Category: Nevin Manimala

PLoS One. 2021 Dec 31;16(12):e0261954. doi: 10.1371/journal.pone.0261954. eCollection 2021.

ABSTRACT

Cybersecurity affects us all in our daily lives. New knowledge on best practices, new vulnerabilities, and timely fixes for cybersecurity issues is growing super-linearly, and is spread across numerous, heterogeneous sources. Because of that, community contribution-based, question and answer sites have become clearinghouses for cybersecurity-related inquiries, as they have for many other topics. Historically, Stack Overflow has been the most popular platform for different kinds of technical questions, including for cybersecurity. That has been changing, however, with the advent of Security Stack Exchange, a site specifically designed for cybersecurity-related questions and answers. More recently, some cybersecurity-related subreddits of Reddit, have become hubs for cybersecurity-related questions and discussions. The availability of multiple overlapping communities has created a complex terrain to navigate for someone looking for an answer to a cybersecurity question. In this paper, we investigate how and why people choose among three prominent, overlapping, question and answer communities, for their cybersecurity knowledge needs. We aggregated data of several consecutive years of cybersecurity-related questions from Stack Overflow, Security Stack Exchange, and Reddit, and performed statistical, linguistic, and longitudinal analysis. To triangulate the results, we also conducted user surveys. We found that the user behavior across those three communities is different, in most cases. Likewise, cybersecurity-related questions asked on the three sites are different, more technical on Security Stack Exchange and Stack Overflow, and more subjective and personal on Reddit. Moreover, there appears to have been a differentiation of the communities along the same lines, accompanied by overall popularity trends suggestive of Stack Overflow’s decline and Security Stack Exchange’s rise within the cybersecurity community. Reddit is addressing the more subjective, discussion type needs of the lay community, and is growing rapidly.

PMID:34972166 | DOI:10.1371/journal.pone.0261954

PLoS One. 2021 Dec 31;16(12):e0261433. doi: 10.1371/journal.pone.0261433. eCollection 2021.

ABSTRACT

Diagnostic tests for hearing impairment not only determines the presence (or absence) of hearing loss, but also evaluates its degree and type, and provides physicians with essential data for future treatment and rehabilitation. Therefore, accurately measuring hearing loss conditions is very important for proper patient understanding and treatment. In current-day practice, to quantify the level of hearing loss, physicians exploit specialized test scores such as the pure-tone audiometry (PTA) thresholds and speech discrimination scores (SDS) as quantitative metrics in examining a patient’s auditory function. However, given that these metrics can be easily affected by various human factors, which includes intentional (or accidental) patient intervention, there are needs to cross validate the accuracy of each metric. By understanding a “normal” relationship between the SDS and PTA, physicians can reveal the need for re-testing, additional testing in different dimensions, and also potential malingering cases. For this purpose, in this work, we propose a prediction model for estimating the SDS of a patient by using PTA thresholds via a Random Forest-based machine learning approach to overcome the limitations of the conventional statistical (or even manual) methods. For designing and evaluating the Random Forest-based prediction model, we collected a large-scale dataset from 12,697 subjects, and report a SDS level prediction accuracy of 95.05% and 96.64% for the left and right ears, respectively. We also present comparisons with other widely-used machine learning algorithms (e.g., Support Vector Machine, Multi-layer Perceptron) to show the effectiveness of our proposed Random Forest-based approach. Results obtained from this study provides implications and potential feasibility in providing a practically-applicable screening tool for identifying patient-intended malingering in hearing loss-related tests.

PMID:34972151 | DOI:10.1371/journal.pone.0261433

PLoS One. 2021 Dec 31;16(12):e0261850. doi: 10.1371/journal.pone.0261850. eCollection 2021.

ABSTRACT

OBJECTIVE: Identify risk factors for poor pain outcomes six months after primary knee replacement surgery.

METHODS: Observational cohort study on patients receiving primary knee replacement from the UK Clinical Practice Research Datalink, Hospital Episode Statistics and Patient Reported Outcomes. A wide range of variables routinely collected in primary and secondary care were identified as potential predictors of worsening or only minor improvement in pain, based on the Oxford Knee Score pain subscale. Results are presented as relative risk ratios and adjusted risk differences (ARD) by fitting a generalized linear model with a binomial error structure and log link function.

RESULTS: Information was available for 4,750 patients from 2009 to 2016, with a mean age of 69, of whom 56.1% were female. 10.4% of patients had poor pain outcomes. The strongest effects were seen for pre-operative factors: mild knee pain symptoms at the time of surgery (ARD 18.2% (95% Confidence Interval 13.6, 22.8), smoking 12.0% (95% CI:7.3, 16.6), living in the most deprived areas 5.6% (95% CI:2.3, 9.0) and obesity class II 6.3% (95% CI:3.0, 9.7). Important risk factors with more moderate effects included a history of previous knee arthroscopy surgery 4.6% (95% CI:2.5, 6.6), and use of opioids 3.4% (95% CI:1.4, 5.3) within three months after surgery. Those patients with worsening pain state change had more complications by 3 months (11.8% among those in a worse pain state vs. 2.7% with the same pain state).

CONCLUSIONS: We quantified the relative importance of individual risk factors including mild pre-operative pain, smoking, deprivation, obesity and opioid use in terms of the absolute proportions of patients achieving poor pain outcomes. These findings will support development of interventions to reduce the numbers of patients who have poor pain outcomes.

PMID:34972159 | DOI:10.1371/journal.pone.0261850

PLoS One. 2021 Dec 31;16(12):e0261473. doi: 10.1371/journal.pone.0261473. eCollection 2021.

ABSTRACT

Chemotherapy-induced peripheral neuropathy (CIPN) is a dose-limiting adverse reaction in cancer patients treated with several cytotoxic anticancer agents including paclitaxel. Duloxetine, an antidepressant known as a serotonin-noradrenalin reuptake inhibitor, is the only agent that has moderate evidence for the use to treat painful CIPN. The present retrospective cohort study aimed to analyze risk factors for paclitaxel-induced peripheral neuropathy (PIPN), and investigate ongoing prescription drug use for PIPN in Japan. Female breast and gynecologic cancer patients who underwent paclitaxel-based chemotherapy at a single center in Japan between January 2016 and December 2019 were enrolled in this study. Patients’ information obtained from electronic medical records were statistically analyzed to test possible risk factors on PIPN diagnosis. Patients’ age, total paclitaxel dose, the history of female hormone-related diseases, hypertension and body mass index (BMI), but not additional platinum agents, were significantly associated with increased PIPN diagnosis. Drugs prescribed for PIPN included duloxetine, pregabalin, mecobalamin and Goshajinkigan, a polyherbal medicine, regardless of poor evidence for their effectiveness against CIPN, and were greatly different between breast and gynecologic cancer patients diagnosed with PIPN at the departments of Surgery and Gynecology, respectively. Thus, older age, greater total paclitaxel dose, the history of estrogen-related diseases, hypertension and BMI are considered risk factors for PIPN in paclitaxel-based chemotherapy of female cancer patients. It appears an urgent need to establish a guideline of evidence-based pharmacotherapy for PIPN.

PMID:34972132 | DOI:10.1371/journal.pone.0261473

PLoS One. 2021 Dec 31;16(12):e0261471. doi: 10.1371/journal.pone.0261471. eCollection 2021.

ABSTRACT

BACKGROUND: The prevalence of diabetes and the use of electronic health (eHealth) are increasing. Lifestyle changes in a positive direction may reduce morbidity and mortality in patients with diabetes. The main objective of this study was to test the association between lifestyle changes based on online information seeking and discussing the information with a doctor.

METHODS: In this cross-sectional study we used e-mail survey data from 1250 members of The Norwegian Diabetes Association, collected in 2018. Included in the analyses were 847 men and women aged 18 to 89 years diagnosed with diabetes and who reported use of eHealth within the previous year. We used descriptive statistics to estimate lifestyle changes based on information from the internet. Logistic regressions were used to estimate the associations between lifestyle changes after online information seeking and discussing the information with a doctor. Analyses were adjusted for gender, age, education, and self-rated health.

RESULTS: Lifestyle changes accomplished after online information seeking was reported by 46.9% (397/847) of the participants. The odds of changing lifestyle were more than doubled for those who had discussed information from the internet with a doctor (odds ratio 2.54, confidence interval 1.90-3.40). The odds of lifestyle changes were lower in the age groups 30-39 years and 60 years and over, compared to those aged 18-29 years (the reference group). Lifestyle changes were not associated with gender, education, or self-rated health.

CONCLUSIONS: Our findings indicate that health-care professionals can play an important role in lifestyle changes additional to health-advice found on the internet. This study underlines the importance of easily accessible high-quality online information, as well as the importance of making room for discussing lifestyle in the clinical encounter.

PMID:34972136 | DOI:10.1371/journal.pone.0261471

PLoS One. 2021 Dec 31;16(12):e0261182. doi: 10.1371/journal.pone.0261182. eCollection 2021.

ABSTRACT

BACKGROUND: Contextual effects from the physical and social environment contribute to inequitable protection for a large proportion of road users, especially in low- and middle-income countries like South Africa where distorted urban planning and socio-spatial disparities from the apartheid era prevail.

OBJECTIVES: This paper examines the differentiated risk of road traffic crashes and injuries to vulnerable road users in South Africa, including pedestrians, females and users of some modes of public transport, in relation to characteristics of the crashes that proxy a range of contextual influences such as rurality and socio-economic deprivation.

METHODS: The study is based on a descriptive analysis of 33 659 fatal crashes that occurred in South Africa over a three-year period from 2016-2018. Measures of simple proportion, population-based fatality rate, “impact factor” and crash severity are compared between disaggregated groups using Chi-Square analysis, with the Cramer’s V statistic used to assess effect size.

RESULTS AND SIGNIFICANCE: Key findings show a higher pedestrian risk in relation to public transport vehicles and area-level influences such as the nature of roads or extent of urbanity; higher passenger risk in relation to public transport vehicles and rurality; and higher risk for female road users in relation to public transport vehicles. The findings have implications for prioritising a range of deprivation-related structural effects. In addition, we present a “User-System-Context” conceptual framework that allows for a holistic approach to addressing vulnerability in the transport system. The findings provide an important avenue for addressing the persistently large burden of road traffic crashes and injuries in the country.

PMID:34972108 | DOI:10.1371/journal.pone.0261182

PLoS One. 2021 Dec 31;16(12):e0261383. doi: 10.1371/journal.pone.0261383. eCollection 2021.

ABSTRACT

OBJECTIVES: Traffic speed is important to public health as it is a major contributory factor to collision risk and casualty severity. 20mph (32km/h) speed limit interventions are an increasingly common approach to address this transport and health challenge, but a more developed evidence base is needed to understand their effects. This study describes the changes in traffic speed and traffic volume in the City of Edinburgh, pre- and 12 months post-implementation of phased city-wide 20mph speed limits from 2016-2018.

METHODS: The City of Edinburgh Council collected speed and volume data across one full week (24 hours a day) pre- and post-20mph speed limits for 66 streets. The pre- and post-speed limit intervention data were compared using measures of central tendency, dispersion, and basic t-tests. The changes were assessed at different aggregations and evaluated for statistical significance (alpha = 0.05). A mixed effects model was used to model speed reduction, in the presence of key variables such as baseline traffic speed and time of day.

RESULTS: City-wide, a statistically significant reduction in mean speed of 1.34mph (95% CI 0.95 to 1.72) was observed at 12 months post-implementation, representing a 5.7% reduction. Reductions in speed were observed throughout the day and across the week, and larger reductions in speed were observed on roads with higher initial speeds. Mean 7-day volume of traffic was found to be lower by 86 vehicles (95% CI: -112 to 286) representing a reduction of 2.4% across the city of Edinburgh (p = 0.39) but with the direction of effect uncertain.

CONCLUSIONS: The implementation of the city-wide 20mph speed limit intervention was associated with meaningful reductions in traffic speeds but not volume. The reduction observed in road traffic speed may act as a mechanism to lessen the frequency and severity of collisions and casualties, increase road safety, and improve liveability.

PMID:34972123 | DOI:10.1371/journal.pone.0261383

PLoS One. 2021 Dec 31;16(12):e0257530. doi: 10.1371/journal.pone.0257530. eCollection 2021.

ABSTRACT

To what extent can the strength of a local urban community impact neighborhood safety? We construct measures of community vibrancy based on a unique dataset of block party permit approvals from the City of Philadelphia. Our first measure captures the overall volume of block party events in a neighborhood whereas our second measure captures differences in the type (regular versus spontaneous) of block party activities. We use both regression modeling and propensity score matching to control for the economic, demographic and land use characteristics of the surrounding neighborhood when examining the relationship between crime and our two measures of community vibrancy. We conduct our analysis on aggregate levels of crime and community vibrancy from 2006 to 2015 as well as the trends in community vibrancy and crime over this time period. We find that neighborhoods with a higher number of block parties have a significantly higher crime rate, while those holding a greater proportion of spontaneous block party events have a significantly lower crime rate. We also find that neighborhoods which have an increase in the proportion of spontaneous block parties over time are significantly more likely to have a decreasing trend in total crime incidence over that same time period.

PMID:34972104 | DOI:10.1371/journal.pone.0257530

J Neurosurg. 2021 Dec 31:1-8. doi: 10.3171/2021.10.JNS211608. Online ahead of print.

ABSTRACT

OBJECTIVE: Placement of a subdural drain reduces recurrence and death after evacuation of chronic subdural hematoma (CSDH), but little is known about optimal drainage duration. In the present national trial, the authors investigated the effect of drainage duration on recurrence and death.

METHODS: In a randomized controlled trial involving all neurosurgical departments in Denmark, patients treated with single burr hole evacuation of CSDH were randomly assigned to 24 hours or 48 hours of postoperative passive subdural drainage. Follow-up duration was 90 days, and the primary study outcome was recurrent hematoma requiring reoperation. Secondary outcome was death. In addition, complications and length of hospital stay were recorded and analyzed.

RESULTS: Of the 420 included patients, 212 were assigned 24-hour drainage and 208 were assigned 48-hour drainage. The recurrence rate was 14% in the 24-hour group and 13% in the 48-hour group. Four patients died in the 24-hour group, and 8 patients died in the 48-hour group; this difference was not statistically significant. The ORs (95% CIs) for recurrence and mortality (48 hours vs 24 hours) were 0.94 (0.53-1.66) and 2.07 (0.64-7.85), respectively, in the intention-to-treat analysis. The ORs (95% CIs) for recurrence and mortality per 1-hour increase in drainage time were 1.0005 (0.9770-1.0244) and 1.0046 (0.9564-1.0554), respectively, in the as-treated sensitivity analysis that used the observed drainage times instead of the preassigned treatment groups. The rates of surgical and drain-related complications, postoperative infections, and thromboembolic events were not different between groups. The mean ± SD postoperative length of hospital stay was 7.4 ± 4.3 days for patients who received 24-hour drainage versus 8.4 ± 4.9 days for those who received 48-hour drainage (p = 0.14). The mean ± SD postoperative length of stay in the neurosurgical department was significantly shorter for the 24-hour group (2 ± 0.9 days vs 2.8 ± 1.6 days, p < 0.001).

CONCLUSIONS: No significant differences in the rates of recurrent hematoma or death during 90-day follow-up were identified between the two groups that randomly received either 24- or 48-hour passive subdural drainage after burr hole evacuation of CSDH.

PMID:34972091 | DOI:10.3171/2021.10.JNS211608

PLoS One. 2021 Dec 31;16(12):e0260051. doi: 10.1371/journal.pone.0260051. eCollection 2021.

ABSTRACT

OBJECTIVES: To model the risk of COVID-19 mortality in British care homes conditional on the community level risk.

METHODS: A two stage modeling process (“doubly latent”) which includes a Besag York Mollie model (BYM) and a Log Gaussian Cox Process. The BYM is adopted so as to estimate the community level risks. These are incorporated in the Log Gaussian Cox Process to estimate the impact of these risks on that in care homes.

RESULTS: For an increase in the risk at the community level, the number of COVID-19 related deaths in the associated care home would be increased by exp (0.833), 2. This is based on a simulated dataset. In the context of COVID-19 related deaths, this study has illustrated the estimation of the risk to care homes in the presence of background community risk. This approach will be useful in facilitating the identification of the most vulnerable care homes and in predicting risk to new care homes.

CONCLUSIONS: The modeling of two latent processes have been shown to be successfully facilitated by the use of the BYM and Log Gaussian Cox Process Models. Community COVID-19 risks impact on that of the care homes embedded in these communities.

PMID:34972103 | DOI:10.1371/journal.pone.0260051