The Pattern of Dyslipidemia in Chronic Liver Disease Patients.

Introduction Patients with chronic liver disease are expected to report derangements in serum lipid profiles. Lipid profile monitoring is not a part of the routine management of these patients in our hospital. Few recent studies show how lipid profile varies with the severity of disease and should be considered in the management planning of such patients. The objective of this study was to determine the pattern of dyslipidemia in chronic liver disease patients. Materials and methods A cross-sectional study was conducted involving 171 patients of all genders aged between 18 years and 60 years presenting with chronic liver disease with disease severity graded on Child-Pugh class as A, B, and C. Lipid profile was acquired in all these patients and was compared across various subgroups. Individual serum lipid parameters were graded as normal, high, or very high. Each patient was required to provide written informed consent. Statistical Package for Social Sciences (SPSS) version 21.0 (IBM Corp. Armonk, NY) was used to analyze data statistically, taking a p-value of ≤0.05 as significant. Results The mean age of patients was 51.2±7.3 years. The male to female ratio came out to be 1.5:1, with 103 (60.2%) male and 68 (39.8%) female patients included in the study. The disease was classified as Child-Pugh A in 20 (11.7%) patients, Child-Pugh B in 67 (39.2%) patients, and Child-Pugh C in 84 (49.1%) patients. Forty-four (25.7%) patients were hypertensive while 62 (36.3%) were diabetic. The mean body mass index (BMI) of these patients was 25.9±2.4 kg/m2. Mean serum values among Child-Pugh A, Child-Pugh B, and Child-Pugh C of low-density lipoproteins (LDL) (113.15±14.08 vs. 95.58±14.25 vs. 53.46±5.90 mg/dl; p-value 0.001), high-density lipoproteins (HDL) (50.60±3.19 vs. 40.70±2.95 vs. 35.40±3.88 mg/dl; p-value 0.001), total cholesterol (174.20±17.33 vs. 164.00±17.82 vs. 128.64±24.73 mg/dl; p-value 0.001), and triglycerides (127.15±8.98 vs. 100.84±27.12 vs. 93.36±25.56 mg/dl; p-value 0.001) decreased significantly with increasing severity of disease. Nineteen (11.1%) patients had hyperlipidemia (serum values of two or more parameters above normal) while 152 (88.9%) patients had normal lipid profile. When stratified, no statistically significant difference was found in the frequency of hyperlipidemia across various subgroups based on the patient's gender, age, duration, and severity of the disease, BMI, or diabetic and hypertensive status. Conclusions A substantial proportion of patients with chronic liver disease had hyperlipidemia which varied with the severity of disease on Child-Pugh classification. Routine monitoring of the lipid profile of such patients is necessary for timely identification and management of dyslipidemia to improve the outcome of such patients. It also suggests an important role of lipid profile in the risk stratification and treatment of chronic liver disease patients and warrants further studies in this regard.

Coronavirus Disease 2019-Related Acute Ischemic Stroke: A Case Report.

Coronavirus disease 2019 (COVID-19) is an active worldwide pandemic with diverse presentations and complications. Most patients present with constitutional and respiratory symptoms. Acute ischemic stroke remains a medical emergency even during the COVID-19 pandemic. Here we present a case of a patient with COVID-19 who presented with acute ischemic stroke in the absence of common risk factors for cerebrovascular accidents. A 70-year-old male patient, with no prior comorbidities, presented to the emergency department (ED) with fever, cough, and shortness of breath for four days, and altered level of consciousness and right-sided weakness with the sensory loss for one day. On examination, the patient had a score of 8/15 on the Glasgow coma scale (GCS). There was a right-sided sensory loss and weakness in both upper and lower limbs with a positive Babinski's sign. The pulmonary examination was remarkable for bilateral crepitation. On blood workup, there was leukocytosis and raised c-reactive protein (CRP). D-dimer, ferritin, thyroid-stimulating hormone (TSH), vitamin B12, and hypercoagulability workup were normal. Transthoracic echocardiography was also normal. COVID-19 polymerase chain reaction (PCR) detected the virus. Chest x-ray showed infiltrations in the left middle and both lower zones of the lungs in the peripheral distribution. Computed tomography (CT) scan of the chest showed peripheral and mid to basal predominant multilobar ground-glass opacities. CT scan of the head showed a large hypodense area, with a loss of gray and white matter differentiation, in the left middle cerebral artery territory. Magnetic resonance imaging (MRI) of the head showed abnormal signal intensity area in the left parietal region. It appeared isointense on T1 image and hyperintense on T2 image. It also showed diffusion restriction on the diffusion-weighted 1 (DW1) image with corresponding low signals on the apparent diffusion coefficient (ADC) map. These findings were consistent with left middle cerebral artery territory infarct due to COVID-19. The patient was intubated in the ED. He was deemed unfit for thrombolysis and started on aspirin, anti-coagulation, and other supportive measures. Patients with COVID-19 should be evaluated early for neurological signs. Timely workup and interventions should be performed in any patient suspected of having a stroke to reduce morbidity and mortality.

Validity of National Institutes of Health Stroke Scale for Severity of Stroke to Predict Mortality Among Patients Presenting With Symptoms of Stroke.

Introduction Cerebrovascular accident (CVA), also termed as stroke, is the third leading cause of mortality and the most common cause of disability globally. The National Institutes of Health Stroke Scale (NIHSS) is a valid assessment tool utilized to determine the severity of the stroke and can be used to prioritize patients to design treatment plans, rehabilitation, and better clinical outcomes. The primary objective of this study was to determine the validity of the NIHSS to predict mortality among patients presenting with symptoms of a stroke. Material and methods This was a descriptive case-series conducted over a period of six months between September 2019 and February 2020 at a tertiary care hospital in Nawabshah, Pakistan. The sample population included 141 patients admitted within 24 hours of the onset of symptoms of a stroke. A neurological examination of the patients was performed. On admission, stroke severity was evaluated with the NIHSS. After an initial clinical evaluation, patients underwent a non-enhanced computed tomography (CT) scan of the brain. The score of NIHSS and mortality at 72 hours were recorded on the pre-defined proforma by the investigators. All statistical analysis was performed using Statistical Package for Social Sciences (SPSS) version 23.0 (Armonk, NY: IBM Corp). Results The mean age of the participants was 52.37±8.61 years. 68.1% of patients were hypertensive, 29.1% were diabetic, and 36.9% of patients were found with hyperlipidemia. The mortality rate was 41.1%. The mean NIHSS score was 16.68±6.72 points. The findings of this study demonstrated that the score of 14.9% cases was good (0-6 points), the score of 29.1% cases was moderate (7-15 points), and the score of 56% cases was poor (≥16 points). There was a significant association of NIHSS score with mortality (p<0.001). Conclusions Baseline NIHSS score has a profound association with mortality after acute stroke. It can help clinicians decide whether to provide thrombolytic treatment, rehabilitation or a combination of both in these patients and decrease the mortality rate. However, more studies are needed to potentiate these conclusions.

Correlation of Hemoglobin A1c With Wagner Classification in Patients With Diabetic Foot.

Introduction Diabetic foot is a common complication of diabetes mellitus (DM). The Wagner classification is mostly used to grade its severity. The correlation between the hemoglobin A1c (HbA1c) and the Wagner classification is still controversial. Therefore, the purpose of this study is to determine the correlation of HbA1c with Wagner classification in patients with diabetic foot. Materials and methods This cross-sectional study was conducted at a major hospital in Shaheed Benazirabad in which 88 patients aged 18-65 years, of either gender, with a known history of DM type I or type II, and diagnosed with diabetic foot were enrolled for six months. Blood samples were collected to check the HbA1c levels. Wagner classification grading was performed after the examination of diabetic foot ulcers. Demographics such as age, gender, duration of DM, and other risk factors of foot ulcers were also noted. The mean and standard deviation for continuous variables, such as age and HbA1c level, and the frequency and percentage for categorical variables, such as distribution of age, distribution of HbA1c, gender, duration of DM, grades of Wagner classification, and other risk factors of foot ulcers, were calculated. The correlation of HbA1c with Wagner classification was also calculated by applying the chi-square test and taking p ≤ 0.05 as significant. Results The mean age of the study population was 47.4 ± 10.6 years. Of the 88 patients, 15 (17.04%) were 25-35 years of age, 34 (38.63%) were 36-50 years of age, and 39 (44.31%) were 51-65 years of age; 45 (51.13%) patients were males and 43 (48.86%) patients were females. The mean HbA1c level of the study population was 9.07 ± 1.65%; 5 (5.68%) patients had 6.5-7.5%, 34 (38.63%) patients had 7.6-8.5%, 24 (27.27%) patients had 8.6-9.5%, and 25 (28.41%) patients had an HbA1c level of >9.5%. Twelve (13.63%) patients had ≤ 7 years, 18 (20.45%) had 8-15 years, and 58 (65.9%) had >15 years of duration of DM. Zero (0%) patients had grade 0, 1 (1.13%) patient had grade 1, 6 (6.81%) patients had grade 2, 29 (32.95%) patients had grade 3, 32 (36.36%) patients had grade 4, and 20 (22.72%) patients had grade 5 of Wagner classification. 23 (26.13%) patients had foot abnormalities, 19 (21.59%) patients had nephropathy, 13 (14.77%) patients had neuropathy, 14 (15.91%) patients had hypertension, 9 (10.22%) patients had retinopathy, 3 (3.41%) patients had foot ulcers/toe amputation, 2 (2.27%) patients had a cognitive deficit, and 5 (5.68%) patients had cardiovascular diseases. The correlation of HbA1c with Wagner classification was found statistically significant with p < 0.00001. Conclusions The older age, male gender, longer duration of DM, increased HbA1c, and previously existing foot abnormalities in diabetic patients are the risk factors of diabetic foot. The monitoring of HbA1c can help predict the diabetic foot in the aforesaid high-risk diabetics because the HbA1c linearly rises with the higher grades of Wagner classification of diabetic foot. Subsequently, the strict control of HbA1c as well as patient education about proper foot care can help prevent diabetic foot and its complications. However, more studies on larger scales are needed to establish the factual relationship between HbA1c and Wagner classification.