PREDICTION OF MORTALITY USING CLUSTERS BASED ON CLINICAL AND LAB PARAMETERS: DATA FROM 2072 PATIENTS FROM INSPIRE COHORT

BackgroundLupus is a heterogenous diseases which results in significant premature mortality. Most studies have evaluated risk factors for lupus mortality using regression models which considers the phenotype in isolation. Identifying clusters of patients on the other hand may help overcome the limitations of such analyses.ObjectivesThe objectives of this study were to describe the causes of mortality and to analyze survival across clusters based on clinical phenotype and autoantibodies in patients of the Indian SLE Inception cohort for Research (INSPIRE)MethodsOut of all patients, enrolled in the INSPIRE database till March 3st 2022, those who had <10% missing variables in the clustering variables were included in the study. The cause of mortality and duration between the recruitment into the cohort and mortality was calculated. Agglomerative unsupervised hierarchical cluster analysis was performed using 25 variables that define SLE phenotype in clinical practice. The number of clusters were fixed using the elbow and silhouette methods. Survival rates were examined using Cox proportional hazards models: unadjusted, adjusted for age at disease onset, socio-economic status, steroid pulse, CYC, MMF usage and cluster of the patients.ResultsIndian patients with lupus have significant early mortality and the majority of deaths occurs outside the hospital setting.Out of 2211 patients in the cohort, 2072 were included into the analysis. The median (IQR) age of the patients was 26 (20-33) years and 91.7% were females. There were 288 (13.1%) patients with juvenile onset lupus. The median (range) duration of follow up of the patients was 37 (6-42) months. There were 170 deaths, with only 77 deaths occurring in a health care setting. Death within 6 months of enrollment occured in in 80 (47.1%) patients. Majority (n=87) succumbed to disease activity, 23 to infections, 24 to coexisting disease activity and infection and 21 to other causes. Pneumonia was the leading cause of death (n=24). Pneumococcal infection led to death in 11 patients and SARS-COV2 infection in 7 patients. The hierarchical clustering resulted in 4 clusters and the characteristics of these clusters are represented in a heatmap (Figure-1A,B). The mean (95% confidence interval [95% CI] survival was 39.17 (38.45-39.90), 39.52 (38.71-40.34), 37.73 (36.77-38.70) and 35.80 (34.10-37.49) months (p<0.001) in clusters 1, 2, 3 and 4, respectively with an HR (95% CI) of 2.34 (1.56, 3.49) for cluster 4 with cluster 1 as reference(Figure 1C). The adjusted model showed an HR (95%CI) for cluster 4 of 2.22 (1.48, 3.22) with an HR(95%CI) of 1.78 (1.29, 2.45) for low socioeconomic status as opposed to a high socioeconomic status (Table 1).ConclusionIndian patients with lupus have significant early mortality and the majority of deaths occurs outside the hospital setting. Disease activity as determined by the traditional activity measures may not be sufficient to understand the true magnitude of organ involvement resulting in mortality. Clinically relevant clusters can help clinicians identify those at high risk for mortality with greater accuracy.Table 1.Univariate and multivariate Cox regression models predicting mortalityUnivariateMultivariateVariablesHazard ratio (95% Confidence interval)P valueHazard ratio (95% Confidence interval)P valueCluster1Reference-Reference-20.87 (0.57, 1.34)0.5320.89 (0.57, 1.38)0.59831.22 (0.81, 1.84)0.3371.15 (0.76, 1.73)0.51342.34 (1.56, 3.49)<0.0012.22(1.48, 3.22)<0.001Socioeconomic statusLower1.78 (1.29, 2.45)<0.001Pulse steroidYes1.6 (0.99, 2.58)0.051MMFYes0.71 (0.48, 1.05)0.083CYCYes1.42 (0.99, 2.02)0.052Proliferative LNYes0.99 (0.62, 1.56)0.952Date of birth age0.99 (0.98, 1.01)0.657CYC- cyclophosphamide, MMF- Mycophenolate mofetilFigure 1.A. Agglomerative clustering dendrogram depicting the formation of four clusters. B.Heatmap depicting distribution of variables used in clustering C. Kaplan-Meier curve showing the survival function across the 4 clusters[Figure omitted. See PDF]REFERENCES:NIL.Acknowledgements:NIL.Disclosure of InterestsNone eclared.

Multiple etiological factors led septicemic disease with mass mortality of fishes in freshwater reservoir of Odisha, India

A detailed investigation on mass mortality of fishes was conducted in a small tropical reservoir- Derjang (20o50'32.0"N, 85o01'14.8″E), Odisha, India. Mortality mostly occurred in Systomus sarana followed by Labeo rohita , Cirrhinus mrigala , Labeo catla , Ompok bimaculatus , Labeo calbasu and Mastacembelus armatus. During 20 days of disease occurrence in May–June 2019, a total of about 3000 kg of fish died. The clinical signs in Cyprinid group were haemorrhagic spots, ulcerative lesions, rotten and pale patches in gills due to septicemic disease whereas haemorrhagic spots were the only prominent symptoms observed in Silurid group. Bacteriological isolation and identification through conventional and molecular techniques revealed that Klebsiella pneumoniae was the most common pathogen recovered from S. sarana , C. mrigala and O. bimaculatus. Further Aeromonas hydrophila , Acinetobacter baumannii were isolated from L. rohita and L. catla respectively. The role of these pathogens for this disease outbreak in multiple fish species is discussed in perspective of environmental factors. Sudden environmental alternation by the supercyclone Fani (3rd May 2019) on the coastal part of Odisha might have played a key role to translate the aquatic bacteria into the virulent infective pathogens. In the experimental challenge study, isolated bacteria showed pathogenicity in respective hosts as that in the reservoir. Thus this further revealed both bacteria and fish specific virulency with a variation in LD 50 values. All the gram negative bacterial isolates were found to resist ampicillin and amoxicillin-clavulanic acid and most of them were TEM gene positive. However, the bacteria were found to be susceptible to the rest of the nineteen antibiotics. These findings suggested that the sudden cyclone is an enormous threat to reservoir aquaculture, and should be taken into consideration before breeding, stocking and harvesting of fishes. • Disease outbreak in reservoir during Summer, 2019 caused mass mortality of many freshwater fishes with septicemic symptoms • Klebsiella pnumoniae was the most dominating pathogen recovered, besides Aeromonas hydrophila and Acinetobacter baumannii • Sudden environmental alternation by the cyclone Fani might have played a key role to flare up the virulent pathogens. • Specificity and virulence of bacteria were found host-dependent with variable LD 50 as revealed by challenge experiments [ FROM AUTHOR] Copyright of Aquaculture is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Environmental surface disinfection monitoring by adenosine triphosphate (ATP) bioluminescence based assay in a tertiary health care setting

Introduction: Environmental surfaces in hospitals can be a possible reservoir for microorganisms. Proper cleaning and disinfection of hospital environmental surfaces has become even more crucial during this ongoing COVID-19 pandemic. Appropriate disinfection practices play a crucial role in their prevention. Objectives: This study aimed to observe the effect of monitoring of cleaning and disinfection practices using an ATP bioluminescence assay during the ongoing COVID-19 pandemic. Methods: The study was performed over a period of two and a half months in a tertiary health care centre in India. High touch surfaces were identified where cleaning with freshly prepared 1% Sodium hypochlorite was performed as a part of routine cleaning. Post cleaning of these surfaces, samples were collected and tested using Adenosine Triphosphate bioluminescence (ATP) based assay. Results: A total of 416 testing at various sites were performed during the study duration. Results were non satisfactory (> 250 RLU) at 123 sites and the testing was repeated after repeat cleaning and disinfection. All the tests except two performed following repeat disinfection were satisfactory (< 250 RLU). Decrease in ATP content (RLUs) following repeat cleaning at these 123 sites was significant (p < 0.0001). A decreasing trend in the ATP content as measured in the first reading was noted over a period of two and a half months. Conclusion: The role of monitoring cleaning and disinfection practices in healthcare settings cannot be underscored. ATP bioluminescence based assay is a rapid, easy to perform test providing early feedback which can result in an early corrective action. Though ATP bioluminescence based assay cannot specifically detect SARS-CoV-2, however, give a measure of general cleanliness. However, use of sodium hypochlorite is an EPA (Environmental Protection Agency) approved disinfectant for SARS-CoV-2 along with satisfactory hospital cleaning and disinfection practices may indirectly indicate satisfactory disinfection against SARS-CoV-2.