Objectives: To assess the extent of Blood Request Forms (BRFs) usage in routine blood banking, at a major Hospital in Lahore. Study Design: Cross-sectional Descriptive study. Setting: Shaikh Zayed Medical Complex Blood Bank, Lahore. Period: 6 months (Sept 2016 to March 2017). Material & Methods: A total of 1052 BRFs dispatched from in-patient of Shaikh Zayed Medical Complex, Lahore were selected. Patient’s MR number, date, demographic information, diagnosis, ward, history of transfusions, type of blood transfused, phlebotomist’s name etc., were analyzed. They were assessed and the results were produced in tabulated form as well as in graph. Results: Among the 1052 BRFs, “MR number” was filled in 99.4% (n=1046) forms, while 0.6% (n=6) were not filled. The column of “Date” was filled in 97% (n=1020) forms, while it was left blank in 3% (n=32) forms. Similarly, the column of “Age” was filled in 97.7% (n=1028) forms, whereas it was left empty in 2.3% (n=24) forms. Demographic information like “Patient’s Name” and “Gender” were filled in 100% forms. “Ward” was filled in 97.1% (n=1022) forms, while 2.9% (n=30) were unfilled. As far as “H/O previous transfusion(s)” column is concerned, 40.9% (n=430) forms were filled and 59.1% (n=622) were left unfilled. “H/O previous transfusion reaction(s)” column had almost the similar number with 37.6% (n=396) filled and 62.4% (n=656) left empty. The column of “Diagnosis” was filled in 22.4% (n=236) and was found unfilled in 77.6% (n=816). Moreover, the column of “Which type of component transfused” was filled in 96% (n=1010), while 4% (n=42) were unfilled. The column of “Amount of blood needed” was filled in 96.4% (n=1014) forms, while 3.6% (n=38) forms were unfilled. “When is the blood needed” column had only 29.3% (n=308) filled forms, whereas 70.7% (n=744) forms did not mention when the blood was needed. One of the most important columns is “Patient’s blood group”, which was filled in only 53.4% (n=562) forms, while 46.6% (n=490) forms were left empty. The column of “Name of phlebotomist” was filled in only 13.9% (n=146), while 86.1% (n=906) of the forms were found unfilled in this column. In total, our study revealed that among 1052 BRFs, only 6.8% (n=72) werecompletely filled, while 93.2% (n=980) were incompletely filled. Conclusion: Lack of awareness in BRF filling should be properly addressed to enhance efficiency and to reduce pre-analytical errors in healthcare setups. It is of utmost need that the clinicians and nurses should be made aware that BRFs play a pivotal role in smooth and error-free functioning of the healthcare setups.
Background: Mucin 1 (MUC1) is overexpressed in almost 90% of CA breast cases and is usually associated with poor prognosis. On the other hand, HER2 is profoundly expressed in breast carcinoma and is also linked with increased disease recurrence, tumor invasion and poor prognosis. Thus, this study was designed to assess the expression of MUC1 and HER2 against the histological grades of breast carcinoma in our population. Materials and methods: It was a cross sectional analytical study conducted at Post Graduate Medical Institute/General Surgery Departments of Lahore General Hospital (LGH), Lahore. Duration of study was 12 month from 27-3-2018 to 30-3-2019. Total 60 newly diagnosed cases of CA breast were included in the study. Immunohistochemistry technique was used and MUC1 and HER2 markers were applied to check the probable association between the two markers and the histological grades of cancer. Results: A total of 60 cases were included in the study, out of which 96.7% (n=58) were invasive ductal carcinoma, while 3.3% (n=2) were Invasive lobular carcinoma. Among the total, 60% (n=36) were found positive for MUC1 (moderate/strong) and 40% (n=24) were found negative (negative/weak). Regarding HER2, 26.7% (n=16) were strong positive, 20% (n=12) were at the borderline/equivocal and 53.3% (n=32) were found negative for HER 2. Conclusion: Statistically significant association was found between MUC1 and HER2 against the histological grades of breast cancer patients (p <0.05).
Objectives: To provide awareness to the pathologists and technologists all about the red cells parameters in cold antibodies concerned cases. Case Report Findings: A sixty seven-years-old male admitted in emergency department of our hospital, having clinical history of swelling and pain in both the lower limb and feet, on physical examination, provisionally diagnosed as a case of Cellulitis and deep vein thrombosis(DVT). Blood specimen was obtained for general hematological investigations. Full blood count (FBC) was performed on sysmex XP-100 hematological analyzer which showed invalid findings especially red cells indices which were not corresponding to the hemoglobin (Hb) concentration of the patient. Blood sample was repeated, to confirm invalid red cells indices which showed values as in the 1st blood specimen. Blood smears revealed aggregation of red cells. By warming the ethylenediamine tetra-acetic acid (EDTA) tube containing the blood specimen, in water bath at 37⁰C for one hour and repeated the FBC on hematological analyzer and found the corrected red cells indices. Conclusion: Basic knowledge of cold antibodies and warming the blood sample at 37⁰c for one hour helps the correct diagnosis.
Objective: To see the prevalence and risk factors for post full vaccination (Sinopharm and Sinovac COVID-19 vaccines) weak immunity in persons with no history of viral exposure. Study Design: Prospective Observational. Setting: Syed Research Centre, Sialkot. Period: Nov 2021 to Feb 2022. Material & Methods: Eighty two individuals (male/female, aged: 24-70 years) were enrolled from District Sialkot (Pakistan). Two doses of Sinopharm or Sinovac COVID-19 vaccine were administered to each participant before blood sampling. The quantity of COVID-19 spike immunoglobulin G against SARS-CoV-2 (5-Antigen) was detected in serum using chemiluminescence immunoassay technique [threshold titer: 7.1 (detection), 105. 63 (seroprotection), 492.96 BAU/mL (strong humoral response)]. Results: Overall, 96.3% seropositivity, 89% seroprotection, and 37.8% (n = 31) weak immune response were recorded. Whereas, mean antibody titer was found to be 2312.02 (range: 0.0 – 28711.74) BAU/mL. A vaccinated male had approximately 4 folds (95%CI: 1.297 – 11.504; p = .002) more likelihood of weak immune response than females. Similarly, the rate of poor immunological outcome was higher in individuals with >24.9 Kg/m2 (69.2%, n = 27) body mass index compared to ≤24.9 Kg/m2. A person with Sinopharm COVID-19 vaccine was more vulnerable to weak immune response than Sinovac vaccinated participants (RR = 2.351; 95%CI = 1.327 – 4.167; p .002; 57.6% vs. 24.5%, respectively). Co-occurrence of age (>47 years) and BMI (>24.9 Kg/m2) existed in 11 of 28 males (39.3%) with impaired immunogenicity. Conclusion: The high rate of post full vaccination weak immune response is alarming. Gender, BMI, and vaccine type were amongst the predictors for diminished humoral response.
Objective: To see the prevalence and potential predictors for side effects of Sinopharm and Sinovac COVID-19 vaccines among students of medical, and BS human nutrition and dietetics courses. Study Design: Cross-sectional Proforma-derived. Setting: Sialkot Medical College, Sialkot, Pakistan. Period: July and August, 2021. Material & Methods: Fifty students (MBBS = 30; Dietetics course = 20) with at least one dose of Sinopharm or Sinovac COVID-19 vaccine were recruited, purposively. The subjects were asked to report in an indigenously designed proforma on adverse effects using recall methodology for open time. Results: Forty nine subjects gave complete responses in the proforma. The rate of adverse effects increased from 75% (n = 3) against Sinopharm to 100% (n = 9) against Sinovac vaccine among 13 students of Dietetics who had only 1st dose. For rest of the 36 participants, the rate was found, as: 76.5% (n = 13) against each of the 1st and 2nd dose of Sinopharm; 78.9% (n = 15) against 1st and 68.4 (n = 13) against 2nd doses of Sinovac vaccine. The frequency of different adverse effects per individual ranged 1-3 (Sinopharm) or 1-4 (Sinovac). Whereas, lower rate of injection site pain was recorded on 1st dose of Sinopharm than Sinovac (52.9 vs 57.9%, respectively). None of the variables was noted as potential predictor for the side effects (p >.05). Conclusion: Sinopharm, and Sinovac COVID-19 vaccines exhibit almost similar prevalence of self-manageable side effects. Moreover, there is no predictor for the effects.
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