Clinically significant contrast induced acute kidney injury after non-emergent cardiac catheterization--risk factors and impact on length of hospital stay.

Objective: To evaluate the frequency and risk factors associated with clinically significant contrast-induced nephropathy(CIN) in patients undergoing non-emergent coronary angiography. Study Design: Descriptive study. Place and Duration of Study: The Aga Khan University Hospital, Karachi, from January 2005 to December 2007. Methodology: Case records of patients who underwent coronary angiography with a serum creatinine of ≥ 1.5 mg/dl atthe time of procedure were evaluated. Clinically significant contrast induced nephropathy (CSCIN) was defined as either doubling of serum creatinine from baseline value within a week following the procedure or need for emergency hemodialysis after the procedure.Results: One hundred and sixteen patients met the inclusion criteria. Mean age was 64.0 ± 11.5 years, 72% were males.Overall prevalence of CIN was 17% (rise of serum creatinine by ≥ 0.5 mg/dl) while that of clinically significant CIN (CSCIN) was 9.5% (11 patients). Patients with CSCIN had significantly lower left ventricular ejection fraction (p = 0.03, OR: 0.24;95% CI = 0.06 – 0.91) and higher prevalence of cerebrovascular disease (p \u3c 0.001, OR: 14.66; 95% CI = 3.30 – 65.08).Mean baseline serum creatinine was significantly higher, 3.0 ± 1.5 vs. 2.0 ± 1.1 mg/dl (p = 0.03, OR: 1.47; 95% CI =1.03 – 2.11) whereas mean GFR estimated by Cockcroft-Gault formula was significantly lower at 25 ± 7.4 vs. 41.0 ± 14.6ml/minute (p = 0.001, OR = 0.89, 95% CI = 0.84 – 0.95) at the time of procedure in patients with CSCIN. Mean length ofhospital stay was significantly higher in this group compared to those without CIN, 9.0 ± 5.1 vs. 3.0 ± 3.2 days (p = 0.001,OR = 1.31, 95% CI = 1.12 – 1.54). Multivariate analysis revealed low GFR (p = 0.001, OR = 0.88; 95% CI = 0.82 – 0.95)and low ejection fraction (p = 0.03, OR = 0.20; 95% CI = 0.04 – 0.91) to be independent factors associated withCSCIN. No significant differences were noted between the two groups in patients with hypertension, diabetes andheart failure. Conclusion: CSCIN is a significant concern in high risk groups despite prophylaxis. Patients with lower EF, cerebrovascular disease and low GFR at the time of procedure are more likely to have CIN

Non-diabetic renal disease in patients with type-2 diabetes mellitus

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease in diabetics worldwide, yet most patients with type-2 diabetes mellitus are not formally evaluated with a renal biopsy. The diagnosis is almost always based on clinical grounds. A wide spectrum of non-diabetic renal disease (NDRD) is reported to occur in patients with type-2 diabetes. It has been estimated that up to one-third of all diabetic patients who present with proteinuria are suffering from NDRD. The aim of this analysis was to evaluate the prevalence and etiology of NDRD in patients with type-2 diabetes. We retrospectively reviewed the medical records of patients with type-2 diabetes who underwent kidney biopsy on clinical suspicion of NDRD (absence of diabetic retinopathy and/or neuropathy; short duration of diabetes, i.e. less than five years) from January 2003 through December 2007 at the Aga Khan University Hospital, Karachi. Based on the biopsy findings, patients were grouped as Group-I, isolated NDRD; Group-II, NDRD with underlying DN; and Group-III, isolated DN. Of 68 patients studied, 75% were males and the mean age was 56 years. The mean duration of diabetes was nine years. Group-I included 34 patients (52%), Group-II included 11 patients (17%) and Group-III included 23 patients (31%). Among the Group-I patients, the mean age was 56 years (41-77 years). The most common NDRDs were acute interstitial nephritis (32%), diffuse proliferative glomerulonephritis (17%); membranous nephropathy (12%) and crescentic glomerulonephritis (12%). Among Group-II, the mean age was 60 years (46-71 years), and the most common lesion was interstitial nephritis superimposed on underlying DN (63% cases). Among Group-III, the mean age was 53 years (42- 80 years). The mean proteinuria was 5, 6.3 and 7.3 g/24 h of urine collection in Groups I, II and III, respectively (P = NS). The mean duration of diabetes was 7.3, 11.7 and 10.7 years in Groups I, II and III, respectively. The duration of diabetes was significantly less in Group-I compared with Group-II and Group-III (P = 0.04). Our study suggests that the prevalence of NDRD (either isolated or superimposed on underlying DN) is high in appropriate clinical settings. Performing renal biopsy in diabetics with no extrarenal end organ damage other than nephropathy helps to diagnose and treat NDRD. This is the first report from Pakistan documenting the prevalence of NDRD in patients with type-2 diabetes

Artificial intelligence–built analysis framework for the manufacturing sector: performance optimization of wire electric discharge machining system

In the era of industry 4.0, digitalization and smart operation of industrial systems contribute to higher productivity, improved quality, and efficient resource utilization for industrial operations and processes. However, artificial intelligence (AI)–based modelling and optimization analysis following a generic analysis framework is lacking in literature for the manufacturing sector thereby impeding the inclusion of AI for its potential application's domain. Herein, a comprehensive and generic analysis framework is presented depicting the key stages involved for carrying out the AI-based modelling and optimization analysis for the manufacturing system. The suggested AI framework is put into practice on wire electric discharge machining (WEDM) system, and the cutting speed of WEDM is adjusted for the stainless cladding steel material. Artificial neural network (ANN), support vector machine (SVM), and extreme learning machine (ELM) are three AI modelling techniques that are trained with meticulous hyperparameter tuning. A better-performing model is chosen once the trained AI models have undergone the external validation test to investigate their prediction performance. The sensitivity analysis on the developed AI model is performed and it is found that pulse on time (Pon) is the noteworthy factor affecting the cutting speed of WEDM having the percentage significance value of 26.6 followed by the Dw and LTSS, with the percentage significance value of 17.3 and 16.7 respectively. The parametric optimization incorporating the AI model is conducted and the results pertain to the cutting speed are 27.3% higher than the maximum value of cutting speed achieved for WEDM. The cutting speed performance optimization is realized following the proposed AI-based analysis framework that can be applied, in general, to other manufacturing systems therefore unlocking the potential of AI to contribute to industry 4.0 for the smart operation of manufacturing systems

Sustainable EDM of Inconel 600 in Cu-mixed biodegradable dielectrics: Modelling and optimizing the process by artificial neural network for supporting net-zero from industry

The properties of Nickel-based superalloy(s) like stability at extreme conditions, greater strength, etc., complicate its cutting through conventional operations. Therefore, electric discharge machining (EDM) is preferred for its accurate cutting. However, the conventional dielectric i.e., kerosene used in EDM is hydrocarbon based which generates toxic fumes and contribute to the CO2 emissions during the discharging process in EDM. This affects the operator’s health and the environment. Therefore, the potentiality of five biodegradable dielectrics has been deeply examined herein to address the said issues. Nano copper powder is also employed for uplifting the cutting proficiency of these dielectrics. A set of 15 experiments was performed via full factorial design. An artificial neural network (ANN) is constructed to model and optimize the material removal rate (MRR), surface roughness (SR), and specific energy consumption (SEC). The highest MRR (5.527 mm3 /min) was achieved in coconut oil whereas for obtaining the lowest SR, the sunflower oil at powder concentration (Cp) of 1.0 g/100 ml is the best choice. Sunflower oil also gave a 17.05% better surface finish compared to other dielectrics. Amongst the biodegradable dielectrics, olive oil consumes lowest specific energy (SEC) i.e., 264.16 J/mm3 which is 28.8% less than the SEC of other oils. Furthermore, the maximum CO2 reduction of 72.8 ± 1.4% is achieved with Olive oil in comparison to that found with kerosene in EDM. The multi-objective optimization is conducted and sunflower oil with Cp of 0.667 g/100 ml is termed out to be optimal solution. The biodegradable dielectrics have demonstrated excellent performance for EDM to support net-zero goals from the industrial sector

Spot urine protein: creatinine ratio versus 24 hour urine protein at various levels of GFR patients referred to a tertiary care hospital of Pakistan

OBJECTIVE: To determine the correlation of random single voided urine protein: creatinine ratio to twenty four hour urine protein at different levels of glomerular filtration rate (GFR) in Pakistani population. METHODS: A total of 107 patients were included in this cross section study. Patients were divided into five groups according to the GFR. Spot urine protein: creatinine ratio and 24 hour urine protein was measured by the standard methods. The correlation coefficient ( r) between the two was calculated in each group separately. RESULTS: The GFR in groups 1 to 5 was \u3e or =90, 60-89, 30-59, 15-29, and /minute/1.73 m2 respectively. In group one correlation coefficient r was 0.96, in group two r was 0.81, in group three r was 0.94, in group four r was 0.82 and in group five r was 0.80. CONCLUSION: Random single voided urine protein: creatinine ratio may be used as an alternative to 24 hour urine collection for protein at all levels of GFR in Pakistani population

Validation of bioelectrical impedance analysis for assessing dry weight of dialysis patients in Pakistan

Accurate dry weight estimation (DW) to achieve euvolemia is one of the key objectives of hemodialysis (HD). While conventionally DW is estimated by clinical examination, bioelectrical impedance analysis (BIA) has been proposed as an objective method to determine DW and has been tested extensively in the Western population. We aim to validate BIA for determining DW in a Pakistani population against the conventional clinician\u27s method. This is a single-center validation study conducted at two outpatient HD units of Aga Khan Hospital, Karachi. One hundred and forty-eight DW readings of patients who were on maintenance HD were taken both by BIA technology and by clinical assessment. The clinician was blinded to readings obtained by BIA. Data analysis was carried out using the Statistical Package for Social Sciences (SPSS) version 19. Median age of patients was 63 years (range 12-89). Nearly 54.1% of the samples were female (n = 80). Spearman\u27s correlation between the clinician\u27s estimate and BIA-derived DW showed a correlation coefficient of 0.982, which was statistically significant (

Stroke Mimics on the Stroke Unit – Temporal trends 2008–2017 at a large Norwegian university hospital

Objectives: The objective was to quantify temporal trends in stroke mimics (SM) admissions relative to cerebrovascular accidents (CVA), incidence of hospitalized SMs and characterize the SM case-mix at a general hospital's stroke unit (SU). Materials & Methods: All SU admissions (n = 11240) of patients aged 15 or older to Haukeland University Hospital between 2008–2017 were prospectively included and categorized as CVA or SM. Logistic regression was used to estimate time trends in the proportion of SMs among the admissions. Poisson regression was used to estimate time trends in age- and sex-dependent SM incidence. Results: SMs were on average younger thaan CVA patients (68.3 vs. 71.4 years) and had a higher proportion of females (53.6% vs. 44.5%). The total proportion of SM admissions was 51.0%. There was an increasing time trend in the proportion of SM admissions, odds ratio 1.150 per year (p < 0.001), but this trend appears flattening, represented by a significant quadratic time-term, odds ratio 1.009 (p < 0.001). A higher SM proportion was also associated with the time period of a Mass Media Intervention (FAST campaign) in 2014. There was also an increasing trend in SM incidence, that remains after adjusting for age, sex, and population; also, for incidence the trend appears to be flattening. Conclusions: SMs account for approximately half of the SU admissions, and the proportion has been increasing. A FAST campaign appears to have temporarily increased the SM proportion. The age- and sex-dependent incidence of SM has been increasing but appears to flatten out.publishedVersio

A rare case of Aeromonas hydrophila catheter related sepsis in a patient with chronic kidney disease receiving steroids and dialysis: a case report and review of Aeromonas infections in chronic kidney disease patients

Aeromonas hydrophila (AH) is an aquatic bacterium. We present a case of fifty-five-year-old gentleman with chronic kidney disease (CKD) due to crescentic IgA nephropathy who presented to us with fever. He was recently pulsed with methyl prednisolone followed by oral prednisolone and discharged on maintenance dialysis through a double lumen dialysis catheter. Blood culture from peripheral vein and double lumen dialysis catheter grew AH. We speculate low immunity due to steroids and uremia along with touch contamination of dialysis catheter by the patient or dialysis nurse could have led to this rare infection. Dialysis catheter related infection by AH is rare. We present our case here and take the opportunity to give a brief review of AH infections in CKD patients

B-type natriuretic peptide versus amino terminal pro-B type natriuretic peptide: selecting the optimal heart failure marker in patients with impaired kidney function

Background: The effect of impaired kidney function on B-type natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) is vague. This study was performed to examine the effect of kidney dysfunction on the afore-mentioned markers and determine appropriate cutoffs for systolic heart failure (SHF). Methods: In this cross sectional study adults with estimated glomerular filtration rate (eGFR)/min for ≥3 months were identified in consulting clinics from June 2009 to March 2010. SHF was defined as documented by a cardiologist with ejection fraction of \u3c 40% and assessed by New York Heart Association classification (NYHA). Plasma was assayed for creatinine (Cr), BNP and NT-proBNP. Results: A total of 190 subjects were enrolled in the study, 95 with and 95 without SHF. The mean age of patients was 58 (±15) years, 67.4% being males. Mean BNP levels showed a 2.5 fold and 1.5 fold increase from chronic kidney disease (CKD) stage 3 to stage 5 in patients with and without SHF respectively. NT-proBNP levels in non-heart failure group were 3 fold higher in CKD stage 5 compared to stage 3. Mean NT-proBNP levels were 4 fold higher in CKD stage 5 compared to stage 3 in patients with SHF. Optimal BNP and NT-proBNP cutoffs of SHF diagnosis for the entire CKD group were 300 pg/ml and 4502 pg/ml respectively. Conclusion: BNP and NT-proBNP were elevated in kidney dysfunction even in the absence of SHF; however the magnitude of increase in NT-proBNP was greater than that of BNP. BNP and NT-proBNP can be useful in diagnosing SHF, nonetheless, by using higher cutoffs stratified according to kidney dysfunction. NT-proBNP appears to predict heart failure better than BNP

Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach

The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicates the achievement of accurately machined profiles. Therefore, the proficiency of deep cryogenically treated (DCT) copper (Cu) and brass electrodes under modified dielectrics has been thoroughly investigated to address the issue. A complete factorial design was implemented to machine a 300 μm deep impression on IN617. The machining ability of DCT electrodes averagely gave better dimensional accuracy as compared to non-DCT electrodes by 13.5% in various modified dielectric mediums. The performance of DCT brass is 29.7% better overall compared to the average value of overcut (OC) given by DCT electrodes. Among the non-treated (NT) electrodes, the performance of Cu stands out when employing a Kerosene-Span-20 modified dielectric. In comparison to Kerosene-Tween-80, the value of OC is 33.3% less if Kerosene-Span-20 is used as a dielectric against the aforementioned NT electrode. Finally, OC’s nonlinear and complex phenomena are effectively modeled by an artificial neural network (ANN) with good prediction accuracy, thereby eliminating the need for experiments