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Autoanticorpi anti-insula pancreatica (ICA, GADAb, IA2Ab, IAAb) in 154 pazienti con diabete mellito (DM) di Tipo 1 neoinsorto
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Higher levels of C-reactive protein and ferritin in patients with overweight and obesity and SARS-CoV-2-related pneumonia
Full text linkIntroduction: Overweight and obesity are associated with a more severe COronaVirus Disease 19 (COVID-19). Adipose tissue-related chronic inflammation could be a promoter for the occurrence of the cytokine storm that predicts aggravation of COVID-19. The primary aim was to investigate if this increased risk for more severe COVID-19 was associated with a higher inflammatory response. Methods: We enrolled patients <75 years old hospitalized in a medical COVID-19 ward with SARS-CoV-2-related pneumonia. Patients were classified according to BMI as normal weight, overweight, and obesity. Laboratory parameters were measured at admission and every second day during the hospital stay. Results: Ninety patients (64.4% males; median age 61 years) were enrolled. Invasive mechanical ventilation (IMV) was needed in 9% of the patients with normal weight, in 32.4% of the patients with overweight, and in 12.9% of the patients with obesity (p = 0.045). Maximal C-reactive protein (CRP) level during hospital stay was 92 (48-122) mg/L in patients with normal weight, 140 (82-265) mg/L in patients with overweight, and 117 (67-160) mg/L in patients with obesity (p = 0.037). Maximal ferritin values were 564 (403-1,379) μg/L in patients with a normal weight, 1,253 (754-2,532) μg/L in patients with overweight, and 828 (279-1,582) μg/L in patients with obesity (p = 0.015). Conclusion: Patients with overweight and obesity required more IMV and had higher peaks of CRP and ferritin than patients with normal weight during COVID-19
Association of obstructive sleep apnea with non-alcoholic fatty liver disease in patients with obesity: an observational study
Full text linkPurpose: Obstructive Sleep Apnea (OSA) is associated with the presence and severity of Non-Alcoholic Fatty Liver Disease (NAFLD). We aimed to investigate the relationship between the severity of OSA and NAFLD and to recognize a polysomnographic parameter correlated with progression of fibrosis, determined by a non-invasive score of liver fibrosis, FIBrosis-4 index (FIB-4), in patients affected by severe obesity and OSA. Methods: We enrolled 334 patients (Body Mass Index, BMI 44.78 ± 8.99 kg/m2), divided into classes according to severity of OSA evaluated with Apnea Hypopnea Index (AHI): OSAS 0 or absent (17%), mild OSA (26%), moderate OSA (20%), severe OSAS (37%). We studied anthropometric, polysomnographic, biochemical data and FIB-4. A multiple regression model was computed to identify a polysomnographic independent predictor of FIB-4 among those parameters previously simple correlated with FIB-4. Results: The severity of OSA was associated with a decrease in High-Density Lipoprotein–cholesterol (HDL) and an increase in BMI, triglycerides, Homeostasis model assessment insulin-resistance index (HOMA), transaminases and FIB-4. FIB-4 correlated with sex, age, BMI, AHI, mean percentage oxyhaemoglobin (meanSaO2%), number of desaturations, platelets, transaminases, HDL, triglycerides and HOMA. The only variables independently related to FIB-4 were sex, BMI, triglycerides and meanSpO2 (r = 0.47, AdjRsqr = 0.197). Conclusion: MeanSpO2% represented an independent determinant for the worsening of FIB-4 in patients with severe obesity and OSA. Hence, it could hypothesize a clinical role of meanSaO2% in recognizing patients with obesity and OSA and higher risk of developing advanced fibrosis and, thus, to undergo further investigation. Level III: Evidence obtained from well-designed cohort analytic studies
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Extensive clinical experience - Estimated risk for developing autoimmune Addison's disease in patients with adrenal cortex autoantibodies
No full textSARS-CoV-2 RNA identification in nasopharyngeal swabs: Issues in pre-analytics
Full text linkThe direct identification of SARS-CoV-2 RNA in nasopharyngeal swabs is recommended for diagnosing the novel COVID-19 disease. Pre-analytical determinants, such as sampling procedures, time and temperature storage conditions, might impact on the end result. Our aim was to evaluate the effects of sampling procedures, time and temperature of the primary nasopharyngeal swabs storage on real-time reverse-transcription polymerase chain reaction (rRT-PCR) results. Each nasopharyngeal swab obtained from 10 hospitalized patients for COVID-19 was subdivided in 15 aliquots: five were kept at room temperature; five were refrigerated (+4 °C); five were immediately mixed with the extraction buffer and refrigerated at +4 °C. Every day and for 5 days, one aliquot per condition was analyzed (rRT-PCR) for SARS-CoV-2 gene E and RNaseP and threshold cycles (Ct) compared. To evaluate manual sampling, 70 nasopharyngeal swabs were sampled twice by two different operators and analyzed separately one from the other. A total of 6/10 swabs were SARS-CoV-2 positive. No significant time or storage-dependent variations were observed in SARS-CoV-2 Ct. Re-sampling of swabs with SARS-CoV-2 Ct lower than 33 resulted in highly reproducible results (CV=2.9%), while a high variability was observed when Ct values were higher than 33 (CV=10.3%). This study demonstrates that time and temperature of nasopharyngeal swabs storage do not significantly impact on results reproducibility. However, swabs sampling is a critical step, and especially in case of low viral load, might be a potential source of diagnostic errors
Modifications of Resting Energy Expenditure after surgical or medical weight loss: Is there any difference?
No full textBackground/Aim: Resting energy expenditure (REE) tends to decline after
caloric restriction more than what is expected according to body composition
changes. This metabolic adaptation is considered one of the factors
favoring weight regain and obesity recidivism. Weight maintenance is
more common after bariatric surgery than after medical weight loss. Our
Aim: was to evaluate if metabolic adaptation is different after surgical or
medical weight loss.
Methods: REE (indirect calorimetry) and body composition (fat-free
mass or FFM, fat mass or FM by bioelectrical impedance analysis) were
determined before and after a 12 months weight loss in 98 obese patients
(mean BMI: 46.8 ± 8.0 kg/m2) treated with laparoscopic sleeve gastrectomy
(LSG) and in 21 obese patients (mean BMI: 35.1 ± 15.0 kg/m2) reaching
at least a 10% weight loss with a lifestyle modification program.
Results: Weight loss was 28.3 ± 9.2% of the baseline body weight in the
surgical group and 18.5 ± 6.2% in the medical group (p < 0.001), with
corresponding relative reductions in FM (44.4 ± 18.0 vs 34.7 ± 13.0%,
p < 0.05), FFM (13.1 ± 8.0 vs 6.1 ± 7.3%, p < 0.01), and REE (28.3 ± 12.6
vs 15.0 ± 17.0%, p < 0.01). In order to account for body composition
changes, a predictive equation for REE was derived by using the baseline
FFM and FM values. A predicted post-weight loss REE was then calculated
by using this equation and by entering the individual body composition
values measured after weight loss. Metabolic adaptation was defined
as the difference between observed and predicted REE after weight loss.
Metabolic adaptation was -182 ± 227 kcal/day in the surgical group and
-86 ± 212 kcal/day in the medical group (p = not significant).
Conclusion: Metabolic adaptation during weight loss, defined as any reduction
of REE beyond what is can be expected by FFM and FM loss,
was not significantly different in patients losing weight after LSG and in
patients losing weight by lifestyle modifications. Weight maintenance after
bariatric surgery seems not to be attributable to differences in REE
adaptation during weight loss
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