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351 results for “Case control studies”

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dryad32/100

Data from: Risk factors for bloodborne viral hepatitis in healthcare workers of Pakistan: a population based case–control study

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publicJul 2014View details →

dryad28/100

Data from: Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation

Background Prostate cancer (PC) is the most frequently diagnosed cancer in North American men. Pathologists are in critical need of accurate biomarkers to characterize PC, particularly to confirm the presence of intraductal carcinoma of the prostate (IDC-P), an aggressive histopathological variant for which therapeutic options are now available. Our aim was to identify IDC-P with Raman micro-spectroscopy and machine learning technology following a protocol suitable for routine clinical histopathology laboratories. Methods and findings We used Raman micro-spectroscopy to differentiate IDC-P from PC, as well as PC and IDC-P from benign tissue on formalin-fixed paraffin-embedded first-line radical prostatectomy specimens (embedded in tissue microarrays, TMAs) from 483 patients treated in three Canadian institutions between 1993 and 2013. The main measures were the presence or absence of IDC-P and of PC, regardless of the clinical outcomes. Most of the 483 patients were pT2 stage (44–69%), and pT3a (22–49%) was more frequent than pT3b (9–12%). After approval of the construction of the TMAs by local ethics review board, the diagnostic accuracy study was approved by the Centre hospitalier de l'Université de Montréal (CHUM) ethics review board. Briefly, two consecutive sections of each TMA block were cut. The first section was transferred onto a glass slide to perform immunohistochemistry with H&E counterstaining for cell identification. The second section was placed on an aluminum slide, dewaxed, and then used to acquire an average of 7 Raman spectra per specimen (between 4 and 24 Raman spectra, 4 acquisitions / TMA core). Raman spectra of each cell type were then analyzed to retrieve tissue-specific molecular information and to generate classification models using machine learning technology. Models were trained and cross-validated using data from one institution. Accuracy, sensitivity and specificity were respectively of 87 ± 5%, 86 ± 6% and 89 ± 8% to differentiate PC from benign tissue, and of 95 ± 2%, 96 ± 4% and 94 ± 2% respectively to differentiate IDC-P from PC. The trained models were then tested on data from two independent institutions, reaching accuracies, sensitivities and specificities of 84 and 86%, 84 and 87%, and 81 and 82%, respectively to diagnose PC, and of 85 and 91%, 85 and 88%, and 86 and 93% respectively for the identification of IDC-P. IDC-P could further be differentiated from high-grade prostatic intraepithelial neoplasia (HGPIN), a pre-malignant intraductal proliferation which can be mistaken as IDC-P, with accuracies, sensitivities and specificities >95% in both training and testing cohorts. As we used stringent criteria to diagnose IDC-P, the main limitation of our study is the exclusion of borderline, difficult to classify lesions from our datasets. Conclusions In this study, we developed classification models for the analysis of Raman micro-spectroscopy data to differentiate IDC-P, PC and benign tissue, including HGPIN. Raman micro-spectroscopy could be a next-generation histopathological technique used to reinforce the identification of high-risk PC patients and lead to more precise diagnosis of IDC-P.

opencc-zeroDec 2019View details →

dryad28/100

Data from: Osteosarcopenia in reproductive-aged women with polycystic ovary syndrome: a multicenter case-control study

Context: Osteosarcopenia (loss of skeletal muscle and bone mass and/or function usually associated with aging) shares pathophysiological mechanisms with polycystic ovary syndrome (PCOS). However, the relationship between osteosarcopenia and PCOS remains unclear. Objective: We evaluated skeletal muscle index% (SMI%=[appendicular muscle mass/weight {kg}]×100) and bone mineral density (BMD) in PCOS <a name="_Hlk36059693">(hyperandrogenism+oligoamenorrhea), and contrasted these musculoskeletal markers against 3 reproductive phenotypes: (1) HA (hyperandrogenism+eumenorrhea); (2) OA (normoandrogenic+oligoamenorrhea) and, (3) controls (normoandrogenic+eumenorrhea). </a>Endocrine predictors of SMI% and BMD were evaluated across groups. Design, Setting, Participants: Multicenter case-control study of 203 women (18–48y) in New York State. <a name="_Hlk36062204">Results:</a> PCOS group exhibited reduced SMI% (<a name="_Hlk35952064">mean [95%CI]; 26.2% [25.1,27.3] vs. 28.8% [27.7,29.8])</a>, lower-extremity SMI% (57.6% [56.7,60.0] vs. 62.5% [60.3,64.6]), and BMD (1.11 [1.08,1.14] vs. 1.17 [1.14,1.20] g/cm2) compared to controls. PCOS group also had decreased upper (0.72 [0.70,0.74] vs. 0.73 [0.71,0.76] g/cm2) and lower (1.13 [1.10,1.16] vs. 1.15 [1.12,1.18] g/cm2) limb BMD compared to HA. Matsuda index was lower in PCOS vs. controls and positively associated with SMI% in all groups (All:P≤0.05). Only controls showed associations between insulin-like-growth-factor-1 (IGF-1) and upper (r=0.84) and lower (r=0.72) limb BMD (All:P<0.01). Unlike in PCOS, IGF binding-protein-2 was associated with SMI% in controls (r=0.45) and HA (r=0.67), and with upper limb BMD (r=0.98) in HA (All:P<0.05). Conclusions: Women with PCOS exhibit early signs of osteosarcopenia compared to controls likely attributed to disrupted insulin function. Understanding the degree of musculoskeletal deterioration in PCOS is critical for implementing targeted interventions that prevent and delay osteosarcopenia in this clinical population.

opencc-zeroAug 2020View details →

dryad28/100

Data from: Global assessment of the impact of type 2 diabetes on sleep through specific questionnaires. A case-control study

Type 2 diabetes (T2D) is an independent risk factor for sleep breathing disorders. However, it is unknown whether T2D affects daily somnolence and quality of sleep independently of the impairment of polysomnographic parameters. Material and Methods: A case-control study including 413 patients with T2D and 413 non-diabetic subjects, matched by age, gender, BMI, and waist and neck circumferences. A polysomnography was performed and daytime sleepiness was evaluated using the Epworth Sleepiness Scale (ESS). In addition, 135 subjects with T2D and 45 controls matched by the same previous parameters were also evaluated through the Pittsburgh Sleep Quality Index (PSQI) to calculate sleep quality. Results: Daytime sleepiness was higher in T2D than in control subjects (p=0.003), with 23.9% of subjects presenting an excessive daytime sleepiness (ESS>10). Patients with fasting plasma glucose (FPG ?13.1 mmol/l) were identified as the group with a higher risk associated with an ESS>10 (OR 3.9, 95% CI 1.8-7.9, p=0.0003). A stepwise regression analyses showed that the presence of T2D, baseline glucose levels and gender but not polysomnographic parameters (i.e apnea-hyoapnea index or sleeping time spent with oxigen saturation lower than 90%) independently predicted the ESS score. In addition, subjects with T2D showed higher sleep disturbances [PSQI: 7.0 (1.0-18.0) vs. 4 (0.0-12.0), p<0.001]. Conclusion: The presence of T2D and high levels of FPG are independent risk factors for daytime sleepiness and adversely affect sleep quality. Prospective studies addressed to demonstrate whether glycemia optimization could improve the sleep quality in T2D patients seem warranted.

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Dataset results

Data from: Risk factors for bloodborne viral hepatitis in healthcare workers of Pakistan: a population based case–control study

Data from: Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation

Data from: Osteosarcopenia in reproductive-aged women with polycystic ovary syndrome: a multicenter case-control study

Data from: Global assessment of the impact of type 2 diabetes on sleep through specific questionnaires. A case-control study

Measurement report: Impact of emission control measures on environmental persistent free radicals and reactive oxygen species – A short-term case study in Beijing

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