Tag: pubmed

J Pain. 2023 Jul 17:S1526-5900(23)00475-3. doi: 10.1016/j.jpain.2023.07.009. Online ahead of print.

ABSTRACT

This study investigated for the first time the effects of individual and combined application of three learning techniques (verbal suggestions, classical conditioning, and observational learning) on placebo analgesia and extinction. Healthy participants (N = 206) were assigned to eight different groups in which they were taught through either a verbal suggestion, a conditioning paradigm, a video observing someone, or any combination thereof that a placebo device (inactive TENS) was capable of alleviating heat pain, whereas one group did not (control). Placebo analgesia was quantified as the within-group difference in experienced pain when the placebo device was (sham) ‘activated’ or ‘inactivated’ during equal pain stimuli, and compared between groups. Placebo analgesia was induced in groups with two or three learning techniques. Significantly stronger placebo analgesia was induced in the combination of all three learning techniques as compared to the individual learning techniques or control condition, underlining the additional contribution of 3 combined techniques. Extinction did not differ between groups. Furthermore, pain expectancies, but not state anxiety or trust, mediated placebo analgesia. Our findings emphasize the added value of combining 3 learning techniques to optimally shape expectancies that lead to placebo analgesia, which can be used in experimental and clinical settings. PERSPECTIVE: This unique experimental study compared the individual versus combined effects of three important ways of learning (verbal suggestions, classical conditioning, and observational learning) on expectation-based pain relief. The findings indicate that placebo effects occurring in clinical practice could be optimally strengthened if healthcare providers apply these techniques in combination.

PMID:37468025 | DOI:10.1016/j.jpain.2023.07.009

Sci Total Environ. 2023 Jul 17:165600. doi: 10.1016/j.scitotenv.2023.165600. Online ahead of print.

ABSTRACT

Armed conflicts have detrimental impacts on the environment, including land systems. The prevailing understanding of the relation between Land Use/Land Cover (LULC) and armed conflict fails to fully recognize the complexity of their dynamics – a shortcoming that could undermine food security and sustainable land/water resources management in conflict settings. The Syrian portion of the transboundary Orontes River Basin (ORB) has been a site of violent conflict since 2013. Correspondingly, the Lebanese and Turkish portions of the ORB have seen large influxes of refugees. A major challenge in any geoscientific investigation in this region, specifically the Syrian portion, is the unavailability of directly-measured “ground truth” data. To circumvent this problem, we develop a novel methodology that combines remote sensing products, machine learning techniques and quasi-experimental statistical analysis to better understand LULC changes in the ORB between 2004 and 2022. Through analysis of the resulting annual LULC maps, we can draw several quantitative conclusions. Cropland areas decreased by 21-24 % in Syria’s conflict hotspot zones after 2013, whereas a 3.4-fold increase was detected in Lebanon. The development of refugee settlements was also tracked in Lebanon and on the Syrian/Turkish borders, revealing different LULC patterns that depend on settlement dynamics. The results highlight the importance of understanding the heterogenous spatio-temporal LULC changes in conflict-affected and refugee-hosting countries. The developed methodology is a flexible, cloud-based approach that can be applied to wide variety of LULC investigations related to conflict, policy and climate.

PMID:37467974 | DOI:10.1016/j.scitotenv.2023.165600

Biomed J. 2023 Jul 17:100632. doi: 10.1016/j.bj.2023.100632. Online ahead of print.

ABSTRACT

BACKGROUND: Biomarker dynamics in different time-courses might be the primary reason why a static measurement of a single biomarker cannot accurately predict sepsis outcomes. Therefore, we conducted this prospective hospital-based cohort study to simultaneously evaluate the performance of several conventional and novel biomarkers of sepsis in predicting sepsis-associated mortality on different days of illness among patients with suspected sepsis.

METHODS: We evaluated the performance of 15 novel biomarkers including angiopoietin-2, pentraxin 3, sTREM-1, ICAM-1, VCAM-1, sCD14 and 163, E-selectin, P-selectin, TNF-alpha, interferon-gamma, CD64, IL-6, 8, and 10, along with few conventional markers for predicting sepsis-associated mortality. Patients were grouped into quartiles according to the number of days since symptom onset. Receiver operating characteristic curve (ROC) analysis was used to evaluate the biomarker performance.

RESULTS: From 2014 to 2017, 1,483 patients were enrolled, of which 78% fulfilled the systemic inflammatory response syndrome criteria, 62% fulfilled the sepsis-3 criteria, 32% had septic shock, and 3.3% developed sepsis-associated mortality. IL-6, pentraxin 3, sCD163, and the blood gas profile demonstrated better performance in the early days of illness, both before and after adjusting for potential confounders (adjusted area under ROC curve [AUROC]:0.81-0.88). Notably, the Sequential Organ Failure Assessment (SOFA) score was relatively consistent throughout the course of illness (adjusted AUROC:0.70-0.91).

CONCLUSION: IL-6, pentraxin 3, sCD163, and the blood gas profile showed excellent predictive accuracy in the early days of illness. The SOFA score was consistently predictive of sepsis-associated mortality throughout the course of illness, with an acceptable performance.

PMID:37467969 | DOI:10.1016/j.bj.2023.100632

World Neurosurg. 2023 Jul 17:S1878-8750(23)00968-3. doi: 10.1016/j.wneu.2023.07.037. Online ahead of print.

ABSTRACT

OBJECTIVE: The choice between external ventricular drain (EVD) and intraparenchymal monitor (IPM) for managing intracranial pressure (ICP) in moderate-to-severe traumatic brain injury (msTBI) patients remains controversial. This study aimed to investigate factors associated with receiving EVD versus IPM and to compare outcomes and clinical management between EVD and IPM patients.

METHODS: Adult msTBI patients at two similar academic institutions were identified. Logistic regression was performed to identify factors associated with receiving EVD versus IPM (Model 1) and to compare EVD versus IPM in relation to patient outcomes after controlling for potential confounders (Model 2), through odds ratios (OR) and 95% confidence intervals (CI).

RESULTS: Of 521 patients, 167 (32.1%) had EVD and 354 (67.9%) had IPM. Mean age, sex, and Injury Severity Score were comparable between groups. Epidural hemorrhage (EDH) (OR 0.43, 95%CI 0.21-0.85), greater midline shift (OR 0.90, 95%CI 0.82-0.98) and the hospital with higher volume (OR 0.14, 95%CI 0.09-0.22) were independently associated with lower odds of receiving an EVD whereas patients needing a craniectomy were more likely to receive an EVD (OR 2.04, 95%CI 1.12-3.73). EVD patients received more intense medical treatment requiring hyperosmolar therapy compared to IPM patients (64.1% vs. 40.1%). No statistically significant differences were found in patient outcomes.

CONCLUSIONS: While EDH, greater midline shift, and hospital with larger patient volume were associated with receiving an IPM, the need for a craniectomy was associated with receiving an EVD. EVD patients received different clinical management than IPM patients with no significant differences in patient outcomes.

PMID:37467955 | DOI:10.1016/j.wneu.2023.07.037

World Neurosurg. 2023 Jul 17:S1878-8750(23)00973-7. doi: 10.1016/j.wneu.2023.07.045. Online ahead of print.

ABSTRACT

The incidence of ischemic stroke in young adults (18-45 years old) is increasing gradually. However, performing nutritional assessment in stroke patients is often challenging due to the lack of an accepted standard for nutritional assessment. 260 young stroke patients were recruited in this study and 144 cases in the good prognosis group and 116 cases in the poor prognosis group were scored according to the modified Rankin scale (mRS) 90 days after treatment. The National Institutes of Health Stroke Scale (NIHSS) was performed on admission and discharge of patients. Serum interleukin 6 (IL-6) and high-sensitivity C-reactive protein (hs-CRP) were detected at patient presentation. The Prognostic Nutritional Index (PNI) was assessed on admission. Calculation formula of PNI score: serum albumin (g/L) + 5× total lymphocyte count (10⁹/L). The PNI at admission of young stroke patients with poor prognosis was higher than that of those with good prognosis. PNI at admission was significantly negatively correlated with NIHSS at discharge and mRS score after 90 days in young stroke patients. PNI at admission was also significantly negatively correlated with serum levels of high-sensitivity C-reactive protein and IL-6 at admission. PNI has a statistically predictive value for the 90-day prognosis of young stroke patients.

PMID:37467954 | DOI:10.1016/j.wneu.2023.07.045

Contemp Clin Trials. 2023 Jul 17:107301. doi: 10.1016/j.cct.2023.107301. Online ahead of print.

ABSTRACT

In recent decades, there has been growing interest in leveraging external data information for clinical development as it improves the efficiency of the design and inference of clinical trials when utilized properly and more importantly, alleviates potential ethical and recruitment challenges. When it is of interest to augment the concurrent study’s control arm using external control data, the potential outcome heterogeneity across data sources, also known as prior-data conflict, should be accounted for. In addition, in the outcome modeling, inclusion of prognostic covariates that may have impact on the outcome can avoid efficiency loss or potential bias. In this paper, we propose a Bayesian hierarchical modeling strategy incorporating covariate-adjusted meta-analytic predictive approach (cMAP) and also introduce a propensity score (PS) based sequential procedure that integrates the cMAP. In the simulation study, the proposed methods are found to have advantages in the estimation, power, and type I error control over the standard methods such as PS matching alone and hierarchical modeling that ignores the covariates. An illustrative example is used to illustrate the procedure.

PMID:37467950 | DOI:10.1016/j.cct.2023.107301

Contemp Clin Trials. 2023 Jul 17:107300. doi: 10.1016/j.cct.2023.107300. Online ahead of print.

ABSTRACT

To accelerate clinical development, seamless 2/3 adaptive design is an attractive strategy to combine phase 2 dose selection with phase 3 confirmatory objectives. As the regulatory requirement for dose optimization in oncology drugs shifted from maximum tolerated dose to maximum effective dose, it’s important to gather more data on multiple candidate doses to inform dose selection. A phase 3 dose may be selected based on phase 2 results and carried forward in phase 3 study. Data obtained from both phases will be combined in the final analysis. In many disease settings biomarker endpoints are utilized for dose selection as they are correlated with the clinical efficacy endpoints. As discussed in Li et al. (2015), the combined analysis may cause type I error inflation due to the correlation and dose selection. Sidák adjustment has been proposed to control the overall type I error by adjusting p-values in phase 2 when performing the combined p-value test. However, this adjustment could be overly conservative as it does not consider the underlying correlations among doses/endpoints. We propose an alternative approach utilizing biomarker rank-based ordered test statistics which takes the rank order of the selected dose and the correlation into consideration. If the correlation is unknown, we propose a rank-based Dunnett adjustment, which includes the traditional Dunnett adjustment as a special case. We show that the proposed method controls the overall type I error, and leads to a uniformly higher power than Sidák adjustment and the traditional Dunnett adjustment under all potential correlation scenarios discussed.

PMID:37467949 | DOI:10.1016/j.cct.2023.107300

Environ Res. 2023 Jul 17:116686. doi: 10.1016/j.envres.2023.116686. Online ahead of print.

ABSTRACT

During the mining of rare earth minerals, the application of neodymium-containing manures, and the treatment of spent neodymium iron boron magnet, the generation of ammonia wastewater containing neodymium is increasing. Thus, the effects of neodymium (Nd(III)) on anaerobic ammonium oxidation (Anammox) were investigated from the aspects of performance, kinetics, statistics, microbial community and sludge morphology, and the recovery strategy of EDTA-2Na wash was discussed. The nitrogen removal efficiency of the Anammox reactor decreased significantly and eventually collapsed at the Nd(III) dosing levels of 20 and 40 mg L^-1, respectively. And the toxicity of Nd(III) to AnAOB was determined by the amount internalized into the cells. The EDTA-2Na wash successfully increased the total nitrogen removal rate (TNRR) of Nd(III)-inhibited Anammox to 41.60% of its initial value within 30 days, and the modified Boltzmann model accurately simulated this recovery process. The transient and extended effects of Nd(III), self-recovery, and EDTA-2Na wash on Anammox were effectively assessed using a one-sample t-test. 16S rRNA gene sequencing indicated that Nd(III) remarkably decreased the relative abundance of Planctomycetes and Candidatus Brocadia. The scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) revealed crystal-like neodymium particles on the surface of Anammox sludge. The above-mentioned results demonstrate that the concentration of Nd(III) should be below the toxicity threshold (20 mg L^-1) when treating ammonia wastewater containing neodymium by Anammox, and also emphasize the importance of an appropriate recovery strategy.

PMID:37467943 | DOI:10.1016/j.envres.2023.116686

Environ Pollut. 2023 Jul 17:122217. doi: 10.1016/j.envpol.2023.122217. Online ahead of print.

ABSTRACT

Air pollution exposure may affect child weight gain, but observational studies provide inconsistent evidence. Residential relocation can be leveraged as a natural experiment by studying changes in health outcomes after a sudden change in exposure within an individual. We aimed to evaluate whether changes in air pollution exposure due to residential relocation are associated with changes in body mass index (BMI) in children and adolescents in a natural experiment study. This population-based study included children and adolescents, between 2 and 17 years, who moved during 2011-2018 and were registered in the primary healthcare in Catalonia, Spain (N = 46,644). Outdoor air pollutants (nitrogen dioxides (NO₂), particulate matter <10 μm (PM₁₀) and <2.5 μm (PM_2.5)) were estimated at residential census tract level before and after relocation; tertile cut-offs were used to define changes in exposure. Routinely measured weight and height were used to calculate age-sex-specific BMI z-scores. A minimum of 180 days after moving was considered to observe zBMI changes according to changes in exposure using linear fixed effects regression. The majority of participants (60-67% depending on the pollutant) moved to areas with similar levels of air pollution, 15-49% to less polluted, and 14-31% to more polluted areas. Moving to areas with more air pollution was associated with zBMI increases for all air pollutants (β NO₂ = 0.10(95%CI 0.09; 0.12), β PM_2.5 0.06(0.04; 0.07), β PM₁₀ 0.08(0.06; 0.10)). Moving to similar air pollution areas was associated with decreases in zBMI for all pollutants. No associations were found for those moving to less polluted areas. Associations with moving to more polluted areas were stronger in preschool- and primary school-ages. Associations did not differ by area deprivation strata. This large, natural experiment study suggests that increases in outdoor air pollution may be associated with child weight gain, supporting ongoing efforts to lower air pollution levels.

PMID:37467916 | DOI:10.1016/j.envpol.2023.122217

Cognition. 2023 Jul 17;239:105564. doi: 10.1016/j.cognition.2023.105564. Online ahead of print.

ABSTRACT

Our brains are capable of discriminating similar inputs (pattern separation) and rapidly generalizing across inputs (statistical learning). Are these two processes dissociable in behavior? Here, we asked whether cognitive aging affects them in a differential or parallel manner. Older and younger adults were tested on their ability to discriminate between similar trisyllabic words and to extract trisyllabic words embedded in a continuous speech stream. Older adults demonstrated intact statistical learning on an implicit, reaction time-based measure and an explicit, familiarity-based measure of learning. However, they performed poorly in discriminating similar items presented in isolation, both for episodically-encoded items and for statistically-learned regularities. These results indicate that pattern separation and statistical learning are dissociable and differentially affected by aging. The acquisition of implicit representations of statistical regularities operates robustly into old age, whereas pattern separation influences the expression of statistical learning with high representational fidelity and is subject to age-related decline.

PMID:37467624 | DOI:10.1016/j.cognition.2023.105564