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| 1 | Predictive value of multi-detector computed tomography for accurate diagnosis of serous cystadenoma:Radiologic-pathologic correlation显示文摘AIM:To identify multi-detector computed tomography(MDCT) features most predictive of serous cystadenomas(SCAs),correlating with histopathology,and to study the impact of cyst size and MDCT technique on reader performance.METHODS:The MDCT scans of 164 patients with surgically verified pancreatic cystic lesions were reviewed by two readers to study the predictive value of various morphological features for establishing a diagnosis of SCAs.Accuracy in lesion characterization and reader conf idence were correlated with lesion size(≤3cm or≥3cm) and scanning protocols(dedicated vs routine).RESULTS:28/164 cysts(mean size,39 mm;range,8-92mm) were diagnosed as SCA on pathology.The MDCT features predictive of diagnosis of SCA were microcystic appearance(22/28,78.6%),surface lobulations(25/28,89.3%) and central scar(9/28,32.4%).Stepwise logistic regression analysis showed that only microcystic appearance was signifi cant for CT diagnosis of SCA(P=0.0001).The sensitivity,specificity and PPV of central scar and of combined microcystic appearance and lobulations were 32.4%/100%/100% and 68%/100%/100%,respectively.The reader confidence was higher for lesions>3cm(P=0.02) and for MDCT scans performed using thin collimation(1.25-2.5mm) compared to routine 5 mm collimation exams(P>0.05).CONCLUSION:Central scar on MDCT is diagnostic of SCA but is seen in only one third of SCAs.Microcystic morphology is the most significant CT feature in diagnosis of SCA.A combination of microcystic appearance and surface lobulations offers accuracy comparable to central scar with higher sensitivity. | Anjuli A Shah Nisha I Sainani Avinash Kambadakone Ramesh Zarine K Shah Vikram Deshpande Peter F Hahn Dushyant V Sahani | 2009 | World Journal of Gastroenterology2009，15，22： | 11 |
| 2 | Metabolic syndrome and chronic kidney disease:Current status and future directions显示文摘Metabolic syndrome(Met S) is a term used to denote a combination of selected,widely prevalent cardiovascular disease(CVD)-related risk factors.Despite the ambiguous definition of Met S,it has been clearly associated with chronic kidney disease markers including reduced glomerular filtration rate,proteinuria and/or microalbuminuria,and histopathological markers such as tubular atrophy and interstitial fibrosis.However,the etiological role of Met S in chronic kidney disease(CKD) is less clear.The relationship between MetS and CKD is complex and bidirectional,and so is best understood when CKD is viewed as a common progressive illness along the course of which MetS,another common disease,may intervene and contribute.Possible mechanisms of renal injury include insulin resistance and oxidative stress,increased proinflammatory cytokine production,increased connective tissue growth and profibrotic factor production,increased microvascular injury,and renal ischemia.MetS also portends a higher CVD risk at all stages of CKD from early renal insufficiency to end-stage renal disease.Clinical interventions for MetS in the presence of CKD should include a combination of weight reduction,appropriate dietary modification and increase physical activity,plus targeting of individual CVD-related risk factors such as dysglycemia,hypertension,and dyslipidemia while conforming to relevant national societal guidelines. | G V Ramesh Prasad | 2014 | World Journal of Nephrology2014，3，4： | 8 |
| 3 | New-onset diabetes mellitus after kidney transplantation:Current status and future directions显示文摘A diagnosis of new-onset diabetes after transplantation(NODAT) carries with it a threat to the renal allograft,as well as the same short-and long-term implications of type 2 diabetes seen in the general population.NODAT usually occurs early after transplantation,and is usually diagnosed according to general population guidelines.Non-modifiable risk factors for NODAT include advancing age,African American,Hispanic,or South Asian ethnicity,genetic background,a positive family history for diabetes mellitus,polycystic kidney disease,and previously diagnosed glucose intolerance.Modifiable risk factors for NODAT include obesity and the metabolic syndrome,hepatitis C virus and cytomegalovirus infection,corticosteroids,calcineurin inhibitor drugs(especially tacrolimus),and sirolimus.NODAT affects graft and patient survival,and increases the incidence of post-transplant cardiovascular disease.The incidence and impact of NODAT can be minimized through pre-and post-transplant screening to identify patients at higher risk,including by oral glucose tolerance tests,as well as multi-disciplinary care,lifestyle modification,and the use of modified immunosuppressive regimens coupled with glucose-lowering therapies including oral hypoglycemic agents and insulin.Since NODAT is a major cause of post-transplant morbidity and mortality,measures to reduce its incidence and impact have the potential to greatly improve overall transplant success. | Sneha Palepu G V Ramesh Prasad | 2015 | World Journal of Diabetes2015，6，3： | 8 |
| 4 | Post-transplant dyslipidemia: Mechanisms, diagnosis and management显示文摘Post-transplant dyslipidemia is highly prevalent and presents unique management challenges to the clinician. The two major outcomes to considerwith post-transplant therapies for dyslipidemia are preserving or improving allograft function, and reducing cardiovascular risk. Although there are other cardiovascular risk factors such as graft dysfunction, hypertension, and diabetes, attention to dyslipidemia is warranted because interventions for dyslipidemia have an impact on reducing cardiac events in clinical trials specific to the transplant population. Dyslipidemia is not synonymous with hyperlipidemia. Numerous mechanisms exist for the occurrence of posttransplant dyslipidemia, including those mediated by immunosuppressive drug therapy. Statin therapy has received the most attention in all solid organ transplant recipient populations, although the effect of proper dietary advice and adjuvant pharmacological and nonpharmacological agents should not be dismissed. At all stages of treatment appropriate monitoring strategies for side effects should be implemented so that the benefits from these therapies can be achieved. Clinicians have a choice when there is a conflict between various transplant society and lipid society guidelines for therapy and targets. | Arnav Agarwal G V Ramesh Prasad | 2016 | World Journal of Transplantation2016，6，1： | 6 |
| 5 | Recent advances in new-onset diabetes mellitus after kidney transplantation显示文摘A common challenge in managing kidney transplant recipients(KTR)is posttransplant diabetes mellitus(PTDM)or diabetes mellitus(DM)newly diagnosed after transplantation,in addition to known pre-existing DM.PTDM is an important risk factor for post-transplant cardiovascular(CV)disease,which adversely affects patient survival and quality of life.CV disease in KTR may manifest as ischemic heart disease,heart failure,and/or left ventricular hypertrophy.Available therapies for PTDM include most agents currently used to treat type 2 diabetes.More recently,the use of sodium glucose co-transporter 2 inhibitors(SGLT2i),glucagon-like peptide-1 receptor agonists(GLP-1 RA),and dipeptidyl peptidase 4 inhibitors(DPP4i)has cautiously extended to KTR with PTDM,even though KTR are typically excluded from large general population clinical trials.Initial evidence from observational studies seems to indicate that SGLT2i,GLP-1 RA,and DPP4i may be safe and effective for glycemic control in KTR,but their benefit in reducing CV events in this otherwise high-risk population remains unproven.These newer drugs must still be used with care due to the increased propensity of KTR for intravascular volume depletion and acute kidney injury due to diarrhea and their single-kidney status,pre-existing burden of peripheral vascular disease,urinary tract infections due to immunosuppression and a surgically altered urinary tract,erythrocytosis from calcineurin inhibitors,and reduced kidney function from acute or chronic rejection. | Tess Montada-Atin G V Ramesh Prasad | 2021 | World Journal of Diabetes2021，12，5： | 2 |
| 6 | Pesticide residues in air from coastal environment, south India显示文摘 | RAJENDRAN R B VENUG OPALAN V K RAMESH R | 1999 | Chemosphere1999，399，10： | 1 |
| 7 | Kernel-based object tracking显示文摘 | Ramesh V Meer P | 2003 | IEEE Transactions on Pattern Analysis and Machine Intelligence2003，25，5： | 1 |
| 8 | Kernal-based objec tracking显示文摘 | COMANICIU D RAMESH V MEER P | 2003 | IEEE Trans on Pattern Analysis and Machine Inteligence2003，25，： | 1 |
| 9 | Magnetite induces oxi-dative stress and apoptosis in lung epithelial cells 显示文摘 | Ramesh V Ravichandran P Copeland CL | 2012 | Mol Cell Bio-c1iem2012，363，12： | 1 |
| 10 | Kernel-ba-sed object tracking显示文摘 | Comaniciu D Ramesh V P Meer | 2003 | IEEE Trans on Pattern Analysis and Machine Intelligent2003，25，5： | 1 |
| 11 | Kernel-based Object Tracking 显示文摘 | Comanieiu D Ramesh V MeerP | 2003 | IEEE Transactions on Pattern Analysis and Machine Intelligence2003，25，5： | 1 |
| 12 | Special issue on video communnications,processing,and understanding for third generation surveillance systems显示文摘 | C REGAZZONI V RAMESH | | 0，，10： | 1 |
| 13 | Topology Discovery for Public IPv6 Networks 显示文摘 | Daniel G W Fangzhe C Ramesh V | 2003 | Computer Communications Review2003，33，3： | 1 |
| 14 | Rhabdomyolysis induced acute renal failure secondary to statins 显示文摘 | RAM R SWARNALATHA G RAMESH V | 2013 | Indian J Nephrol2013，23，3： | 1 |
| 15 | Kernel-based object tracking显示文摘 | Comaniciu D Ramesh V Meer P | 2003 | IEEE Transactions on Pattern Analysis and Machine Intelligence2003，25，5： | 1 |
| 16 | Kernel-based Object Tracking显示文摘 | COMANICIU D RAMESH V MEER P | 2003 | IEEE Transactions on Pattern Analysis Machine Intelligence2003，25，5： | 1 |
| 17 | A Fuzzy Multiobjective Approach to Contingency Constrained OPF 显示文摘 | Ramesh V C LI Xuan | 1997 | IEEE Trans on Power Systems1997，12，3： | 1 |
| 18 | Dyschromatosis universalis hereditaria:report of a case and review of the literature 显示文摘 | Al Hawsawi K A1 Aboud K Ramesh V | 2002 | Pediatr Der- mato12002，19，6： | 1 |
| 19 | Kernel-based object Tracking显示文摘 | COMANICIU D RAMESH V MEER P | | 0，，05： | 1 |
| 20 | The P-POSSUM scoring systems for predicting the mortality of neurosurgical patients undergoing craniotomy:further validation of usefulness and application across healthcare systems显示文摘 | Mercer S Guha A Ramesh V | 2013 | Indian J Anaesth2013，57，6： | 1 |
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