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Introduction: Bacterial Meningitis (BM) is a serious health problem worldwide with high mortality and permanent longterm neurological sequelae. Cerebrospinal Fluid (CSF) analysis is the cornerstone for diagnosing BM, but the lack of specificity creates a difficult clinical scenario for initiating proper treatment. Empiric antibiotic use in patients with suspected meningitis at primary care settings decreases the yield of CSF culture and alters CSF cytological and biochemical findings, making it further difficult to diagnose BM. To overcome this difficulty, there is a need for other biochemical markers with higher sensitivity and specificity. Aim: To determine the diagnostic sensitivity and specificity of Procalcitonin (PCT) in serum and CSF in patients with BM and compare its diagnostic accuracy in both sample types. Materials and Methods: A cross-sectional study was conducted in the Department of Internal Medicine at a tertiary care centre in eastern India from September 2018 to August 2020. A total of 82 adult patients with meningitis were recruited as per the protocol, and CSF analysis was done along with estimation of PCT in serum and CSF. Receiver Operating Characteristics (ROC) curve analysis of serum and CSF PCT was used to determine sensitivity and specificity with a 95% confidence interval. Results: Out of the 82 patients recruited, 30 (36.6%) had BM. CSF PCT with a cut-off value of >0.45 ng/mL had a sensitivity of 86.7% and specificity of 92.3%. The sensitivity of serum PCT with a cut-off value of >0.6 ng/mL was 83.3%, and specificity was 86.5%. There was no statistically significant difference in sensitivity and specificity between CSF and serum PCT in patients with BM (p-value=0.7988). Conclusion: Both serum and CSF PCT were found to have high sensitivity and specificity as markers for diagnosing BM without any statistically significant difference between them. [ABSTRACT FROM AUTHOR]

Introduction: Clinical laboratories play an indispensable role in patient care. Laboratory results help in approximately 70% of medical decision making. Patients are the best source of information on quality of service provided by an Institute, as their feedback can help in future planning and taking corrective action. Aim: To evaluate patient satisfaction with clinical laboratory and phlebotomy services in a National Accreditation Board for Testing and Calibration Laboratories (NABL) accredited laboratory in a tertiary care hospital in Eastern India. Materials and Methods: This was a hospital-based cross-sectional study, conducted from May 2021 to June 2021, on the patients visiting the central laboratory of Kalinga Institute of Medical Sciences (KIMS), Bhubaneswar, Odisha. A total of 265 participants above the age of 18 years were included in the study. They were provided with a feedback questionnaire (13 questions). A 5-point Likert scale rating of very dissatisfied, dissatisfied, neutral, satisfied and very satisfied was used. Descriptive statistics such as number and percentage were used to present the data. Results: Out of the total, 96% was the response rate, hence, the complete questionnaires analysed were of 254 participants (130 males and 124 females). Out of the total 254 participants, 155 (61%) were very satisfied, 61 (24%) were satisfied, 28 (11%) were neutral and 10 (3.93%) were dissatisfied with the overall laboratory services. Laboratory test results were reliable scored very high and was reported to be very satisfactory by 177 participants (69.68%), satisfactory by 51 participants (20.07%) and 165 participants (64.96%) were very satisfied and 58 participants (22.83%) were satisfied with staff courtesy, skill and behaviour. However, none of the participants were very dissatisfied and 10 (4%) were dissatisfied, expected the laboratory services to be little better. For explanation of test results 79 participants (31.10%) were very dissatisfied and another 114 participants (44.88%) were dissatisfied. A total of 34 participants (13.38%) were very dissatisfied and another 50 participants (19.68%) were dissatisfied with the given information about location and time of report collection. Conclusion: Patient satisfaction is an important indicator of the quality of service delivered. The overall satisfaction level with the laboratory service was 85%, showing a majority of the participants were satisfied or very satisfied with the overall services of the laboratory. There is a need to improve on cleanliness and more emphasis is to be laid, on transmission of accurate and adequate information to the patients. [ABSTRACT FROM AUTHOR]

Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was hemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), turnaround time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. turnaround time (TAT) was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase. [ABSTRACT FROM AUTHOR]