Category: Nevin Manimala

Int J Soc Psychiatry. 2022 Jun 2:207640221099416. doi: 10.1177/00207640221099416. Online ahead of print.

ABSTRACT

BACKGROUND: Although technologies (including information, e-learning, and communication) have been daily employed by University students in the last years, the COVID-19 pandemic has led to a considerable increase in their use. Technostress is a modern term referring to levels of stress caused by the prolonged exposure to technology.

AIM: The aim of this study is to assess the technostress and related anxiety and depression among Paraguayan University students, describing their sociodemographic characteristics and relevant associations.

METHODS: A cross-sectional and descriptive study has been conducted. Participants were recruited through an Internet-based survey. Technostress, anxiety, and depression have been assessed with the Technostress Questionnaire (TechQ), the Generalized Anxiety Disorder-7 (GAD-7) questionnaire, and the Patient Health Questionnaire-2 (PHQ-2), respectively.

RESULTS: A total of 378 participants were included, 74.1% of whom were women. According to the TechQ scores, 47.4% of the participants reported a low/moderate level of technostress whereas 5.2% showed severe scores. About 58.5% of participants reported a GAD-7 score ⩾10, meeting diagnostic criteria for generalized anxiety. About 60.3% scored ⩾3 at the PHQ-2 reporting significant levels of depression. Technostress has been significantly associated with levels of anxiety (p < .001) as well as depression (p < .001).

CONCLUSION: Our results suggest further research regarding the implications of technostress on the well-being of University students. Specific measures aimed to improve students’ coping with the challenges of technology and technostress should be promoted.

PMID:35652309 | DOI:10.1177/00207640221099416

Adv Clin Exp Med. 2022 Jun 2. doi: 10.17219/acem/149988. Online ahead of print.

ABSTRACT

BACKGROUND: Air pollution has a negative influence on neurological and psychiatric disorders. However, findings concerning the impact of air pollution on depression remain inconclusive. A deeper insight into these associations is warranted.

OBJECTIVES: To evaluate the impact of long-term exposure to air pollution on the incidence of depression among residents of 13 counties in the Lower Silesia region of Poland.

MATERIAL AND METHODS: We used data on cases of depression from the National Health Fund (Narodowy Fundusz Zdrowia – NFZ) from 13 counties of Lower Silesia between January 1, 2010, and December 31, 2015. Patients with a confirmed diagnosis of depression were included. Data on air pollution levels were extracted from the Chief Inspectorate of Environmental Protection (Główny Inspektorat Ochrony Środowiska – GIOŚ), and demographic data were extracted from Statistics Poland (Główny Urząd Statystyczny – GUS).

RESULTS: The percentage of people diagnosed with depression over the 6-year study period depended on the group of counties homogeneous in terms of air pollution exposure (p < 0.001). We showed statistically significant correlations between different depression diagnoses and exposure to air pollutants. Elevated concentration of airborne fine particles with a diameter less than 2.5 μm (PM2.5) and carbon monoxide (CO), and low benzo(a)pyrene (BaP), sulfur dioxide (SO2) and cadmium (Cd) levels were independent risk factors for major depressive episodes with psychotic symptoms (F32.3). There was a significant negative correlation between ozone (O3) levels and depression incidence.

CONCLUSIONS: Regions with heavy air pollution had a higher incidence of depression. There is a significant association between the exposure to air pollutants and different depression diagnoses.

PMID:35652299 | DOI:10.17219/acem/149988

Turk Neurosurg. 2022 Mar 25. doi: 10.5137/1019-5149.JTN.38252-22.3. Online ahead of print.

ABSTRACT

AIM: The present study aimed to evaluate the effects of favipiravir (FVP) on cell viability and cytotoxicity in human degenerated primary intervertebral disc (IVD) tissue cell cultures treated with FVP. Furthermore, the protein expressions of hypoxia-inducible factor 1 alpha (HIF-1α), nuclear factor-kappa-b (NF-κB), and interleukin-1 beta (IL-1β) were also examined.

MATERIAL AND METHODS: Untreated cell cultures served as the control group, named group 1. Cell cultures treated with FVP served as the study group, named group 2. Pharmacomolecular analyses were performed in all groups at 0, 24, 48, and 72 hours (h). Obtained data were evaluated statistically.

RESULTS: Cell proliferation was suppressed in the FVP-treated samples compared to the control group samples at 24 and 72 h, and this was statistically significant (P 0.05). Decreased or increased protein expression levels of HIF-1 NF-κB, and IL-1β in FVP-treated samples may be an indication of suppression in anabolic events as well as proliferation in IVD cultures. FVP administration showed that AF/NP cells in a culture medium may induce a strong inflammatory response to FVP. This strong inflammatory response is likely to cause slowed proliferation. It may also be a trigger for many catabolic events. NF-B expression increased within the first 24 h and then decreased rapidly. Based on the data obtained, it may be suggested that the rapidly increasing NF-kB may have stimulated the expression of many antiproliferative genes.

CONCLUSION: The suppression of IL-1β and NF-kB protein expressions in IVD cells treated with FVP is important in the treatment of IVD degeneration (IDD). If the protein expression of HIF-1α could be increased along with the suppression of IL-1β and NF-kB, FVP would perhaps be a promising pharmacological agent in the treatment of IDD.

PMID:35652184 | DOI:10.5137/1019-5149.JTN.38252-22.3

Turk Neurosurg. 2022 Apr 6. doi: 10.5137/1019-5149.JTN.37703-22.2. Online ahead of print.

ABSTRACT

AIM: Chronic subdural hematoma (CSDH) is one of the most common forms of intracranial bleeding encountered in neurosurgical practice. Recurrence of CSDH is a significant problem, and recurrence rates can be as high as 33%. In the last 20 years, the insertion of postoperative drains into the cavity has become a common strategy owing to its reduction of the risk of recurrence. This study aimed to analyze and compare the factors that influence the recurrence of CSDH among patients treated with subdural non-suction-assisted passive drainage, subgaleal suction-assisted active drainage, and without drainage.

MATERIAL AND METHODS: We retrospectively evaluated 87 surgical patients with a diagnosis of CSDH treated between 2007 and 2018 using patient records from the neurosurgery archive of our faculty. The patients were divided into three groups: drain-free group (group A), subdural passive drainage group (group B), and subgaleal active drainage group (group C). Recurrence was defined as an increase in hematoma volume on imaging and persistence of the patient’s symptoms.

RESULTS: Patients with double-membrane CSDH exhibited higher recurrence rates (p = 0.043) and those with low-density CSDH exhibited lower recurrence rates (p = 0.015) compared to the other patients. No relationship was found between the number of burr holes made and CSDH recurrence (p = 0.177). Group C showed the lowest recurrence rate (13.3%), but the differences between groups were not statistically significant.

CONCLUSION: Hematoma density, membrane type, postoperative Glasgow Outcome Scale scores, and postoperative drainage time were found to be statistically significant predictors of recurrence. Burr-hole craniotomy with subgaleal active drainage is a safe and effective method for preventing CSDH recurrence and carries a reduced risk of parenchymal injury.

PMID:35652185 | DOI:10.5137/1019-5149.JTN.37703-22.2

Turk Neurosurg. 2022 Feb 25. doi: 10.5137/1019-5149.JTN.36452-21.3. Online ahead of print.

ABSTRACT

AIM: The role of adjuvant radiotherapy after surgery for atypical meningiomas remains controversial. The present study was designed to investigate the recurrence rate of atypical meningiomas after surgery (with or without adjuvant radiotherapy) and determine which factors were related with recurrence.

MATERIAL AND METHODS: Data obtained from 83 patients who underwent surgery and histopathologically diagnosed with atypical meningioma at a single institution between January 2009 and June 2019 were retrospectively reviewed. Then, the patients were divided into two groups: the surgery-only (n = 43) and surgery + adjuvant radiotherapy (n = 40) groups.

RESULTS: The mean age of the patients was 53.5 ± 14.6 years. Among them, 51 (61.4%) were female and 32 (38.6%) were male. The recurrence rates were 30.2% (n = 13) in the surgery-only group and 17.5% (n = 7) in the surgery + adjuvant radiotherapy group. A statistically significant decrease in the recurrence rate was observed after adjuvant radiotherapy application (p = 0.046). Moreover, adjuvant radiotherapy significantly increased progression-free survival (p = 0.042). Peritumoral edema, sinus invasion, brain invasion, subtotal tumor resection, and complications were significant predictors of tumor recurrence, and the main risk factors for the recurrence of atypical meningiomas were brain invasion (p = 0.019) and subtotal tumor resection (p = 0.006). Progression-free survival and overall survival of the study group were 45.50 ± 27.56 and 56.69 ± 28.17 months, respectively. The parameters examined in the study, except for tumor recurrence, did not show a statistically significant influence on overall survival.

CONCLUSION: This study revealed that the important prognostic factors for tumor recurrence are subtotal tumor resection and brain invasion. Moreover, adjuvant radiotherapy in addition to surgical resection reduces the recurrence rate of atypical meningiomas and improves progression-free survival of the patients. However, adjuvant radiotherapy did not show a significant influence on overall survival.

PMID:35652183 | DOI:10.5137/1019-5149.JTN.36452-21.3

Genet Epidemiol. 2022 Jun 1. doi: 10.1002/gepi.22459. Online ahead of print.

ABSTRACT

As research in genetics has advanced, some findings have been unexpected or shown to be inconsistent between studies or datasets. The reasons these inconsistencies arise are complex. Results from genetic studies can be affected by various factors including statistical power, linkage disequilibrium, quality control, confounding and selection bias, as well as real differences from interactions and effect modifiers, which may be informative about the mechanisms of traits and disease. Statistical artefacts can manifest as differences between results but they can also conceal underlying differences, which implies that their critical examination is important for understanding the underpinnings of traits. In this review, we examine these factors and outline how they can be identified and conceptualised with structural causal models. We explain the consequences they have on genetic estimates, such as genetic associations, polygenic scores, family- and genome-wide heritability, and describe methods to address them to aid in the estimation of true effects of genetic variation. Clarifying these factors can help researchers anticipate when results are likely to diverge and aid researchers’ understanding of causal relationships between genes and complex traits.

PMID:35652173 | DOI:10.1002/gepi.22459

CNS Neurosci Ther. 2022 Jun 1. doi: 10.1111/cns.13873. Online ahead of print.

ABSTRACT

Perioperative neurocognitive disorders (NCDs) refer to neurocognitive abnormalities detected during the perioperative periods, including preexisting cognitive impairment, preoperative delirium, delirium occurring up to 7 days after surgery, delayed neurocognitive recovery, and postoperative NCD. The Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) is the golden standard for diagnosing perioperative NCDs. Given the impracticality of using the DSM-5 by non-psychiatric practitioners, many diagnostic tools have been developed and validated for different clinical scenarios. The etiology of perioperative NCDs is multifactorial and includes predisposing and precipitating factors. Identifying these risk factors is conducive to preoperative risk stratification and perioperative risk reduction. Prevention for perioperative NCDs should include avoiding possible contributors and implementing nonpharmacologic and pharmacological interventions. The former generally includes avoiding benzodiazepines, anticholinergics, prolonged liquid fasting, deep anesthesia, cerebral oxygen desaturation, and intraoperative hypothermia. Nonpharmacologic measures include preoperative cognitive prehabilitation, comprehensive geriatric assessment, implementing fast-track surgery, combined use of regional block, and sleep promotion. Pharmacological measures including dexmedetomidine, nonsteroidal anti-inflammatory drugs, and acetaminophen are found to have beneficial effects. Nonpharmacological treatments are the first-line measures for established perioperative NCDs. Pharmacological treatments are still limited to severely agitated or distressed patients.

PMID:35652170 | DOI:10.1111/cns.13873

Radiol Artif Intell. 2022 Apr 20;4(3):e210115. doi: 10.1148/ryai.210115. eCollection 2022 May.

ABSTRACT

PURPOSE: To present a method that automatically detects, subtypes, and locates acute or subacute intracranial hemorrhage (ICH) on noncontrast CT (NCCT) head scans; generates detection confidence scores to identify high-confidence data subsets with higher accuracy; and improves radiology worklist prioritization. Such scores may enable clinicians to better use artificial intelligence (AI) tools.

MATERIALS AND METHODS: This retrospective study included 46 057 studies from seven “internal” centers for development (training, architecture selection, hyperparameter tuning, and operating-point calibration; n = 25 946) and evaluation (n = 2947) and three “external” centers for calibration (n = 400) and evaluation (n = 16764). Internal centers contributed developmental data, whereas external centers did not. Deep neural networks predicted the presence of ICH and subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and/or epidural hemorrhage) and segmentations per case. Two ICH confidence scores are discussed: a calibrated classifier entropy score and a Dempster-Shafer score. Evaluation was completed by using receiver operating characteristic curve analysis and report turnaround time (RTAT) modeling on the evaluation set and on confidence score-defined subsets using bootstrapping.

RESULTS: The areas under the receiver operating characteristic curve for ICH were 0.97 (0.97, 0.98) and 0.95 (0.94, 0.95) on internal and external center data, respectively. On 80% of the data stratified by calibrated classifier and Dempster-Shafer scores, the system improved the Youden indexes, increasing them from 0.84 to 0.93 (calibrated classifier) and from 0.84 to 0.92 (Dempster-Shafer) for internal centers and increasing them from 0.78 to 0.88 (calibrated classifier) and from 0.78 to 0.89 (Dempster-Shafer) for external centers (P < .001). Models estimated shorter RTAT for AI-prioritized worklists with confidence measures than for AI-prioritized worklists without confidence measures, shortening RTAT by 27% (calibrated classifier) and 27% (Dempster-Shafer) for internal centers and shortening RTAT by 25% (calibrated classifier) and 27% (Dempster-Shafer) for external centers (P < .001).

CONCLUSION: AI that provided statistical confidence measures for ICH detection on NCCT scans reliably detected and subtyped hemorrhages, identified high-confidence predictions, and improved worklist prioritization in simulation.Keywords: CT, Head/Neck, Hemorrhage, Convolutional Neural Network (CNN) Supplemental material is available for this article. © RSNA, 2022.

PMID:35652116 | PMC:PMC9152881 | DOI:10.1148/ryai.210115

Radiol Artif Intell. 2022 May 4;4(3):e210064. doi: 10.1148/ryai.210064. eCollection 2022 May.

ABSTRACT

PURPOSE: To assess generalizability of published deep learning (DL) algorithms for radiologic diagnosis.

MATERIALS AND METHODS: In this systematic review, the PubMed database was searched for peer-reviewed studies of DL algorithms for image-based radiologic diagnosis that included external validation, published from January 1, 2015, through April 1, 2021. Studies using nonimaging features or incorporating non-DL methods for feature extraction or classification were excluded. Two reviewers independently evaluated studies for inclusion, and any discrepancies were resolved by consensus. Internal and external performance measures and pertinent study characteristics were extracted, and relationships among these data were examined using nonparametric statistics.

RESULTS: Eighty-three studies reporting 86 algorithms were included. The vast majority (70 of 86, 81%) reported at least some decrease in external performance compared with internal performance, with nearly half (42 of 86, 49%) reporting at least a modest decrease (≥0.05 on the unit scale) and nearly a quarter (21 of 86, 24%) reporting a substantial decrease (≥0.10 on the unit scale). No study characteristics were found to be associated with the difference between internal and external performance.

CONCLUSION: Among published external validation studies of DL algorithms for image-based radiologic diagnosis, the vast majority demonstrated diminished algorithm performance on the external dataset, with some reporting a substantial performance decrease.Keywords: Meta-Analysis, Computer Applications-Detection/Diagnosis, Neural Networks, Computer Applications-General (Informatics), Epidemiology, Technology Assessment, Diagnosis, Informatics Supplemental material is available for this article. © RSNA, 2022.

PMID:35652114 | PMC:PMC9152694 | DOI:10.1148/ryai.210064

Cancer Inform. 2022 May 26;21:11769351221100754. doi: 10.1177/11769351221100754. eCollection 2022.

ABSTRACT

The creation of patient-derived cancer organoids represents a key advance in preclinical modeling and has recently been applied to a variety of human solid tumor types. However, conventional methods used to assess in vivo tumor tissue treatment response are poorly suited for the evaluation of cancer organoids because they are time-intensive and involve tissue destruction. To address this issue, we established a suite of 3-dimensional patient-derived glioma organoids, treated them with chemoradiotherapy, stained organoids with non-toxic cell dyes, and imaged them using a rapid laser scanning confocal microscopy method termed “Apex Imaging.” We then developed and tested a fragmentation algorithm to quantify heterogeneity in the topography of the organoids as a potential surrogate marker of viability. This algorithm, SSDquant, provides a 3-dimensional visual representation of the organoid surface and a numerical measurement of the sum-squared distance (SSD) from the derived mass center of the organoid. We tested whether SSD scores correlate with traditional immunohistochemistry-derived cell viability markers (cellularity and cleaved caspase 3 expression) and observed statistically significant associations between them using linear regression analysis. Our work describes a quantitative, non-invasive approach for the serial measurement of patient-derived cancer organoid viability, thus opening new avenues for the application of these models to studies of cancer biology and therapy.

PMID:35652106 | PMC:PMC9150230 | DOI:10.1177/11769351221100754