Serum lactate dehydrogenase and its isoenzymes as predictors of clinical outcomes in acute exacerbation of chronic obstructive pulmonary disease: a retrospective analysis of a hospitalized cohort

We aimed to test the relationship between serum lactate dehydrogenase (LDH) and its isoenzymes and treatment outcomes during hospitalization for acute exacerbations of chronic obstructive pulmonary disease (AECOPD). Thirty-eight AECOPD patients were recruited from a tertiary hospital from December 2017 to June 2018. Serum LDH and LDH isoenzymes were measured on venous blood collected at admission. Treatment outcomes included duration of hospital stay, initiation of mechanical or non-invasive ventilation (NIV), initiation of antipseudomonal antibiotics, change in empirical antibiotic treatment, need for intravenous corticosteroids or methylxanthines, and percentage of change in C-reactive protein from admission to the third day. Multivariate linear and binary logistic regression analyses were used to test the study's objectives. We found that, after adjusting for age, gender, comorbidities, COPD severity, level of hypoxemia, and inflammation markers, each 10 U/L increase in serum LDH was associated with prolongation of the hospital stay by 0.25 (0.03, 0.46) days, 42% higher odds [odds ratio (OR) 1.42 (1.00, 2.03)] for need of NIV, and 25% higher odds [OR 1.25 (1.04, 1.49)] for initiation of antipseudomonal treatment. LDH1 and LDH2 were the LDH isoenzymes that mainly drove these relationships. LDH release in the context of an AECOPD could originate from lung, muscle, or heart tissue damage due to airway inflammation, respiratory muscle recruitment, and myocardial stress. Myocardial injury and aerobic adaptation in respiratory muscles may explain the predominance of LDH1 and LDH2 isoenzymes in these associations.

Lactate dehydrogenase isoenzymes in patients with acute exacerbation of chronic obstructive pulmonary disease: An exploratory cross-sectional study

We aimed to evaluate differences in serum lactate dehydrogenase (LDH) isoenzymes between patients hospitalized for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and other lower respiratory tract infections (LRTIs). Based on self-reported COPD diagnosis, 71 participants were divided into AECOPD (n = 38, 29 males, mean age 70.5 years) and LRTI (n = 33, 12 males, mean age 70.4 years) groups. Information on demographics, comorbidities, and COPD severity markers, as well as arterial blood gases and laboratory data were collected, while serum LDH electrophoresis was performed to examine the LDH isoenzymes. Adjusting for sex, age, comorbidities, degree of hypoxemia, inflammation markers, muscle and myocardial enzymes, and total serum LDH, the mean differences (95 % confidence intervals) in the ratios of serum LDH isoenzymes to total serum LDH between groups (LDHx_AECOPD - LDHx_LRTI) were statistically significant for LDH1 [4.9 (1.4 to 8.3)], LDH2 [3.0 (0.1 to 5.8)], LDH3 [-4.3 (-6.3 to -2.3)], and LDH4 [-3.2 (-4.9 to -1.5)]. A sum of LDH3 and LDH4 ratios below 29 % had the highest discriminative ability to classify a subject in the AECOPD group (AUC 0.841, sensitivity 76 %, specificity 87 %). Aerobic metabolic adaptive mechanisms in respiratory muscles during AECOPD could explain the above differences.

Efficacy and safety of three different analgesic methods for patients undergoing transrectal ultrasound-guided prostate biopsy: a prospective, randomized controlled trial

BACKGROUND

Recent evidence suggests that additional analgesic regimens to periprostatic nerve block (PPNB) anesthesia provide substantial pain relief during transrectal ultrasound-guided prostate biopsy. In this regard, we investigated the efficacy and safety of tramadol alone or in combination with parecoxib as adjunct regimens to PPNB anesthesia.

MATERIAL AND METHODS

A total of 51 participants were randomly allocated into three study groups: Group 1 received PPNB anesthesia, Group 2 received tramadol and PPNB anesthesia, whereas Group 3 received both tramadol and parecoxib as adjunct regimens to PPNB anesthesia. The pain was evaluated at three different time points during biopsy: at the time of probe insertion (NRS1), at the time of PPNB anesthesia (NRS2), and at the time of the actual biopsy itself (NRS3), using a numeric rating scale (NRS) of pain. Safety was evaluated by the occurrence of complications and adverse effects.

RESULTS

The mean NRS1 score was statistically significantly different in Groups 2 and 3 than in Group 1 (2.4 ± 1.3 and 1.1 ± 1.2 vs. 4.5 ± 1.8; p <0.0167). We found a statistically significant difference regarding NRS 2 score in Groups 2 and 3 than in Group 1 (2.6 ± 1.4 and 1.1 ± 1.3 vs. 4.1 ± 1.3; p <0.0167). The mean NRS1 and NRS2 scores were found to be statistically significantly different in Group 3 than in Group 2 (1.1 ± 1.2 vs. 2.4 ± 1.3 as well as 1.1 ± 1.3 vs. 2.6 ± 1.4; p <0.0167). Also, a statistically significant difference was found between Groups 2 and 3 regarding hematuria episodes [0 (0.0) vs. 5 (29.4); p <0.0167].

CONCLUSION

Tramadol as an adjunct regimen to PPNB anesthesia is a safe and straightforward technique that provides a significant analgesic effect. The effectiveness is even higher when tramadol is combined with parecoxib. HIPPOKRATIA 2020, 24(4): 166-172.

Breath analysis of smokers, non-smokers, and e-cigarette users

Solid phase micro extraction-Gas Chromatography/Mass Spectrometry (SPME-GC/MS) analysis was performed in exhaled breath samples of 48 healthy volunteers: 20 non-smokers, 10 smokers and 18 e-cigarette (EC, vape) users. Each volunteer provided 1 L of exhaled breath in a pre-cleaned Tedlar bag, in which an SPME fiber was exposed to absorb the emitted breath volatile organic compounds (VOCs). The acquired data were processed using multivariate data analysis (MDA) methods in order to identify the characteristic chemicals of the three groups. The results revealed that the breath of non-smokers demonstrated inverse correlation with a variety of molecules related to the breath from smokers including furan, toluene, 2-butanone and other organic substances. Vapers were distinguished from smokers by the chemical speciation of the e-liquids, such as that of esters (e.g. ethyl acetate), terpenes (e.g. α-pinene, β-pinene, d-limonene, p-cymene, etc.) and oxygenated compounds (e.g. 3-hexen-1-ol, benzaldehyde, hexanal, decanal, etc). Two classification models were developed (a) using principal component analysis (PCA) with hierarchical cluster analysis (HCA) and (b) using partial least squares-discriminant analysis (PLS-DA). Both models were validated using 8 new samples (4 vapers and 4 smokers), collected in addition to the 48 samples of the calibration set. The combination of GC/MS breath analysis and MDA contributed successfully in classifying the volunteers into their respective groups and highlighted the relevant characteristic VOCs. The respective dynamic combination (SPME-GC/MS and MDA) provides a means for long term non-invasive monitoring of the population's health status for early detection purposes.

Main and side stream effects of electronic cigarettes

Over the last decade there has been a significant boost towards the use of electronic cigarettes (e-cigarettes), especially among youth. Different concentrations of propylene glycol (PG) or vegetable glycerin (VG), flavors and nicotine are mixed in plastic cartridges and commercially offered or privately produced by the vapers. During vaping, a mixture of air and vapors is inhaled to the lungs. Since the ingredients of the e-cigarettes are not burned but vaporized (heated), fewer chemicals are emitted. The levels of potentially toxic compounds (e.g. volatile organic compounds (VOCs), particulate matter (PM), metals, radicals, nitrosamines, etc.) emitted from vaping appear to be lower compared to that of tobacco smoking (from combustible cigarettes). Nevertheless, measurable toxic elements and VOCs are still released (e.g. acetaldehyde, formaldehyde, acrolein, benzene, etc.) along with other volatiles associated with e-liquid flavoring and device variability with PG and VG. The wide range of available flavors at various purities along with the heating temperature are important parameters affecting the evolution of VOCs and aerosols. There is lack of standardized short- and long-term epidemiological medical data (chronic exposure) on e-cigarettes effects to users, non-users and the human micro-environment (second- or third-hand exposure). Therefore, the potential health, safety and environmental effects of vaping are reviewed, examined and discussed.

Nutritional characterization of carobs and traditional carob products

Twenty traditional carob products were measured for their nutritional composition, and their results were compared with the pulp of Cypriot carob cultivars. Moisture, ash, fat, proteins, sugars, dietary fibers, minerals, caffeine-theobromine, carbohydrates, and energy value were determined. Fluctuations of the nutritional composition values based on the ingredients' chemical synthesis and product manufacturing process were noted. Only 60% of the products had a label indicating their nutritional value, and the majority of them (75%) were consistent with that of labeling. Chemometric analyses distinguished the carob products according to their type and the discriminator components highlighted their particular nutritional value. Carobs can be characterized as functional foods with low-fat content, high content in dietary fibers, and high content and/or source of minerals; however, carob products partially satisfied those health and nutritional claims as expected. This pilot research contributes to the nutritional estimation of carob and highlights the traditional carob products.