Objective Variables Research Articles

Predictors of the development of febrile neutropenia in chemotherapy for advanced germ cell tumors.

To identify the predictive factors for the development of febrile neutropenia (FN) in the course of chemotherapy for patients with germ cell tumors. From January 2005 to December 2018, 80 patients were treated with induction chemotherapy for advanced germ cell tumors at Kanagawa Cancer Center Hospital, Japan. Of these, we retrospectively analyzed 267 cycles of chemotherapy. The incidence of FN was used as the objective variable. As predictive factors, we analyzed age, international germ cell consensus classification (IGCCC), laboratory data at the start of chemotherapy in each cycle, length of the largest metastatic lesion, number of cycles, and prophylactic use of granulocyte colony stimulating factor (G-CSF). We finally analyzed 267 cycles in 78 patients. The median age was 36 years (15-64). There was a total of 267 cycles. FN occurred in 40 cycles (15%) in 31 patients (40%). The first cycle was accompanied by a significantly higher FN than the subsequent cycles (p < 0.001). The univariate analysis identified age ≧36 years (p = 0.001), creatinine clearance (CCr) <70 (p < 0.001), serum albumin <3.3 (p = 0.002), maximum tumor diameter ≧60 mm (p = 0.036), and first cycle as significant risk factors. The multivariate analysis identified age, CCr, and first cycle as independent predictive factors of FN development. We identified older age, renal dysfunction, and first cycle of chemotherapy as predictive factors for FN. No statistically significant difference was shown in the usage of prophylactic G-CSF. Special attention should be given to FN in patients with high-risk factors.

The art of sustainable wellbeing: an eastern philosophy approach to cultivating happiness

ABSTRACT Our jobs are now less secure and more reliant on technology, where knowledge is shared in real time irrespective of the location or time. Although we now have more flexibility in how we work, our work-life boundaries are getting affected, thus becoming blurred. When boundaries are porous, it creates role conflicts and promotes insecurity and tension in one’s life. The existing subjective well-being (SWB) research focuses on observing, measuring, and controlling what is external to the individual and showing ‘what happens’ to SWB when subjective and objective variables are at play. By drawing on Eastern philosophical and spiritual approaches, this paper provides insights into the true nature of our perceived situational awareness of the present moment. It suggests that with techniques such as mindfulness and insight (Vipassana), it is possible to get a deeper understanding of the root causes and effects of consciousness and shape our perceived worldviews and subjective well-being.

A 2-tuple fuzzy linguistic model for recommending health care services grounded on aspect-based sentiment analysis

Evaluating the quality of health care systems usually entails the examination of objective variables (waiting time, patients per doctor, etc.). Nonetheless, other subjective variables can be used thanks to new Internet tools. Many online medical services let users convey their opinions on the offered services. That information is an interesting tool to measure the quality of these services. It describes sentiments about different features using a wide range of adjectives, adverbs and nouns, many times, completely different for each feature. Therefore, it is interesting to assess every feature individually using different scales. This study presents an application of a multi-granular fuzzy linguistic model to represent the opinions about the different features of health care systems with the aim of recommending hospitals according to the user preferences. To test this approach, the opinions from real hospitals have been assessed using different user preferences. The obtained results outperform other state-of-the-art approaches.

Analysis of cell populations in the normal rhesus macaque (Macaca mulatta) lower intestinal tract and diagnostic thresholds for chronic enterocolitis.

Rhesus macaques (Macaca mulatta) are used extensively in biomedical research, often with a focus on the gastrointestinal tract, and yet a full characterization of their normal resident intestinal cell populations has not been published. In addition, chronic enterocolitis (CE), also known as idiopathic chronic diarrhea, affects up to 25% of colony-housed rhesus macaques, often requiring euthanasia for welfare concerns and severely limiting their value as a breeding animal or research subject. We aimed to characterize subjective and objective variables in sections of the ileum, cecum, colon, and rectum in 16 healthy rhesus macaques and compare these results with a cohort of 37 animals euthanized for CE to produce relevant diagnostic thresholds and to improve case definitions for future studies. We found neutrophils to be an infrequent but expected component of the large intestinal leukocyte population. Animals with CE had significantly increased total leukocyte populations between crypts in the cecum, colon, and rectum; variable increases in specific cell populations across all levels of the distal intestinal tract; and significantly increased intraepithelial CD3+ T cells in the colon and rectum. Concentrations of enteroendocrine cells, enterochromaffin cells, and intestinal mast cells were not significantly different between healthy and affected individuals. This study characterizes individual leukocyte populations in the rhesus macaque lower intestinal tract, is the first to evaluate rhesus macaque intestinal mast cells, and provides key diagnostic thresholds for evaluating animals with potential CE.

Outdoor thermal perception in the semi-arid climate of Constantine, Algeria: A field survey during the post-COVID-19

The purpose of the paper was to assess pedestrians' thermal perception, in the semi-arid climate of Constantine, Algeria, with particular emphasis on the protocols implemented in public spaces during the post-COVID-19. Three outdoor public spaces were selected in August 2021 to conduct a field study involving 254 respondents, randomly assigned. The adopted approach combined objective and subjective assessment, as well as numerical simulations using ENVI-met. Accordingly, microclimate monitoring and a questionnaire survey were carried out simultaneously from 7 a.m. to 7 p.m. in each study site. A strong association was found between the combined microclimate parameters (objective variables) and thermal sensation of the surveyors with (R2 = 0.74). Besides, Kruskal-Wallis H test revealed that the subjective thermal sensation was significantly influenced (p-value <0.05) by thermal history and purpose of visit (subjective variables). Most interviewees preferred ‘move to shade’ measure as a remedial behavior to reduce their thermal discomfort. Further, a neutral temperature of 22.7 °C PET was obtained by a linear regression between the Mean Thermal Sensation Votes (MTSV) and Physiological Equivalent Temperature (PET), the comfort range was estimated between 18.6 °C ≤ PET≤ 26.8 °C during summer. Regarding the COVID-19 pandemic effects, the Chi-square test suggests that the frequency of pedestrian visits was statistically independent of the imposed pandemic measures. However, the planned activities were affected by social distancing and the use of face masks increases pedestrians' thermal discomfort. Overall, the study highlights the significance of environmental and non-environmental factors to improve outdoor thermal comfort, and ensure human well-being.

The Polysomnographical Meaning of Changed Sleep Quality-A Study of Treatment with Reduced Time in Bed.

Reports of poor sleep are widespread, but their link with objective sleep (polysomnography-PSG) is weak in cross-sectional studies. In contrast, the purpose of this study was to investigate the association between changes in subjective and objective sleep variables using data from a study of the reduction in time in bed (TIB). One sleep recording was carried out at baseline and one at treatment week 5 (end of treatment) (N = 34). The Karolinska Sleep Quality Index improved and was correlated with improvement in sleep efficiency (r = 0.41, p < 0.05) and reduction in TIB (r = -0.47, p < 0.01) and sleep latency (r = 0.36, p < 0.05). The restorative sleep index showed similar results. Improvements in the insomnia severity index (ISI) essentially lacked correlations with changes in the PSG variables. It was suggested that the latter may be due to the ISI representing a week of subjective sleep experience, of which a single PSG night may not be representative. It was concluded that changes in the subjective ratings of sleep are relatively well associated with changes in the PSG-based sleep continuity variables when both describe the same sleep.

Long-term hard X-ray variability properties of Swift-BAT blazars

ABSTRACT We present results from the first dedicated study in the time domain of the hard X-ray variability behaviour of blazars on long time-scales based on ∼13 yr of continuous hard X-ray data in the 14–195 keV band. We use monthly binned data from the recent 157-month Swift-BAT (Burst Alert Telescope) catalogue to characterize the hard X-ray variability of 127 blazars and search for potential differences between the variability of BL Lacertae objects (BL Lacs) and flat-spectrum radio quasars (FSRQs). A significant portion of the blazars in the sample (∼37 per cent) do not show statistically significant hard X-ray variability on monthly time-scales, which is deeply at odds with previous studies that show that blazars are highly variable in the X-rays and other energy bands on a wide range of time-scales. We also find that, on average, the FSRQs and BL Lacs for which we do detect variability exhibit similar flux variability; this suggests that the variability in these FSRQs is not necessarily driven by variations in the source function of scattered external radiation arriving from extended regions, and that it is instead possibly driven by processes that lead to variations in particle injection. In addition, only five blazars in our sample show significant spectral variability in the long-term light curves. For three blazars, we find that a power law that changes slope on monthly time-scales is sufficient to characterize the variable hard X-ray spectrum, suggesting that, at least for some bright blazars, the long-term spectra in the hard X-rays may be described in a relatively simple fashion.

Registers in Oral Speech of Mowindahako: Metafunctions and The Way of Life of The Tolakinese

Abstract. This research is oriented toward the role of registers in mowindahako custom. This qualitative research is focused on the lexis and speech of mowindahako from a Sociolinguistics perspective. The data collected and carried out through direct observations during customs be held and interviews with the participants in open-ended question perspective. The data were analyzed using BUL/Sharing Elements technique, coding according to the research object variables and thematic analysis, and ethnoscience analysis. The results showed that its register is divided into 2 types of expression, both are verbal expression in high formalistic poetic diglossia (wua-wua ndulura) and non-lingual (non-verbal: the things, body movements of participants in the mombesara process, and 4 traditional participants). Register used acts as a code or signal for the participants in the interaction process. This is an abstract and concrete realization of metafunction whose discourse provides an understanding of the purpose and meaning of mowindahako which has a philosophical function. This function is seen through the ideational, participants' ideational, logical, and experiential concepts al concept is based on the discourse in the mombesara process and the interpersonal traditional participants. Mowindahako's register construction ultimately showed the world what Tolakinese society is and how they are by through complex verbal and non-verbal metafunctions and stratification, axiological cognition, and their mindset and outlook on life. Keywords: Register, Diglossia, Metafunctions, Mowindahako, Mombesara

In silico simulations and molecular descriptors to predict in vitro transactivation potencies of Baikal seal estrogen receptors by environmental contaminants

Baikal seals (Pusa sibirica) are vulnerable to high levels of organic pollutants. Here, we evaluated the transactivation potencies of bisphenols (BPs) and hydroxylated polychlorinated biphenyls (OH-PCBs) via the Baikal seal estrogen receptor α and β (bsERα and bsERβ) using in vitro and in silico approaches. In vitro reporter gene assays showed that most BPs and OH-PCBs exhibited estrogenic activity with bsER sub-type-specific potency. Among the BPs tested, bisphenol AF showed the lowest EC50 for both bsERs. 4′-OH-CB50 and 4′-OH-CB30 showed the lowest EC50 among OH-PCBs tested for bsERα and bsERβ, respectively. 4-((4-Isopropoxyphenyl)-sulfonyl)phenol, 4′-OH-CB72, and 4′-OH-CB121 showed weak bsERα-specific transactivation. Only 4-OH-CB107 did not affect both bsERs. In silico docking simulations revealed the binding affinities of these chemicals to bsERs and partially explained the in vitro results. Using the in silico simulations and molecular descriptors as explanatory variables and the in vitro results as objective variables, the quantitative structure-activity relationship (QSAR) models constructed for classification and regression accurately separated bsER-active compounds from non-active compounds and predicted the in vitro bsERα- and bsERβ-transactivation potencies, respectively. The QSAR models also suggested that chemical polarity, van der Waals surface area, bridging atom structure, position of the phenolic-OH group, and ligand interactions with key residues of the ligand binding pocket are critical variables to account for the bsER transactivation potency of the test compounds. We also succeeded in constructing computational models for predicting in vitro transactivation potencies of mouse ERs in the same manner, demonstrating the applicability of our approach independent of species-specific responses.

Impact of nausea/vomiting on EQ-5D-5L utility scores in patients taking iron preparations for heavy menstrual bleeding or anemia

BackgroundThe purpose of this study was to establish an estimating equation to predict the 5-level EQ-5D version (EQ-5D-5L) utility score in patients taking iron preparations for heavy menstrual bleeding (HMB) or anemia and to evaluate whether the presence of nausea or vomiting was a significant predictor of EQ-5D-5L-based quality of life.MethodsA cross-sectional survey was conducted to collect EQ-5D-5L utility scores and other patient reported outcomes from 385 patients taking iron preparations for HMB or anemia who were selected from the disease patient panel. Using the utility scores as objective variables, explanatory variable candidates were selected considering correlations, multicollinearity, and clinical validity. Predicting models were constructed using regression-based models (linear model, generalized linear model (GLM), Tobit model). Stepwise regression method was applied for selecting statistically significant (p < 0.05) predictors. Goodness-of-fit of models were assessed by mean absolute error and mean squared error (MSE).ResultsThe EQ-5D-5L utility scores (mean ± standard deviation) of 96 patients with nausea/vomiting and 289 patients without nausea/vomiting were 0.67 ± 0.16 and 0.84 ± 0.14, respectively (p < 0.001). The presence of nausea/vomiting was shown to be the most significant factor reducing the utility score in the statistical models using the explanatory variable candidates selected in the study. As the results of the goodness-of-fit test, GLM with the smallest MSE was selected to establish the estimating equation.ConclusionThe estimating equation to predict the EQ-5D-5L utility scores in patients taking iron preparations for HMB or anemia was established. The presence of nausea/vomiting was found to be a factor significantly reducing utility scores, with a decrement of the value estimated to be -0.117.Trial registrationUMIN000045700 (http://www.umin.ac.jp/ctr/). Registered on October 11, 2021.

Development of artificial intelligence prognostic model for surgically resected non-small cell lung cancer

There are great expectations for artificial intelligence (AI) in medicine. We aimed to develop an AI prognostic model for surgically resected non-small cell lung cancer (NSCLC). This study enrolled 1049 patients with pathological stage I–IIIA surgically resected NSCLC at Kyushu University. We set 17 clinicopathological factors and 30 preoperative and 22 postoperative blood test results as explanatory variables. Disease-free survival (DFS), overall survival (OS), and cancer-specific survival (CSS) were set as objective variables. The eXtreme Gradient Boosting (XGBoost) was used as the machine learning algorithm. The median age was 69 (23–89) years, and 605 patients (57.7%) were male. The numbers of patients with pathological stage IA, IB, IIA, IIB, and IIIA were 553 (52.7%), 223 (21.4%), 100 (9.5%), 55 (5.3%), and 118 (11.2%), respectively. The 5-year DFS, OS, and CSS rates were 71.0%, 82.8%, and 88.7%, respectively. Our AI prognostic model showed that the areas under the curve of the receiver operating characteristic curves of DFS, OS, and CSS at 5 years were 0.890, 0.926, and 0.960, respectively. The AI prognostic model using XGBoost showed good prediction accuracy and provided accurate predictive probability of postoperative prognosis of NSCLC.

Emergency-department initiated buprenorphine: Impact on quality of life

IntroductionEmergency department (ED)-initiated medications for opioid use disorder (MOUD) have emerged as an acute care strategy against the opioid epidemic. When initiated in the outpatient setting, MOUD has been demonstrated to have a positive impact on patients’ quality of life (QoL). It is unclear how engagement in ED-initiated MOUD, a novel initiation setting and unique patient cohort, might impact QoL. We sought to describe QoL variables reported by patients engaged in ED-initiated MOUD. MethodsA retrospective observational study of an ED-initiated MOUD program was performed, inclusive of enrollments from July 2019 through February 2022. Participants were interviewed at intake, 3-months, and 6-months, during which QoL indices were measured via Government Performance and Results Act (GPRA) variables. Descriptive statistics and Pearson's Chi-Square analyses were utilized to assess the data. ResultsOf 315 participants, majority were white (78.4 %), male (64.4 %), between the ages of 25–44 (74.6 %), and heavily burdened by lack of insurance, homelessness, and unemployment. One hundred forty participants (44.4 % eligible) completed 3-month follow-up and 90 (28.5 %) completed 6-month follow-up. There were no significant demographic differences amongst respondents at 3- and 6-months as compared to intake. Objective QoL variables significantly improved at 3- and 6-months as compared to intake (p < 0.01). Subjective QoL variables also demonstrated significant improvement at follow-up (p < 0.05). ConclusionED patients with OUD, eligible for MOUD, may face a number of social and interpersonal variables which heavily impact QoL. ED-initiated MOUD may positively impact subsequent QoL when measured over time.

Feature Selection Method for Machine Tool Wear Diagnosis

We propose an algorithm for estimating the wear condition of tools. We have previously developed a method for predicting machining dimensions by learning features of waveform shapes such as torque during machining as explanatory variables and measured machining dimensions as objective variables. In this method, the features do not fully explain the machining dimensions because including data other than the machining operation such as tool change. In this paper, we propose a method to improve explanatory power and prediction accuracy by selecting subsequences from the machining waveform that are highly related to machining dimensions as explanatory variables. The effectiveness of the proposed method was confirmed through an evaluation using data of machining product part.

Prediction of Impact Information of Composites Laminates Considering the Practicality

Recently, carbon fiber reinforced plastics (CFRP) have been used in various applications, including aircraft. Because they are vulnerable to out-of-plane loads, internal and externaldamage occurs when foreign objects impact them. Internal damage that can affect residual properties is difficult to find and judge from the outside without special devices, which arehighly costed and are sometimes difficult to conduct in some locations. In this study, surface contour information was obtained from impact tests on CFRP laminates, and thepredictability of compression after impact (CAI)strength was investigated using a conventional single-task random forest model, and a decision tree-based multi-task learning model with other objective variables related to impact tests. The models estimated CAI strength with around 75% R2, and the conventional single-task learning model showed the highest value. The importance of each model indicated that factors that contribute to impact-related objective variables (impactor shape, delamination area, and delamination length) and those to CAI strength do not have a strong relationship.

Development of a Real-Time Trust/Distrust Metric Using Interactive Hybrid Cognitive Task Analysis

While there is increased interest in how trust spreads in Human Autonomy Teams (HATs), most trust measurements are subjective and do not examine real-time changes in trust. To develop a trust metric that consists of objective variables influenced by trust/distrust manipulations, we conducted an Interactive hybrid Cognitive Task Analysis (IhCTA) for a Remotely Piloted Aerial System (RPAS) HAT. The IhCTA adapted parts of the hybrid Cognitive Task Analysis (hCTA) framework. In this paper, we present the four steps of the IhCTA approach, including 1) generating a scenario task overview, 2) generating teammate-specific event flow diagrams, 3) identifying interactions and interdependencies impacted by trust/distrust manipulations, and 4) processing RPAS variables based on the IhCTA to create a metric. We demonstrate the application of the metric through a case study that examines how the influence of specific interactions on team state changes before and after the spread of distrust.

Insights into the Luminescence Quantum Yields of Cyclometalated Iridium(III) Complexes: A Density Functional Theory and Machine Learning Approach.

Cyclometalated iridium(III) complexes have been used in various optical materials, including organic light-emitting diodes (OLEDs) and photocatalysts, and a deeper understanding and prediction of their luminescence quantum yields (LQYs) greatly aid in accelerating material design. In this study, we integrated density functional theory (DFT) calculations with machine learning (ML) techniques to extract factors controlling LQY. Although a substantial data set of Ir(III) complexes and their LQYs is indispensable for constructing accurate ML models to predict LQYs, generating this type of data set is challenging due to the complexities associated with ab initio calculations of LQYs. To address this issue, we investigated the nonradiative decay process of nine Ir(III) complexes emitting blue to green, each exhibiting varying experimental LQYs, by using DFT calculations. For all nine complexes, the quenching process was induced by the rotation of the single bond in one of the ligands, which converted the six-coordinate structure to the five-coordinate structure. Since the decay mechanism was common for the nine Ir(III) complexes, parameters correlated with LQYs could be used as objective variables instead of LQYs. Based on this idea, we collected a data set featuring Ir(III) complexes and the energy differences between their six- and five-coordinate triplet structures, which correlated with LQYs. We also constructed ML models using the calculated LQYs as the objective variables with the parameters from the ground-state calculations as explanatory variables. The analyses of the constructed model revealed that the LUMO energy of the ligand made the most significant negative contribution to LQY. This suggests that the potential energy surface of the metal-to-ligand charge transfer (MLCT) excited state, which stabilizes the six-coordinate structure, is reduced by decreasing the energy of the unoccupied orbitals.

Development of freight trip generation model using observed and unobserved information of supply chain characteristics for a sustainable urban transformation

Supply Chain Characteristics (SCC) drive the city logistics to control the economic activities that support urban life and transformation. The dynamics of freight trip activity and SCC in city logistics are less understood by city planners, disrupting the prediction of urban Freight Trip Generation (FTG) models. To develop robust urban FTG models, the present study introduces the concept of estimating the freight trip activity using observed and unobserved (subjective) information of SCC for sustainable urban transport movement. Traditionally, the objective variable excludes the unobserved information of SCC while developing the FTG model; this gap can be addressed by incorporating subjective variables to measure both observed and unobserved information of SCC. A unique framework was designed by a combination of objective and subjective variables through Exploratory Factor Analysis (EFA) and Structural Equation Modelling (SEM) to estimate the freight trip activity. An Establishment Based Freight Survey (EBFS) collected from an Indian smart city (1793 samples) comprising various SCC was used to test the developed framework. Deployed EFA can identify the subjective variables using latent constructs to explain the observed and unobserved information in the SCC. Then, sequential execution of SEM with hypothesis path structure for estimating the freight trip activity. The direct, indirect, and total effects of the FTG model revealed added advantage of causal inter-relationship of urban freight trip activity and SCC between intermediate and pure receiver establishment. The developed FTG models using observed and unobserved information of SCC predicted freight trip activity with an accuracy of 57% for intermediate and 63% for pure receiver establishment. The effect of SSC on freight trip activity aids in creating sustainable urban freight transportation that could be an agile, responsive, and flexible adaptive system for the global market demand.

Parents’ desire to change phone use: Associations with objective smartphone use and feelings about problematic use and distraction

We examined objective smartphone use (via a mobile sensing application) and self-reported desire to change phone use among a sample of 268 U.S. parents of infants. Using the Transtheoretical Stages of Change model as a conceptual foundation, we contextualized their attitudes and behaviors and explored how phone use and desire to change relate to perceptions of distraction and problematic phone use around their child. Latent profile analysis of parents' precontemplation, contemplation, and action scores revealed two classes—precontemplators (15%) and contemplators (85%). Contemplators—those considering or desiring change—showed more bedtime phone use and general social networking than precontemplors; however, there were no significant differences between groups on other objective use measures (e.g., total daily duration of phone use, phone use around child, etc.). Contemplators also showed greater perceptions of problematic use around their child and parenting distraction. Moreover, parents’ problematic use and distraction were predictive of higher contemplation scores, even after controlling for demographic and objective phone use variables. Taken together, these results suggest that perceptions of phone use as problematic may be more important than actual phone habits, especially total phone use duration, for desire to change. Suggestions for future research and intervention are provided.

Impact of Pulmonary Rehabilitation on Recuperation of Moderate-to-Severe Coronavirus Disease 2019 Patients in Western India

Background: Coronavirus disease 2019 (COVID-19) virus has caused widespread Acute Respiratory Disease globally since 2020. Patients with evidence of lower respiratory illness either clinically or radiologically had moderate-to-severe illness. COVID respiratory and nonrespiratory symptoms (psychological and cognitive) noticed after 4–8 weeks of primary disease were called long COVID syndrome. Survivors of moderate-to-severe disease had a poor quality of life. The main objective of this retrospective study was to assess the role of outpatient pulmonary rehabilitation (PR) done in moderate-severe COVID-19 survivors who had symptoms after 4–8 weeks at Shaivam Lung Rehabilitation Centre, Ahmedabad. Methods: We analyzed the impact of PR on 30 patients' post-COVID-19 who were willing to participate during the ongoing pandemic. It was an outpatient 6–8 weeks of program designed to target respiratory and general muscle training, relaxation technique, nutritional counseling, occupational and psychological support. Patients were tested with of combination of self-assessment quality of life scale (adapted from short form 36 questionnaire), muscle training, dyspnea scale, and physical assessment. The standard objective assessment included oxygenation index (SpO2/FiO2 ratio), 6 min walk distance (6 MWD), Modified Medical Research Council (MMRC) score, manual muscle testing (MMT) along with pulmonary function testing. All these subjective and objective variables were tested pre- and post-PR program to assess the impact on defined parameters. Results: From December 2020 to March 2022, we studied the impact of PR on 30 out of 55 patients fitting into the inclusion criteria. Significant benefit was noted in subjective Short Form 36 (SF 36) score and objective (6 MWD, MMRC, oxygenation, MMT) quality of life post-PR program ( P &lt; 0.001). Improvement in spirometry was not statistically significant, indicating structural chronicity of COVID pulmonary fibrosis. Conclusion: PR is safe, effective, and feasible on an outpatient basis in COVID-19 survivors of illness with poor quality of life. Further research is required to prove its widespread benefit in such patients.

Relationship of maximum walking speed with peak oxygen uptake and anaerobic threshold in male patients with heart failure

This retrospective observational study aimed to examine the relationships of maximum walking speed (MWS) with peak oxygen uptake (peak VO2) and anaerobic threshold (AT) obtained by cardiopulmonary exercise testing (CPX) in patients with heart failure. The study participants were 104 consecutive men aged ≥ 20 years who had been hospitalized or had undergone outpatient care at our hospital for heart failure between February 2019 and January 2023. MWS was measured in a 5-m section with a 1-m run-up before and after the course. Multivariable analysis was used to examine the association between MWS and peak VO2 and AT by CPX. The Pearson correlation coefficient showed that MWS was positively correlated with percent-predicted peak VO2 and percent-predicted AT (r = 0.463, p < 0.001; and r = 0.485, p < 0.001, respectively). In the multiple linear regression analysis employing percent-predicted peak VO2 and percent-predicted AT as the objective variables, only MWS demonstrated a significant positive correlation (standardized β: 0.471, p < 0.001 and 0.362, p < 0.001, respectively). Multiple logistic regression analyses, using an 80% cutoff in percent-predicted peak VO2 and AT, revealed that only MWS was identified as a significant factor in both cases (odds ratio [OR]: 1.239, 95% confidence interval [CI]: 1.071–1.432, p = 0.004 and OR: 1.469, 95% CI: 1.194–1.807, p < 0.001, respectively). MWS was correlated with peak VO2 and AT in male patients with heart failure. The MWS measurement as a screening test for exercise tolerance may provide a simple means of estimating peak VO2 and AT in heart failure patients.