RESUMO
In patients with heart failure, guideline directed medical therapy improves outcomes and requires close patient monitoring. Pulmonary artery pressure monitors permit remote assessment of cardiopulmonary haemodynamics and facilitate early intervention that has been shown to decrease heart failure hospitalization. Pressure sensors implanted in the pulmonary vasculature are stabilized through passive or active interaction with the anatomy and communicate with an external reader to relay invasively measured pressure by radiofrequency. A body mass index > 35 kg/m2 and chest circumference > 165 cm prevent use due to poor communication. Pulmonary vasculature anatomy is variable between patients and the pulmonary artery size, angulation of vessels and depth of sensor location from the chest wall in heart failure patients who may be candidates for pressure sensors remains largely unexamined. The present study analyses the size, angulation, and depth of the pulmonary artery at the position of implantation of two pulmonary artery pressure sensors: the CardioMEMS sensor typically implanted in the left pulmonary artery and the Cordella sensor implanted in the right pulmonary artery. Thirty-four computed tomography pulmonary angiograms from patients with heart failure were analysed using the MIMICS software. Distance from the bifurcation of the pulmonary artery to the implant site was shorter for the right pulmonary artery (4.55 ± 0.64 cm vs. 7.4 ± 1.3 cm) and vessel diameter at the implant site was larger (17.15 ± 2.87 mm vs. 11.83 ± 2.30 mm). Link distance (length of the communication path between sensor and reader) was shorter for the left pulmonary artery (9.40 ± 1.43 mm vs. 12.54 ± 1.37 mm). Therefore, the detailed analysis of pulmonary arterial anatomy using computed tomography pulmonary angiograms may alter the choice of implant location to reduce the risk of sensor migration and improve readability by minimizing sensor-to-reader link distance.
Assuntos
Insuficiência Cardíaca , Artéria Pulmonar , Humanos , Artéria Pulmonar/diagnóstico por imagem , Insuficiência Cardíaca/terapia , Próteses e Implantes , Hemodinâmica , Monitorização FisiológicaRESUMO
OBJECTIVES: To evaluate 2 renal tubular enzymes; urinary neutrophil gelatinase-associated lipocalin (uNGAL), and urinary N-acetyl-beta-D-glucosaminidase (uNAG), and serum Cystatin C as candidate biomarkers for early diagnosis of early stage of diabetic nephropathy (DB) in patients with type 2 diabetes mellitus (T2DM). METHODS: This cross-sectional study was carried out at King Abdulaziz University Hospital (KAUH), Jeddah, Saudi Arabia during the period between May 2017 and May 2018 and was conducted on 86 patients with T2DM. Patients were classified according to their albumin/creatinine ratio (ACR) into 3 groups; a normal albuminuria group with ACR less than 30 mg/g creatinine, a moderately increased albuminuria group with ACR: 30-299 mg/g creatinine, and a severely increased albuminuria group with ACR ≥300 mg/g. Healthy adults were recruited as a control group. Urine uNGAL, uNAG, and serum Cystatin C were measured in all patients. RESULTS: Compared with healthy control, diabetic patients with normal albuminuria excreted significantly higher levels of uNGAL (p less than 0.001). In addition, significantly elevated uNGAL, uNAG and cystatin C levels were observed in moderately increased albuminuria and severely increased albuminuria groups when compared to the control and normoalbuminuric groups (p less than 0.001). urinary neutrophil gelatinase-associated lipocalin, urinary N-acetyl-beta-D-glucosaminidase and Cystatin C showed a positive correlation with fasting blood glucose (FBG), HbA1c, duration of diabetes, urea, creatinine, and ACR. CONCLUSION: Our results indicated that uNGAL could be a sensitive biomarker for early renal dysfunction in diabetic patients while uNAG and serum Cystatin C might have prognostic value.
Assuntos
Cistatina C/sangue , Diabetes Mellitus Tipo 2/complicações , Nefropatias Diabéticas/diagnóstico , Lipocalina-2/urina , Biomarcadores/sangue , Biomarcadores/urina , Estudos Transversais , Diagnóstico Precoce , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , PrognósticoRESUMO
BACKGROUND: Fine-needle aspiration cytology remains a valuable screening tool for preoperative management of thyroid nodules. However, the rates of false-negative and false-positive diagnosis remain a challenge for pathologists. OBJECTIVES: To assess the value of thyroid fine-needle aspiration as a screening tool and its accuracy of diagnoses relative to final histological diagnoses. PATIENTS AND METHODS: A chart review was conducted of all adult patients who underwent fine-needle aspiration of thyroid nodule(s) and were subjected to thyroid surgery at King Abdulaziz Medical City, Jeddah, Saudi Arabia, between January 2007 and June 2014. The fine-needle aspiration results were correlated with final histopathology results. RESULTS: Of the 408 aspirates from 373 patients, the Bethesda System for Reporting Thyroid Cytology (BSRTC) diagnostic categories were as follows: nondiagnostic in 26 aspirates (6.4%); benign in 128 (31.4%); atypia/follicular lesion of undetermined significance in 52 (12.7%); follicular neoplasm/suspicion for a follicular neoplasm in 83 (20.3%); suspicious for malignancy in 23 (5.6%) and malignant in 96 (23.5%). The comparative histopathological diagnoses were benign in 192 (47.1%) and malignant in 216 (52.9%) aspirates. The calculated risk of malignancy in the fine-needle aspiration categories was 34.6% in diagnostic category (DC) I, 15.6% in DC II, 50% in DC III, 52% in DC IV, 95.7% in DC V and 100% in DC VI. The sensitivity of fine-needle aspiration with BSRTC was 88.9%, specificity was 75.6%, positive predictive value was 79.7%, negative predictive value was 84.4% and accuracy was 81.5%. CONCLUSION: The results of this retrospective study demonstrated higher risks of malignancy in DC I, DC II, DC III and DC IV than that of the original BSRTC definition, along with a higher specificity and positive predictive value for cancer diagnosis, and a lower sensitivity and negative predictive value.