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Article: Long-term survival following medical management of

Kulirankal, Kiran G / Mary, Ann / Moni, Merlin / Pillai, Gopal S / Sathyapalan, Dipu T

2024 Volume 43, Page(s) 100638

Abstract: A male in his 40's with no known comorbidities developed severe COVID-19 pneumonia and received a four-week course of methylprednisolone. The patient subsequently developed ... ...

Abstract	A male in his 40's with no known comorbidities developed severe COVID-19 pneumonia and received a four-week course of methylprednisolone. The patient subsequently developed disseminated
Language	English
Publishing date	2024-03-01
Publishing country	Netherlands
Document type	Case Reports
ZDB-ID	2670415-8
ISSN	2211-7539
ISSN	2211-7539
DOI	10.1016/j.mmcr.2024.100638
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Penicilliosis in a Non-HIV Patient: A Case Report.

Hakeem, Sai Chandra / Kulirankal, Kiran G / Mary, Ann / Moni, Merlin / Sathyapalan, Dipu T

Cureus

2023 Volume 15, Issue 4, Page(s) e37484

Abstract: A 68-year-old female, with a known case of mantle cell lymphoma, came with complaints of persistent cough with expectoration for three months, not responding to multiple courses of antibiotics. Bronchoscopy was done and bronchoalveolar lavage (BAL) ... ...

Abstract	A 68-year-old female, with a known case of mantle cell lymphoma, came with complaints of persistent cough with expectoration for three months, not responding to multiple courses of antibiotics. Bronchoscopy was done and bronchoalveolar lavage (BAL) culture revealed
Language	English
Publishing date	2023-04-12
Publishing country	United States
Document type	Case Reports
ZDB-ID	2747273-5
ISSN	2168-8184
ISSN	2168-8184
DOI	10.7759/cureus.37484
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Article ; Online: Characterization and predictive risk scoring of long COVID in a south indian cohort after breakthrough COVID infection; a prospective single centre study.

Nair, Pranav / Nair, Chithira V / Kulirankal, Kiran G / Corley, Elizabeth M / Edathadathil, Fabia / Gutjahr, Georg / Moni, Merlin / Sathyapalan, Dipu T

BMC infectious diseases

2023 Volume 23, Issue 1, Page(s) 670

Abstract: Background: With the World Health Organization (WHO) declaring an end to the COVID-19 pandemic, the focus has shifted to understanding and managing long-term post-infectious complications. "Long COVID," characterized by persistent or new onset symptoms ... ...

Abstract	Background: With the World Health Organization (WHO) declaring an end to the COVID-19 pandemic, the focus has shifted to understanding and managing long-term post-infectious complications. "Long COVID," characterized by persistent or new onset symptoms extending beyond the initial phase of infection, is one such complication. This study aims to describe the incidence, clinical features and risk profile of long COVID among individuals in a South Indian cohort who experienced post-ChAdOx1 n-Cov-2 vaccine breakthrough infections. Methods: A single-centre hospital-based prospective observational study was conducted from October to December 2021. The study population comprised adult patients (> 18 years) with a confirmed COVID-19 diagnosis who had received at least a single dose of vaccination. Data was collected using a specially tailored questionnaire at week 2, week 6, and week 12 post-negative COVID-19 test. A propensity score based predictive scoring system was developed to assess the risk of long COVID. Results: Among the 414 patients followed up in the study, 164 (39.6%) reported long COVID symptoms persisting beyond 6 week's post-infection. The presence of long COVID was significantly higher among patients above 65 years of age, and those with comorbidities such as Type II Diabetes Mellitus, hypertension, dyslipidemia, coronary artery disease, asthma, and cancer. Using backwards selection, a reduced model was developed, identifying age (OR 1.053, 95% CI 0.097-1.07, p < 0.001), hypertension (OR 2.59, 95% CI 1.46-4.59, p = 0.001), and bronchial asthma (OR 3.7176, 95% CI 1.24-11.12, p = 0.018) as significant predictors of long COVID incidence. A significant positive correlation was observed between the symptomatic burden and the number of individual comorbidities. Conclusions: The significant presence of long COVID at 12 weeks among non-hospitalised patients underscores the importance of post-recovery follow-up to assess for the presence of long COVID. The predictive risk score proposed in this study may help identify individuals at risk of developing long COVID. Further research is needed to understand the impact of long COVID on patients' quality of life and the potential role of tailored rehabilitation programs in improving patient outcomes.
MeSH term(s)	Adult ; Humans ; Post-Acute COVID-19 Syndrome ; COVID-19/epidemiology ; COVID-19 Testing ; Diabetes Mellitus, Type 2 ; Pandemics ; Prospective Studies ; Quality of Life ; Asthma ; Breakthrough Infections ; Hypertension
Language	English
Publishing date	2023-10-09
Publishing country	England
Document type	Observational Study ; Journal Article
ZDB-ID	2041550-3
ISSN	1471-2334 ; 1471-2334
ISSN (online)	1471-2334
ISSN	1471-2334
DOI	10.1186/s12879-023-08600-6
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Article ; Online: Incidence and Characterization of Post-COVID-19 Symptoms in Hospitalized COVID-19 Survivors to Recognize Syndemic Connotations in India: Single-Center Prospective Observational Cohort Study.

Nair, Chithira V / Moni, Merlin / Edathadathil, Fabia / A, Appukuttan / Prasanna, Preetha / Pushpa Raghavan, Roshni / Sathyapalan, Dipu T / Jayant, Aveek

JMIR formative research

2023 Volume 7, Page(s) e40028

Abstract: Background: Long COVID, or post-COVID-19 syndrome, is the persistence of signs and symptoms that develop during or after COVID-19 infection for more than 12 weeks and are not explained by an alternative diagnosis. In spite of health care recouping to ... ...

Abstract	Background: Long COVID, or post-COVID-19 syndrome, is the persistence of signs and symptoms that develop during or after COVID-19 infection for more than 12 weeks and are not explained by an alternative diagnosis. In spite of health care recouping to prepandemic states, the post-COVID-19 state tends to be less recognized from low- and middle-income country settings and holistic therapeutic protocols do not exist. Owing to the syndemic nature of COVID-19, it is important to characterize post-COVID-19 syndrome. Objective: We aimed to determine the incidence of post-COVID-19 symptoms in a cohort of inpatients who recovered from COVID-19 from February to July 2021 at a tertiary-care center in South India. In addition, we aimed at comparing the prevalence of post-COVID-19 manifestations in intensive care unit (ICU) and non-ICU patients, assessing the persistence, severity, and characteristics of post-COVID-19 manifestations, and elucidating the risk factors associated with the presence of post-COVID-19 manifestations. Methods: A total of 120 adult patients admitted with COVID-19 in the specified time frame were recruited into the study after providing informed written consent. The cohort included 50 patients requiring intensive care and 70 patients without intensive care. The follow-up was conducted on the second and sixth weeks after discharge with a structured questionnaire. The questionnaire was filled in by the patient/family member of the patient during their visit to the hospital for follow-up at 2 weeks and through telephone follow-up at 6 weeks. Results: The mean age of the cohort was 55 years and 55% were men. Only 5% of the cohort had taken the first dose of COVID-19 vaccination. Among the 120 patients, 58.3% had mild COVID-19 and 41.7% had moderate to severe COVID-19 infection. In addition, 60.8% (n=73) of patients had at least one persistent symptom at the sixth week of discharge and 50 (41.7%) patients required intensive care during their inpatient stay. The presence of persistent symptoms at 6 weeks was not associated with severity of illness, age, or requirement for intensive care. Fatigue was the most common reported persistent symptom with a prevalence of 55.8%, followed by dyspnea (20%) and weight loss (16.7%). Female sex (odds ratio [OR] 2.4, 95% CI 1.03-5.58; P=.04) and steroid administration during hospital stay (OR 4.43, 95% CI 1.9-10.28; P=.001) were found to be significant risk factors for the presence of post-COVID-19 symptoms at 6 weeks as revealed by logistic regression analysis. Conclusions: Overall, 60.8% of inpatients treated for COVID-19 had post-COVID-19 symptoms at 6 weeks postdischarge from the hospital. The incidence of post-COVID-19 syndrome in the cohort did not significantly differ across the mild, moderate, and severe COVID-19 severity categories. Female sex and steroid administration during the hospital stay were identified as predictors of the persistence of post-COVID-19 symptoms at 6 weeks.
Language	English
Publishing date	2023-04-18
Publishing country	Canada
Document type	Journal Article
ISSN	2561-326X
ISSN (online)	2561-326X
DOI	10.2196/40028
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Article: Epidemiology of Community-Acquired Sepsis: Data from an E-Sepsis Registry of a Tertiary Care Center in South India.

Edathadathil, Fabia / Alex, Soumya / Prasanna, Preetha / Sudhir, Sangita / Balachandran, Sabarish / Moni, Merlin / Menon, Vidya / Sathyapalan, Dipu T / Singh, Sanjeev

Pathogens (Basel, Switzerland)

2022 Volume 11, Issue 11

Abstract: The study aims to characterize community-acquired sepsis patients admitted to our 1300-bedded tertiary care hospital in South India from the Surviving Sepsis Campaign (SSC) guideline-compliant e-sepsis registry stratified by focus of infection. The ... ...

Abstract	The study aims to characterize community-acquired sepsis patients admitted to our 1300-bedded tertiary care hospital in South India from the Surviving Sepsis Campaign (SSC) guideline-compliant e-sepsis registry stratified by focus of infection. The prospective observational study recruited 1009 adult sepsis patients presenting to the emergency department at the center based on Sepsis-2 criteria for a period of three years. Of the patients, 41% were between 61 and 80 years with a mean age of 57.37 ± 13.5%. A total of 13.5% (136) was under septic shock and in-hospital mortality for the study cohort was 25%. The 3 h and 6 h bundle compliance rates observed were 37% and 49%, respectively, without significant survival benefits. Predictors of mortality among patients with bloodstream infections were septic shock (
Language	English
Publishing date	2022-10-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2695572-6
ISSN	2076-0817
ISSN	2076-0817
DOI	10.3390/pathogens11111226
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Article ; Online: Cardiovascular risk assessment using ASCVD risk score in fibromyalgia: a single-centre, retrospective study using "traditional" case control methodology and "novel" machine learning.

Surendran, Sandeep / Mithun, C B / Moni, Merlin / Tiwari, Arun / Pradeep, Manu

Advances in rheumatology (London, England)

2021 Volume 61, Issue 1, Page(s) 72

Abstract: Background: In autoimmune inflammatory rheumatological diseases, routine cardiovascular risk assessment is becoming more important. As an increased cardiovascular disease (CVD) risk is recognized in patients with fibromyalgia (FM), a combination of ... ...

Abstract	Background: In autoimmune inflammatory rheumatological diseases, routine cardiovascular risk assessment is becoming more important. As an increased cardiovascular disease (CVD) risk is recognized in patients with fibromyalgia (FM), a combination of traditional CVD risk assessment tool with Machine Learning (ML) predictive model could help to identify non-traditional CVD risk factors. Methods: This study was a retrospective case-control study conducted at a quaternary care center in India. Female patients diagnosed with FM as per 2016 modified American College of Rheumatology 2010/2011 diagnostic criteria were enrolled; healthy age and gender-matched controls were obtained from Non-communicable disease Initiatives and Research at AMrita (NIRAM) study database. Firstly, FM cases and healthy controls were age-stratified into three categories of 18-39 years, 40-59 years, and ≥ 60 years. A 10 year and lifetime CVD risk was calculated in both cases and controls using the ASCVD calculator. Pearson chi-square test and Fisher's exact were used to compare the ASCVD risk scores of FM patients and controls across the age categories. Secondly, ML predictive models of CVD risk in FM patients were developed. A random forest algorithm was used to develop the predictive models with ASCVD 10 years and lifetime risk as target measures. Model predictive accuracy of the ML models was assessed by accuracy, f1-score, and Area Under 'receiver operating Curve' (AUC). From the final predictive models, we assessed risk factors that had the highest weightage for CVD risk in FM. Results: A total of 139 FM cases and 1820 controls were enrolled in the study. FM patients in the age group 40-59 years had increased lifetime CVD risk compared to the control group (OR = 1.56, p = 0.043). However, CVD risk was not associated with FM disease severity and disease duration as per the conventional statistical analysis. ML model for 10-year ASCVD risk had an accuracy of 95% with an f1-score of 0.67 and AUC of 0.825. ML model for the lifetime ASCVD risk had an accuracy of 72% with an f1-score of 0.79 and AUC of 0.713. In addition to the traditional risk factors for CVD, FM disease severity parameters were important contributors in the ML predictive models. Conclusion: FM patients of the 40-59 years age group had increased lifetime CVD risk in our study. Although FM disease severity was not associated with high CVD risk as per the conventional statistical analysis of the data, it was among the highest contributor to ML predictive model for CVD risk in FM patients. This also highlights that ML can potentially help to bridge the gap of non-linear risk factor identification.
MeSH term(s)	Adolescent ; Adult ; Cardiovascular Diseases/epidemiology ; Cardiovascular Diseases/etiology ; Case-Control Studies ; Female ; Fibromyalgia/epidemiology ; Heart Disease Risk Factors ; Humans ; Machine Learning ; Middle Aged ; Retrospective Studies ; Risk Assessment ; Risk Factors ; United States ; Young Adult
Language	English
Publishing date	2021-11-27
Publishing country	England
Document type	Journal Article
ISSN	2523-3106
ISSN (online)	2523-3106
DOI	10.1186/s42358-021-00229-w
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Article ; Online: Colistin (Polymyxin E) Use in Abdominal Solid Organ Transplant Recipients.

Krishnakumar, Radhika T / Asok, Amrita / Mohamed, Zubair U / Padma, Uma D / Sathyapalan, Dipu T / Moni, Merlin / Balachandran, Sabarish / Kumar, Anil V / Nair, Rajesh / Sudhindran, Surendran / Singh, Sanjeev K

Journal of pharmacy practice

2022 Volume 36, Issue 4, Page(s) 761–768

Abstract: Background: ...

Abstract	Background:
MeSH term(s)	Humans ; Colistin/adverse effects ; Anti-Bacterial Agents/adverse effects ; Transplant Recipients ; Organ Transplantation/adverse effects ; Bacterial Infections/drug therapy
Chemical Substances	Colistin (Z67X93HJG1) ; Anti-Bacterial Agents
Language	English
Publishing date	2022-02-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	1027474-1
ISSN	1531-1937 ; 0897-1900
ISSN (online)	1531-1937
ISSN	0897-1900
DOI	10.1177/08971900221074967
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Article ; Online: Epidemiology of Community-Acquired Sepsis

Fabia Edathadathil / Soumya Alex / Preetha Prasanna / Sangita Sudhir / Sabarish Balachandran / Merlin Moni / Vidya Menon / Dipu T. Sathyapalan / Sanjeev Singh

Pathogens, Vol 11, Iss 1226, p

Data from an E-Sepsis Registry of a Tertiary Care Center in South India

2022 Volume 1226

Abstract	The study aims to characterize community-acquired sepsis patients admitted to our 1300-bedded tertiary care hospital in South India from the Surviving Sepsis Campaign (SSC) guideline-compliant e-sepsis registry stratified by focus of infection. The prospective observational study recruited 1009 adult sepsis patients presenting to the emergency department at the center based on Sepsis-2 criteria for a period of three years. Of the patients, 41% were between 61 and 80 years with a mean age of 57.37 ± 13.5%. A total of 13.5% (136) was under septic shock and in-hospital mortality for the study cohort was 25%. The 3 h and 6 h bundle compliance rates observed were 37% and 49%, respectively, without significant survival benefits. Predictors of mortality among patients with bloodstream infections were septic shock ( p = 0.01, OR 2.4, 95% CI 1.23–4.79) and neutrophil-to-lymphocyte ratio ( p = 0.008, OR 1.01, 95% CI 1.009–1.066). The presence of Acinetobacter ( p = 0.005, OR 4.07, 95% CI 1.37–12.09), Candida non-albicans ( p = 0.001, OR16.02, 95% CI 3.0–84.2) and septic shock ( p = 0.071, OR 2.5, 95% CI 0.97–6.6) were significant predictors of mortality in patients with community-acquired pneumonia. The registry has proven to be a key data source detailing regional microbial etiology and clinical outcomes of adult sepsis patients, enabling comprehensive evaluation of regional community-acquired sepsis to tailor institutional sepsis treatment protocols.
Keywords	sepsis ; community-acquired sepsis ; registry ; surviving sepsis campaign ; Medicine ; R
Subject code	610
Language	English
Publishing date	2022-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Machine Learning Understanding of Sepsis.

Shetty, Manish / Alex, Soumya Mary / Moni, Merlin / Edathadathil, Fabia / Prasanna, Preetha / Menon, Veena / Menon, Vidya P / Athri, Prashanth / Srinivasa, Gowri

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

2021 Volume 2021, Page(s) 2175–2179

Abstract: Sepsis is a serious cause of morbidity and mortality and yet its pathophysiology remains elusive. Recently, medical and technological advances have helped redefine the criteria for sepsis incidence, which is otherwise poorly understood. With the ... ...

Abstract	Sepsis is a serious cause of morbidity and mortality and yet its pathophysiology remains elusive. Recently, medical and technological advances have helped redefine the criteria for sepsis incidence, which is otherwise poorly understood. With the recording of clinical parameters and outcomes of patients, enabling technologies, such as machine learning, open avenues for early prognostic systems for sepsis. In this work, we propose a two-phase approach towards prognostic scoring by predicting two outcomes in sepsis patients - Sepsis Severity and Comorbidity Severity. We train and evaluate multiple machine learning models on a dataset of 80 parameters collected from 800 patients at Amrita Institute of Medical Sciences, Kerala, India. We present an analysis of these results and harmonize consistencies and/or contradictions between elements of human knowledge and that of the model, using local interpretable model-agnostic explanations and other methods.
MeSH term(s)	Humans ; Incidence ; India ; Machine Learning ; Sepsis/diagnosis
Language	English
Publishing date	2021-12-07
Publishing country	United States
Document type	Journal Article
ISSN	2694-0604
ISSN (online)	2694-0604
DOI	10.1109/EMBC46164.2021.9629558
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Article: Assessment of Post-Covid Symptoms in Covid-19 Recovered Patients: A Prospective Cohort Study in a Tertiary Care Centre of South India.

Kambhampati, Nikhil Teja / Chithira / PillaiM, Gopala Krishna / Ts, Dipu / Moni, Merlin

The Journal of the Association of Physicians of India

2020 Volume 70, Issue 4, Page(s) 11–12

Abstract: The post-Covid symptoms among patients hospitalised with covid has to be determined for elucidating the spectrum of illness which persists even after the apparent recovery. The understanding of the post-Covid symptoms will help us to better manage ... ...

Abstract	The post-Covid symptoms among patients hospitalised with covid has to be determined for elucidating the spectrum of illness which persists even after the apparent recovery. The understanding of the post-Covid symptoms will help us to better manage aftermath of the pandemic. Our aim is to determine the incidence of post-Covid symptoms in a cohort of inpatients who recovered from COVID-19 from a tertiary care centre in South India. Material: 120 survivors from patients admitted with COVID 19 were prospectively followed up for 6 weeks after their discharge from the hospital. The cohort included 50 patients requiring Intensive care unit (ICU) care and 70 ward patients. The follow-up was conducted on the second and sixth week after discharge with a structured questionnaire. The questionnaire was filled by the patient/ bystanders during their visit to the hospital for follow-up at 2 weeks and through telephone follow up at 6 weeks. Observation: Mean age of the cohort was 55 years and 55% were males. 58.3% had mild covid and 41.7% had moderate to severe covid infection. 60.8% (n=73) of patients had at least one persistent symptom at sixth week of discharge. 50 (41.7%) patients required intensive care during their inpatient stay. Presence of persistent symptoms at 6 weeks was not associated with severity of illness, age or requirement for intensive care. Fatigue was the most common reported persistent symptom with a prevalence of 55.8% followed by weight loss (22.5%) and dyspnoea (20%). Female sex (OR 2.4, 95% CI: 1.03-5.58, p = 0.041) and steroid administration during hospital stay (OR: 4.43; 95% CI: 1.9-10.28, p = 0.001), were found to be significant risk factors for the presence of post-Covid symptoms at 6 weeks as revealed by logistic regression analysis. Conclusion: 60.8% of inpatients treated for covid had post-Covid symptoms at 6 weeks post- discharge from hospital. Female sex and steroid administration during hospital stay were identified as predictors of persistence of post-Covid symptoms at 6weeks.
MeSH term(s)	COVID-19/complications ; COVID-19/epidemiology ; Cohort Studies ; Female ; Humans ; India/epidemiology ; Male ; Middle Aged ; Prospective Studies ; Steroids ; Tertiary Care Centers
Chemical Substances	Steroids
Language	English
Publishing date	2020-12-07
Publishing country	India
Document type	Journal Article
ZDB-ID	800766-4
ISSN	0004-5772
ISSN	0004-5772
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