Regional Institute of Medical Sciences

Trematode species belonging to the genus Paragonimus are the source of the food-borne parasitic zoonosis known as paragonimiasis. The disease has been identified as an outbreak in northeastern India since the early 1980s and is frequently diagnosed as tuberculosis because of similar clinical and radiological findings. This study is an attempt to update the clinic-radiological features and geographical distribution of the disease in recent times.

We retrospectively collected and analysed the data of 37 paragonimiasis suspected cases attending three healthcare facilities in Manipur from 2011 to 2023. Clinical data, history of food habits and geographical location, and laboratory data were retrieved and analysed. In the microbiology laboratory, sputum and pleural fluid examination were subjected to microbiological examination and serological testing using DIGFA, an immunochromatographic dot blot rapid test.

Out of 37 cases, 32 cases were confirmed to be paragonimiasis. Clinical manifestations were pleural effusion (n = 11), cerebral with pulmonary (n = 1), cutaneous (n = 1), and pulmonary (n = 19). All patients had a history of consuming crabs. Thirteen cases were pediatric patients, representing 40.6 %. At the time of presentation, 22 cases (68.75 %) were clinically suspected to be TB, and 16 (50 %) of them were already receiving anti-TB drugs. The patients were treated with oral praziquantel, 25 mg/kg of body weight, three times a day.

The disease remains a public health concern in Manipur, as evidenced by the identification of new endemic foci. It continues to be misdiagnosed and mismanaged as tuberculosis. More awareness and a policy to examine AFB smear-negative sputum samples for paragonimiasis in patients with high eosinophil count is the need of the hour.

Background Lockdown is a state of confinement that results in changes to the environmental factors that otherwise help entrain to circadian rhythm, and hence the need arises to understand the changes to various physiological factors during lockdown. Methodology A cross-sectional questionnaire-based study was conducted using snowball sampling, including people residing in Northeast India. A chi-square test was applied for the association between variables. A two-tailed Z test was done to analyze significant changes between two proportions. Result The final sample size was 992, and the mean age was 27.38 ± 10.887 years. A significant delay in bedtime (P = 0.0271), an increase in sleep latency (P = 0.0083), screen time duration (P = 0.0293), daytime sleep (P = 0.0155), and restfulness of sleep (P < 0.00001), as well as a decrease in sleep without awakening (P = 0.0001), were observed during lockdown compared to before the lockdown. In subjects sleeping beyond 1 AM, a significant decrease in restfulness (P = 0.00084) and an increase in sleep latency of more than one hour (P = 0.00528) were observed. An increase in water intake (508, 52%), fruit juice consumption (452, 46.1%), vegetable consumption (516, 52.9%), snacking (515, 52.8%), and body weight (447, 46.3%), along with a decrease in junk food consumption (527, 54.5%), were observed during lockdown. A significant decrease in alcohol consumption was observed during (P = 0.00338) and after (P = 0.03572) the lockdown. Breakfast timing was delayed in 395 individuals (40.5%), with a significant delay noted in those sleeping beyond 1 AM (P = 0.00634). A significant decrease in the frequency of lower stool passage (P = 0.01314) and a reduction in formed stools (P = 0.01016), along with a decrease in morning defecation (P = 0.0001), were observed. A significant decrease in morning defecation was observed in those sleeping beyond 1 AM (P = 0.01208). The changes in restfulness, sleep disturbance, screen time duration, sleep latency, defecation timing, and alcohol consumption observed during lockdown persisted even after the lockdown. Conclusions The most significant changes were seen for sleep. Changes in diet were inclined toward positive health. Sleeping beyond 1 AM, however, predisposed to longer latency of sleep, reduction in restfulness of sleep, and delayed breakfast and defecation time. Some of the changes observed during lockdown persisted even after the relaxation of restrictions.

Background Patients undergoing maintenance hemodialysis (HD) are exposed to large volumes of treated water, making its microbiological quality crucial for patient safety. Contaminated dialysis water can introduce microbial pathogens into the bloodstream, increasing the risk of pyrogenic reactions, sepsis, and chronic inflammation. Water quality monitoring remains a challenge in many healthcare settings despite its importance. This study evaluates the microbiological quality of treated water and dialysate used in a tertiary care hospital dialysis unit in Imphal, India. Methods This observational study was conducted at the Regional Institute of Medical Sciences, Imphal, from August 2021 to January 2025. A total of 84 water samples were collected from different points in the dialysis system, including product water, storage water, middle port water, and return water. Samples were processed using membrane filtration and analyzed for microbial contamination using culture-based methods and Vitek 2 Compact for species identification. The findings were assessed against the Association for the Advancement of Medical Instrumentation (AAMI) standards for dialysis water quality.  Results Microbiological analysis revealed varying contamination levels across different water sources. Product water exhibited the highest microbial presence, with Acinetobacter species being the most frequently detected organism. The most recent sample (January 2025) showed Aeromonas spp. and Acinetobacter spp. in product water. Some samples exceeded AAMI standards, with colony-forming unit (CFU) counts ranging from 104 to 274 CFU/100 mL in product water. Storage, middle port, and return water showed lower contamination levels. Out of the total 21 samples collected, unsatisfactory microbial growth was observed in three samples of product water and one sample of storage water as per AAMI standard, whereas no unsatisfactory growth was detected in any of the middle port water or return water samples. Acinetobacter baumannii was detected in all four water types, while other multidrug-resistant organisms, such as Klebsiella pneumoniae, were found in return water. Conclusion The study highlights fluctuating levels of microbial contamination in dialysis water, with Acinetobacter species being the predominant contaminant. Regular monitoring, stringent adherence to water treatment protocols, and strict infection control measures are essential to ensure dialysis water safety and improve patient outcomes.