Fluid dynamics in patients with nasal disease

Computational fluid dynamics （CFD） analysis is useful for quantitative assessment in patients with upper airway obstructions. We compared CFD analysis with rhinomanometry （RM） and acoustic rhinometry （AR）. Twenty patients with nasal and paranasal diseases who required computed tomography assessment underwent RM and AR. We measured the pressure and velocity at four parts of the upper airway using CFD analysis. Then we evaluated the correlation among CFD analysis, RM, and AR. CFD analysis detected obstruction sites in the nasal airway and pharynx in 14 and 2patients, respectively. High negative pressure accompanied the nasal obstruction, even behind the nasal cavity. Nasal airway pressure measured using CFD analysis strongly correlated with nasal resistance in RM （Spearman correlation coefficient＝0.853）. CFD analysis’s sensitivity and specificity to detect the obstruction were 84.6％ and 57.1％, respectively （compared to those of RM） and 83.3％ and 50.0％, respectively （compared to those of AR）. The CFD analysis’s ability to detect obstruction was comparable to that of RM and AR; therefore, it may help evaluate the upper airways in patients with nasal and paranasal diseases. We found impaired nasal ventilation also affected other parts of the upper airway. Further studies with a larger sample size are required to validate the use of CFD analysis for assessing the degree of upper airway ventilation disorders

Computational fluid dynamics analysis in patients with nasal disease

Computational fluid dynamics （CFD） analysis is useful for quantitative assessment in patients with upper airway obstructions. We compared CFD analysis with rhinomanometry （RM） and acoustic rhinometry （AR）. Twenty patients with nasal and paranasal diseases who required computed tomography assessment underwent RM and AR. We measured the pressure and velocity at four parts of the upper airway using CFD analysis. Then we evaluated the correlation among CFD analysis, RM, and AR. CFD analysis detected obstruction sites in the nasal airway and pharynx in 14 and 2patients, respectively. High negative pressure accompanied the nasal obstruction, even behind the nasal cavity. Nasal airway pressure measured using CFD analysis strongly correlated with nasal resistance in RM （Spearman correlation coefficient＝0.853）. CFD analysis’s sensitivity and specificity to detect the obstruction were 84.6％ and 57.1％, respectively （compared to those of RM） and 83.3％ and 50.0％, respectively （compared to those of AR）. The CFD analysis’s ability to detect obstruction was comparable to that of RM and AR; therefore, it may help evaluate the upper airways in patients with nasal and paranasal diseases. We found impaired nasal ventilation also affected other parts of the upper airway. Further studies with a larger sample size are required to validate the use of CFD analysis for assessing the degree of upper airway ventilation disorders

Changes in Pediatric Patient Trends in Eating and Swallowing Disorders: A Comparison between the First and Fifth Year after Establishment of the Special Needs Dental Center

A Special Needs Dental Center （hereafter referred to as the Center） was established at Showa University Dental Hospital in April 2012 to treat patients who need special care. In cooperation with the Division of Dentistry for Persons with Disabilities, the Division of Hygiene and Oral Health is mainly engaged in the treatment of patients with eating and swallowing disorders. It has been five years since the establishment of the Center. The present study was aimed to establish an effective medical support method through a comparative study of changes in patient trends. A total of 65 patients who visited the Center from April 2017 to March 2018 were examined and their statistics were compared with those of 60 previously reported patients who initially visited the Center for medical examination in 2012. In 2012, many visits occurred during the nursing period; however, in 2017, the number of patients who visited after the weaning period increased. Other noted trends were increased diversity in primary disease, more patient referrals, fewer patients with severe swallowing dysfunction, and more patients with oral dysfunction. The necessity of eating and swallowing practice is thought to increase when lifestyle and oral environment change. The treatment of eating and swallowing disorders is important in the dental profession. Due to the introduction of insurance coverage in Japan in 2018 for developmental insufficiency of oral function, more pediatric patients with eating and swallowing disorders will likely be treated in the future

Urinary neutrophil gelatinase-associated lipocalin: a useful biomarker for tacrolimus-induced acute kidney injury in liver transplant patients.

Tacrolimus is widely used as an immunosuppressant in liver transplantation, and tacrolimus-induced acute kidney injury (AKI) is a serious complication of liver transplantation. For early detection of AKI, various urinary biomarkers such as monocyte chemotactic protein-1, liver-type fatty acid-binding protein, interleukin-18, osteopontin, cystatin C, clusterin and neutrophil gelatinase-associated lipocalin (NGAL) have been identified. Here, we attempt to identify urinary biomarkers for the early detection of tacrolimus-induced AKI in liver transplant patients. Urine samples were collected from 31 patients after living-donor liver transplantation (LDLT). Twenty recipients developed tacrolimus-induced AKI. After the initiation of tacrolimus therapy, urine samples were collected on postoperative days 7, 14, and 21. In patients who experienced AKI during postoperative day 21, additional spot urine samples were collected on postoperative days 28, 35, 42, 49, and 58. The 8 healthy volunteers, whose renal and liver functions were normal, were asked to collect their blood and spot urine samples. The urinary levels of NGAL, monocyte chemotactic protein-1 and liver-type fatty acid-binding protein were significantly higher in patients with AKI than in those without, while those of interleukin-18, osteopontin, cystatin C and clusterin did not differ between the 2 groups. The area under the receiver operating characteristics curve of urinary NGAL was 0.876 (95% confidence interval, 0.800-0.951; P<0.0001), which was better than those of the other six urinary biomarkers. In addition, the urinary levels of NGAL at postoperative day 1 (p = 0.0446) and day 7 (p = 0.0006) can be a good predictive marker for tacrolimus-induced AKI within next 6 days, respectively. In conclusion, urinary NGAL is a sensitive biomarker for tacrolimus-induced AKI, and may help predict renal event caused by tacrolimus therapy in liver transplant patients

Characteristics of the urinary biomarkers.

<p><b>Abbreviations:</b> AUC, area under the curve; CI, confidence interval; IL-18, interleukin-18; L-FABP, liver-type fatty acid-binding protein; MCP-1, monocyte chemotactic protein-1; NGAL, neutrophil gelatinase-associated lipocalin.</p><p>Characteristics of the urinary biomarkers.</p

Patient characteristics.

<p>NOTE: The results are given as mean ± standard deviation. Statistical analysis was performed using the Mann-Whitney U test and Kruskal-Wallis test.</p><p><b>Abbreviations:</b> BUN, blood urea nitrogen; eGFR, estimated glomerular filtration rate; MELD, Model for End-stage Liver Disease; Scr, serum creatinine; POD, postoperative day.</p><p>Patient characteristics.</p

Time-dependent changes tacrolimus concentration, Scr levels and urinary NGAL concentrations.

<p>The average ± SD values of tacrolimus trough concentrations, Scr levels and urinary NGAL concentrations in the liver transplant patients who experienced AKI during the period of postoperative day 1–5 (B, F, J), during the postoperative day 6–10 (C, G, K), after the postoperative day 11 (D, H, L) and AKI-free patients (A, E, I) are summarized. The cut-off values of urinary NGAL calculated from ROC analysis were 61.0 ng/mg creatinine (red dotted line).</p

Comparison of the urinary levels of NGAL (A), MCP-1 (B), L-FABP (C), IL-18 (D), osteopontin (E), cystatin C (F), and clusterin (G) between AKI-free group (37 measurements of 11 subjects) and AKI group (40 measurements of 20 subjects).

<p>Data were from urinary samples in the post-transplant tacrolimus therapy. Data were normalized to urinary creatinine concentration and plotted on a logarithmic Y axis. Statistical analyses were performed using the Mann-Whitney U test and Kruskal-Wallis test. *P<0.05, ***P<0.001. NGAL, neutrophil gelatinase-associated lipocalin; MCP-1, monocyte chemotactic protein-1; L-FABP, liver-type fatty acid-binding protein; IL-18, interleukin-18, N.D., not detected.</p