathematical model that describes liver evolution and concentrations of alanine aminotransferase and aspartate aminotransferase in a group of rats damaged with carbon tetrachloride. Carbon tetrachloride was employed to induce cirrhosis. A second groups damaged with carbon tetrachloride was exposed simultaneously a plant extract as hepatoprotective agent. The model reproduces the data obtained in the experiment reported in [Rev. Cub. Plant. Med. 22(1), 2017], and predicts that using the plants extract helps to get a better natural recovery after the treatment. Computer simulations show that the extract reduces the damage velocity but does not avoid it entirely. The present paper is the first report in the literature in which a mathematical model reliably predicts the protective effect of a plant extract mixture in rats with cirrhosis disease. The results reported in this manuscript could be used in the future to help in fighting cirrhotic conditions in humans, though more experimental and mathematical work is required in that case.

Discrete and Semi-Discrete Multidimensional Solitons and Vortices: Established Results and Novel Findings.

This article presents a concise survey of basic discrete and semi-discrete nonlinear models, which produce two- and three-dimensional (2D and 3D) solitons, and a summary of the main theoretical and experimental results obtained for such solitons. The models are based on the discrete nonlinear Schrödinger (DNLS) equations and their generalizations, such as a system of discrete Gross-Pitaevskii (GP) equations with the Lee-Huang-Yang corrections, the 2D Salerno model (SM), DNLS equations with long-range dipole-dipole and quadrupole-quadrupole interactions, a system of coupled discrete equations for the second-harmonic generation with the quadratic (χ(2)) nonlinearity, a 2D DNLS equation with a superlattice modulation opening mini-gaps, a discretized NLS equation with rotation, a DNLS coupler and its PT-symmetric version, a system of DNLS equations for the spin-orbit-coupled (SOC) binary Bose-Einstein condensate, and others. The article presents a review of the basic species of multidimensional discrete modes, including fundamental (zero-vorticity) and vortex solitons, their bound states, gap solitons populating mini-gaps, symmetric and asymmetric solitons in the conservative and PT-symmetric couplers, cuspons in the 2D SM, discrete SOC solitons of the semi-vortex and mixed-mode types, 3D discrete skyrmions, and some others.

Longitudinal Quantiles of Frailty Trajectories Considering Death: New Insights into Sex and Cohort Differences in the Reference Curves for Frailty Progression of Older European.

BACKGROUND: Most previous studies of frailty trajectories in older adults focus on the average trajectory and ignore death. Longitudinal quantile analysis of frailty trajectories permits the definition of reference curves, and the application of mortal cohort inference provides more realistic estimates than models that ignore death. METHODS: Using data from individuals aged 65 or older (n = 25 446) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) from 2004 to 2020, we derived repeated values of the Frailty Index (FI) based on the accumulation of health deficits. We applied weighted Generalized Estimating Equations to estimate the quantiles of the FI trajectory, adjusting for sample attrition due to death, sex, education, and cohort. RESULTS: The FI quantiles increased with age and progressed faster for those with the highest level of frailty (ß^a0.9 = 0.0229, p < .001; ß^a0.5 = 0.0067, p < .001; H0: ßa0.5=ßa0.9, p < .001). Education was consistently associated with a slower progression of the FI in all quantiles (ß^ae0.1 = -0.0001, p < .001; ß^ae0.5 =-0.0004, p < .001; ß^ae0.9 = -0.0003, p < .001) but sex differences varied across the quantiles. Women with the highest level of frailty showed a slower progression of the FI than men when considering death. Finally, no cohort effects were observed for the FI progression. CONCLUSIONS: Quantile FI trajectories varied by age, sex, education, and cohort. These differences could inform the practice of interventions aimed at older adults with the highest level of frailty.

Precise Modeling of the Particle Size Distribution in Emulsion Polymerization: Numerical and Experimental Studies for Model Validation under Ab Initio Conditions.

The particle size distribution (PSD) in emulsion polymerization (EP) has been modeled in the past using either the pseudo bulk (PB) or the 0-1/0-1-2 approaches. There is some controversy on the proper type of model to be used to simulate the experimental PSDs, which are apparently broader than the theoretical ones. Additionally, the numerical technique employed to solve the model equations, involving hyperbolic partial differential equations (PDEs) with moving and possibly steep fronts, has to be precise and robust, which is not a trivial matter. A deterministic kinetic model for the PSD evolution of ab initio EP of vinyl monomers was developed to investigate these issues. The model considers three phases, micellar nucleation, and particles that can contain n≥0 radicals. Finite volume (FV) and weighted-residual methods are used to solve the system of PDEs and compared; their limitations are also identified. The model was validated by comparing predictions with data of monomer conversion and PSD for the batch emulsion homopolymerization of styrene (Sty) and methyl methacrylate (MMA) using sodium dodecyl sulfate (SDS)/potassium persulfate (KPS) at 60 °C, as well as the copolymerization of Sty-MMA (50/50; mol/mol) at 50 and 60 °C. It is concluded that the PB model has a structural problem when attempting to adequately represent PSDs with steep fronts, so its use is discouraged. On the other hand, there is no generalized evidence of the need to add a stochastic term to enhance the PSD prediction of EP deterministic models.

Analysis of Adverse Drug Reactions in Pediatric Patients with Epilepsy: An Intensive Pharmacovigilance Study.

Epilepsy is a chronic neurological disease characterized by the presence of spontaneous seizures, with a higher incidence in the pediatric population. Anti-seizure medication (ASM) may produce adverse drug reactions (ADRs) with an elevated frequency and a high severity. Thus, the objective of the present study was to analyze, through intensive pharmacovigilance over 112 months, the ADRs produced by valproic acid (VPA), oxcarbazepine (OXC), phenytoin (PHT), and levetiracetam (LEV), among others, administered to monotherapy or polytherapy for Mexican hospitalized pediatric epilepsy patients. A total of 1034 patients were interviewed; 315 met the inclusion criteria, 211 patients presented ADRs, and 104 did not. A total of 548 ASM-ADRs were identified, and VPA, LEV, and PHT were the main culprit drugs. The most frequent ADRs were drowsiness, irritability, and thrombocytopenia, and the main systems affected were hematologic, nervous, and dermatologic. LEV and OXC caused more nonsevere ADRs, and PHT caused more severe ADRs. The risk analysis showed an association between belonging to the younger groups and polytherapy with ADR presence and between polytherapy and malnutrition with severe ADRs. In addition, most of the severe ADRs were preventable, and most of the nonsevere ADRs were nonpreventable.

Analysis of the influence of the COVID-19 outbreak on household solid waste management: An empirical study using PLS-SEM.

The global increase in solid waste pollution due to economic growth and population growth has led to severe ecological deterioration. This situation is exacerbated by the ongoing coronavirus disease (COVID-19) pandemic, which has significantly impacted consumer behavior and consumption habits. Proper management of solid waste has thus become critical in mitigating environmental degradation. In this study, we aim to examine the relationship between the outbreak of COVID-19, environmental attitudes (EATT), social norms (SN), environmental knowledge (EK), technological innovation (TI), and solid waste management (SWM) in Ecuadorian households during the pandemic. We collected data from 426 households in Ecuador using an online questionnaire and analyzed it using the Partial Least Squares Structural Equation Model method to test the hypotheses. Likewise, we validated the measurement and structural model. The results are novel about SWM, considering a developing country severely affected during the pandemic. Our findings suggest that COVID-19 has a negative impact on SWM, while EATT, SN, and TI have a positive influence on SWM. However, we found that EK does not significantly affect SWM.

Modelling of surface reactions and diffusion mediated by bulk diffusion.

We develop a continuum framework applicable to solid-state hydrogen storage, cell biology and other scenarios where the diffusion of a single constituent within a bulk region is coupled via adsorption/desorption to reactions and diffusion on the boundary of the region. We formulate content balances for all relevant constituents and develop thermodynamically consistent constitutive equations. The latter encompass two classes of kinetics for adsorption/desorption and chemical reactions-fast and Marcelin-De Donder, and the second class includes mass action kinetics as a special case. We apply the framework to derive a system consisting of the standard diffusion equation in bulk and FitzHugh-Nagumo type surface reaction-diffusion system of equations on the boundary. We also study the linear stability of a homogeneous steady state in a spherical region and establish sufficient conditions for the occurrence of instabilities driven by surface diffusion. These findings are verified through numerical simulations which reveal that instabilities driven by diffusion lead to the emergence of steady-state spatial patterns from random initial conditions and that bulk diffusion can suppress spatial patterns, in which case temporal oscillations can ensue. We include an extension of our framework that accounts for mechanochemical coupling when the bulk region is occupied by a deformable solid. This article is part of the theme issue 'Foundational issues, analysis and geometry in continuum mechanics'.

"Multivariate analysis of the impact of sleep and working hours on medical errors: a MICE approach".

BACKGROUND: The main objective of this study was to describe the relationship between working conditions, sleep and psycho-affective variables and medical errors. METHODS: This was an observational, analytical and cross-sectional study in which 661 medical residents answered questionnaires about working conditions, sleep and psycho-affective variables. Actigraphic sleep parameters and peripheral temperature circadian rhythm were measured in a subgroup of 38 subjects. Bivariate and multivariate predictors of medical errors were assessed. RESULTS: Medical residents reported working 66.2 ± 21.9 weekly hours. The longest continuous shift was of 28.4 ± 10.9 h. They reported sleeping 6.1 ± 1.6 h per day, with a sleep debt of 94 ± 129 min in workdays. A high percentage of them reported symptoms related to psycho-affective disorders. The longest continuous shift duration (OR = 1.03 [95% CI, 1.00-1.05], p = 0.01), working more than six monthly on-call shifts (OR = 1.87 [95% CI, 1.16-3.02], p = 0.01) and sleeping less than six hours per working day (OR = 1.66 [95% CI, 1.10-2.51], p = 0.02) were independently associated with self-reported medical errors. The report of medical errors was associated with an increase in the percentage of diurnal sleep (2.2% [95% CI, 0.1-4.3] vs 14.5% [95% CI, 5.9-23.0]; p = 0.01) in the actigraphic recording. CONCLUSIONS: Medical residents have a high working hour load that affect their sleep opportunities, circadian rhythms and psycho-affective health, which are also related to the report of medical errors. These results highlight the importance of implementing multidimensional strategies to improve medical trainees' sleep and wellbeing, increasing in turn their own and patients' safety.

Estimates of Resting Energy Expenditure and Total Energy Expenditure Using Predictive Equations for Individuals After Bariatric Surgery: a Systematic Review with Meta-analysis.

PURPOSE: Patients after metabolic bariatric surgery (MBS) require attention to maintain energy balance and avoid weight regain. Predictive equations for resting energy expenditure (REE) and total energy expenditure (TEE) are needed since gold standard methods like calorimetry and doubly labeled water are rarely available in routine clinical practice. This study aimed to determine which predictive equation for REE and TEE has the lowest bias in subjects after MBS. METHODS: MEDLINE, Embase, Web of Science, and CENTRAL searches were performed. Meta-analyses were performed with the data calculated by the predictive equations and measured by the gold standard methods for those equations that had at least two studies with these data. The DerSimonian and Laird random-effects model and the I2 statistic were used to quantify heterogeneity in the quantitative analyses. The risk of bias was assessed using the Joanna Briggs Institute critical appraisal checklist. RESULTS: Seven studies were included. The present study found that the Mifflin St. Jeor (1990) equation had the lowest bias (mean difference = - 39.71 kcal [95%CI = - 128.97; 49.55]) for calculating REE in post-BS individuals. The Harris-Benedict (1919) equation also yielded satisfactory results (mean difference = - 54.60 kcal [95%CI = - 87.92; - 21.28]). CONCLUSION: The predictive equation of Mifflin St. Jeor (1990) was the one that showed the lowest bias for calculating the REE of patients following MBS.

Bifactor SEM and MIRT Structure of a 12-Item Human Immunodeficiency Virus Stigma Scale in Peruvian Adults.

BACKGROUND: The stigma associated with human immunodeficiency virus (HIV) can lead to prejudice and discrimination against people who have been infected by this virus, consequently, it is important to have a validated tool to measure this phenomenon. However, there is only 1 national precedent that has validated the scores of this instrument in its 21-item version. Therefore, this study examined the bifactor structural equation method (SEM) and multidimensional item response theory (MIRT) structure of a 12-item human immunodeficiency virus stigma scale in Peruvian adults. METHODS: We evaluated 342 patients (57.6% female and 42.45% male) diagnosed with HIV receiving highly active antiretroviral therapy (HAART) from a hospital located in East Lima, aged 18 to 45 years (M = 31.4, SD = 9.79). A SEM was used to test 2 measurement models, a 4-factor correlated oblique model and a bifactor model due to high interfactor relationships. RESULTS: Acceptable fit indices were identified for the oblique model (χ2/df = 1.26, SRMR = 0.044, RMSEA [90% CI] = 0.028 [0.000-0.047], CFI = 0.996, TLI = 0.994). In the same way, similar results were evident for the bifactor model (χ2/df = 1.14, SRMR = 0.039, RMSEA [90% CI] = 0.020 [0.000-0.044], CFI = 0.998, TLI = 0.997), however, in the latter it showed a greater explanation for the unidimensional model (H = 0.87, PUC = 0.82, LCA = 0.70), which was also evidenced by the bifactor MIRT analysis. CONCLUSION: It is concluded that the 12-item HIV Stigma Scale meets the psychometric properties of internal structure and unifactorial reliability.

Predicting body weight through biometric measurements in growing hair sheep using data mining and machine learning algorithms.

Determination of live weight, which is one of the most important features that determine meat production, is a very important issue for herd management and sustainable livestock. In this context, the necessity of finding alternative methods has emerged, especially in rural conditions, due to the difficulties to be experienced in finding the weighing tool. Especially for conditions with no weighing tool, it has been tried to establish relations between the information obtained from body measurements and live weight. Since these studies will differ from species to species and breed to breed, the need for new studies is extremely high. For this aim, it is to evaluate the body measurement information obtained with the present study using several statistical approaches. To implement this aim, several data mining and machine learning algorithms such as multivariate adaptive regression splines (MARS), classification and regression tree (CART), and support vector machine regression (SVR) algorithms were used for training (70%) and test (30%) sets. To predict final body weight, 280 hair sheep breeds (162 female and 118 male) ranging from 2 months to 3 years were used with different data mining and machine learning approaches. Various goodness-of-fit criteria were used to evaluate the performances of the aforementioned algorithms. Although the MARS and SVR algorithms gave the same and highest results in terms of R2 and r values for both the train and the test sets, the SVR algorithm is one of the methods to be recommended as a result of this study, especially when other goodness-of-fit criteria are evaluated. In conclusion, the usage of SVR algorithms may be a useful tool of machine learning approaches for detecting the hair sheep breed standards and may contribute to increasing the sheep meat quality in Mexico.

Solving the Power Flow Problem in Bipolar DC Asymmetric Distribution Networks Using Broyden's Method.

This research addresses the power flow analysis in bipolar asymmetric direct current (DC) networks by applying Broyden's numerical method. This general successive approximations method allows for a simple Newton-based recursive formula to reach the roots of multiple nonlinear equations. The main advantage of Broyden's approach is its simple but efficient structure which can be applied to real complex nonlinear equations.The power flow problem in bipolar DC networks is still challenging, as multiple operating options must be considered, e.g., the possibility of having a solidly grounded or floating neutral wire. The main goal of this research is to contribute with a generalization of Broyden's method for the power flow solution in bipolar DC networks, with the main advantage that, under well-defined conditions, this is a numerical method equivalent to the matricial backward/forward power flow, which is equivalent to the successive approximations power flow method. Numerical results in the 21-, 33-, and 85-bus grids while considering two connections for the neutral wire (i.e., solidly grounded at any node or floating) show the effectiveness of Broyden's method in the power flow solution for bipolar asymmetric DC networks. All numerical simulations were carried out in the MATLAB programming environment.