Crossing the chasm: strategies for digital transformation in clinical laboratories.

Total testing process in a clinical laboratory is designed to produce useful information for patients and clinicians. The changing landscape of healthcare industry forces clinical laboratory leaders to meet the needs of their stakeholders, maximize operational efficiency and improve overall quality of patient care at the same time. The increasing number of data produced force healthcare services industry to digital transformation. Digital transformation is a process of change which includes finding solutions to novel and unmet requirements of an industry by integrating information, computing, communication and connectivity technologies to minimize the number of low-value tasks and focus on high-value tasks. As the process of digital transformation includes not only the modernization of IT infrastructure but also a paradigm shift in perception of value creation and delivery to improve the quality and cost-effectiveness of laboratory operations in the long run, financial, managerial, and educational issues have been blocking the widespread implementation. Clinical laboratories are at the crossroads on the road to the future. Laboratories that fail to align themselves with data-driven practices will risk losing a competitive advantage. In this review, strategies for a successful digital transformation will be overviewed in the context of clinical laboratory settings.

Impact of COVID-19 on serum melatonin levels and sleep parameters in children

Background/aim: This study aimed to analyze the serum melatonin levels and changes in sleep patterns in pediatric patients with coronavirus disease 2019 (COVID-19). Materials and methods: This study was designed as a descriptive, cross-sectional study. Serum melatonin levels and sleep parameters of children with the diagnosis of COVID-19 who had mild and moderate disease (i.e., COVID-19 group) were compared with those of children admitted with non-COVID-19 nonspecific upper respiratory tract infection (i.e., control group). The sleep disturbance scale for children (SDSC) questionnaire was applied to the participants> primary caregivers to analyze their sleep patterns at present and six months before symptom onset and to investigate the impact of COVID-19 on sleep patterns. Results: The entire study cohort consisted of 106 patients. The COVID-19 group included 80 patients, while the control group consisted of 26 patients. The mean serum melatonin levels were 136.72 pg/mL and 172.63 pg/mL in the COVID-19 and control groups, respectively (p = 0.16). There was no significant difference between the groups in terms of 6 subcategories of the SDSC questionnaire regarding the present time and 6 months before symptom onset. The total SDSC scores were also similar in two different evaluation time points described above (p = 0.99) Conclusions: We conclude that COVID-19 did not impact the sleep parameters of children. Serum melatonin levels of all patients were higher than the reference range; however, they were higher in the non-COVID-19 patient group than the COVID-19 group. Since serum melatonin levels were higher than the reference values in children with COVID-19, and this disease is significantly less morbid in children, melatonin may have protective effects against COVID-19.

Is the low AMH level associated with the risk of cardiovascular disease in obese pregnants?

Our aim was to investigate whether Antimullerian Hormone (AMH), complete blood count (CBC), Homeostasis model assessment (HOMA-IR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and weight gain have any diagnostic value for the prediction of cardiovascular disease (CVD) in obese and non-obese pregnant patients. A prospective, case-control study was carried out, including 187 patients (93 obese, and 94 non-obese). CVD risk for each patient was evaluated according to the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA). A multivariate logistic regression model was used to identify the independent risk factors of CVD in obese and non-obese patients. The obese patients had significantly lower levels of AMH when compared to the non-obese ones (p = .002). Insulin, HOMA-IR, HbA1c, and SBP were significantly higher in obese patients than non-obese ones (p < .001, p < .001 and p = .001, respectively). Age, SBP, and decreased AMH levels had significantly associated with risk factors of CVD in the obese group (p = .001, p = .002, and p = .049, respectively). Our study suggests that decreased AMH levels, increased age, and SBP are associated with CVD in obese patients. AMH may be used to evaluate CVD risk in advanced aged, obese patients.IMPACT STATEMENTWhat is already known on this subject? Obesity is one of the most common medical complications of pregnancy. Obesity increases maternal complications such as preeclampsia, caesarean rate, cardiovascular disease, obesity, and diabetes after pregnancy; and neonatal complications including macrosomia, hypoglycaemia, hyperbilirubinemia, delivery trauma, shoulder dystocia, and adult-onset obesity, and diabetes. Obese patients have lower serum AMH levels.What the results of this study add? A significant relationship between AMH levels and CVD risk in obese pregnant women was observed.What are the implications of these findings for clinical practice and/or further research? Based on this finding, we concluded that decreased AMH levels are predictive for CVD in obese pregnant women.

Acoustic Radiation Force Impulse (ARFI) for Fibrosis Staging in Patients with Autoimmune Hepatitis.

BACKGROUND/AIMS: The performance of non-invasive fibrosis markers has not been well studied in autoimmune hepatitis (AIH). Acoustic radiation force impulse imaging (ARFI) is a non-invasive radiological method for assessment of liver fibrosis. The aim of this study was to evaluate the accuracy of ARFI for fibrosis staging in patients with AIH. METHODOLOGY: AIH patients who undergone for control liver biopsy after at least two years of biochemical remission period were also assessed by ARFI. Liver fibrosis was staged according to the METAVIR scoring system. RESULTS: A total of 15 patients (13 women and 2 men) with mean age of 40.9 (18-59 years) were included in the study. Repeat liver biopsy was performed a mean of 4.9 (3-9 years) after AIH diagnosis. Nine patients had significant fibrosis scores (F ≥ 2) while, remain 6 patients had mild or no fibrosis. The mean (±SD) shear wave velocities for patients with fibrosis stage II-IV was significantly higher than those with fibrosis stage 0-I (2.28 ± 0.68 m/s and 1.20 ± 0.24, respectively, p = 0.002). CONCLUSIONS: ARFI is able to differentiate significant from non significant liver fibrosis in patients with AIH. Our study suggests that this non-invasive method can be used for monitoring fibrosis progression in AIH.

The effect of jet-lag on serum concentrations of thyroid stimulating hormone and prolactin: A case report.

INTRODUCTION: This case report is about the importance of sleeping status for analysis of thyroid hormone stimulating hormone (TSH) and prolactin (PRL) which arose from discordant results of a patient who was referred for serum TSH and PRL testing within 12-hour period after an intercontinental flight. CASE DESCRIPTION: An adult male patient was admitted to our laboratory for serum TSH and PRL tests and came back questioning the accuracy of his previous results. FURTHER INVESTIGATIONS: A new analysis with a new sample was offered. His new results were not consistent with his previous results. WHAT HAPPENED: It was revealed that the night before the first sampling, he travelled back to Turkey from The United States of America and came to testing within 12 hours after the arrival. DISCUSSION: Sleeping status is one of the factors that can affect laboratory results. Intercontinental flights causing jet-lag can alter the secretions of TSH and PRL which are predominantly modulated by thyrotropin-releasing hormone (TRH). MAIN LESSON: Travel history and sleeping status are important factors to be evaluated prior sampling for hormone analysis. Patients must be informed about the importance of sampling timing.