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This case report describes an uncommon presentation of lung adenocarcinoma, which appeared as a skull mass. While not the first reported case in medical literature, it is still a rare occurrence for lung adenocarcinoma to present in this manner. This report focuses on the clinical presentation and treatment of an elderly male patient who had a progressively enlarging and painful skull mass. The initial imaging revealed an about 5 cm soft tissue mass at the dorsal midline of the parietal-occipital bone. Subsequent imaging identified a lung mass, and a biopsy of the skull bone confirmed that the mass was metastatic adenocarcinoma originating from the lung. For treatment, the patient underwent occipital partial resection of the mass, followed by wire mesh cranioplasty. Chemotherapy and external beam radiotherapy were administered to alleviate symptoms and control the spread of cancer. Lung carcinoma with distant metastasis is generally associated with a poorer prognosis. However, some supporting data suggest that early detection and aggressive management play crucial roles in preventing further metastasis and improving the patient's quality of life and overall survival rate. Skull bone metastasis from lung cancer is indeed a rare phenomenon, and cases like these contribute valuable knowledge to the field. By reporting such cases, healthcare professionals can gain a better understanding of the clinical manifestations, diagnostic challenges, and appropriate management strategies for these uncommon occurrences. This case report underscores the significance of maintaining a high index of suspicion and utilizing a multimodality approach to diagnose rare instances of calvarial metastasis.

Background: Globally in 2015, 2.6 million stillbirths occurred with estimated stillbirth rate (SBR) of 18.4/1000 births. India is the world capital of stillbirth accounting for 22.6% of world's stillbirths. Objectives: The objective of the study is to study the demographic profile of women experiencing stillbirth, to understand the risk factors for stillbirth in low resource settings, and to find the etiology of stillbirth so as to facilitate designing of a stillbirth prevention strategy. Methods: This was a cross-sectional observational study done at a tertiary care hospital of Delhi from June 2017 to December 2019. All babies delivered after 20 weeks of gestation showing no sign of life after birth were considered stillborn. Prestructured proforma was filled for each case and data were analyzed. Results: A total of 50,461 births took place during the study period, out of which 1824 were stillborn, making SBR of 36.15/1000 births of our institution. Most of the women belonged to age group 21-25 years and more than 50% of women were illiterate. Twenty-nine percent of women were completely unbooked, 48% were referred from other centers and 23% were registered at our hospital. Placental causes accounted for 22%, hypertension for 23%, and labor complications for 9% of cases while in 22% cases, cause could not be found. Conclusion: Stillbirth remains a neglected issue. A significant proportion of stillbirths are preventable by adequate antenatal care. Notification of stillbirths will give us the exact figures and realization of the seriousness of the problem which will help us work towards the solutions.

Background & objectives: Nasopharyngeal and oropharyngeal swab (NPS and OPS) collection is widely accepted as the preferred method for obtaining respiratory samples. However, it has certain disadvantages which may be overcome by gargling. The primary objective of this study was to assess agreement between gargle lavage and swab as an appropriate respiratory sample for the detection of SARS-CoV-2. The secondary objective was to assess the patient acceptability of the two sampling methods. Methods: It was a cross-sectional study done at a tertiary care hospital in New Delhi, India, on 50 confirmed COVID-19 patients. Paired swab (NPS and OPS) and gargle samples were taken within 72 h of their diagnosis. Samples were processed by reverse transcription-polymerase chain reaction (RT-PCR) for detection of SARS-CoV-2. Post-sample collection, a 10-point scale was administered to assess the level of discomfort with either of the collection methods. Results: All gargle samples were positive and comparable to their corresponding swab samples irrespective of the symptoms and duration of illness. The cycle threshold (Ct) values for gargle samples were slightly higher but comparable to those of swabs. Bland-Altman plot showed good agreement between the two methods. Majority (72%) of the patients reported moderate-to-severe discomfort with swab collection in comparison to 24 per cent reporting only mild discomfort with gargle collection. Interpretation & conclusions: Our preliminary results show that the gargle lavage may be a viable alternative to swabs for sample collection for the detection of SARS-CoV-2. Adoption of gargle lavage for sample collection will have a significant impact as it will enable easy self-collection, relieve healthcare workers and also lead to substantial cost savings by reducing the need for swabs and personal protective equipment.

Background Catheter-associated urinary tract infections (CAUTIs) are a major healthcare-associated infection (HAI) in trauma care settings, contributing to morbidity, mortality and antimicrobial resistance. In this study we characterize the epidemiology, microbiological profile, antimicrobial resistance patterns, and clinical outcomes of CAUTIs and non-CAUTI urinary tract infections (UTIs) at a Level 1 Trauma Centre in India from 2017 to 2024, using a modified CDC-NHSN definition and digital surveillance. Methods A retrospective analysis of 723 UTI events was conducted using Centers for Disease Control and Prevention’s National Healthcare Safety Network (CDC-NHSN) definitions, modified to include Candida spp. at ≥ 10 5 CFU/mL. Surveillance was performed by dedicated Hospital Infection Control Nurses (HICNs) using a digital system. Microbiological identification and antimicrobial susceptibility testing (AST) were conducted via the conventional manual methods and automated systems. Results of 723 UTI events, 608 (84.0%) were CAUTIs. The cohort had a median age of 34 years (IQR:22–45) and was 76% male. Pseudomonas aeruginosa (18%), Klebsiella pneumoniae (17.9%), and Escherichia coli (15%) were predominant pathogens. Antimicrobial resistance was high, with 100% resistance to ceftazidime in Acinetobacter baumannii and 93.6–94.1% resistance to ciprofloxacin in Klebsiella spp. and Enterococcus spp. Mortality was 25.5% (28.2% in CAUTI, 12.9% in non-CAUTI). Conclusion This large-scale, trauma specific study with modified fungal criteria and digital surveillance highlights the importance of CAUTI burden and the high resistance in pathogens causing this infection. Clinical trial number Not applicable.

Objectives To study whether a trained convolutional neural network (CNN) can be of assistance to radiologists in differentiating Coronavirus disease (COVID)–positive from COVID-negative patients using chest X-ray (CXR) through an ambispective clinical study. To identify subgroups of patients where artificial intelligence (AI) can be of particular value and analyse what imaging features may have contributed to the performance of AI by means of visualisation techniques. Methods CXR of 487 patients were classified into [4] categories—normal, classical COVID, indeterminate, and non-COVID by consensus opinion of 2 radiologists. CXR which were classified as “normal” and “indeterminate” were then subjected to analysis by AI, and final categorisation provided as guided by prediction of the network. Precision and recall of the radiologist alone and radiologist assisted by AI were calculated in comparison to reverse transcriptase-polymerase chain reaction (RT-PCR) as the gold standard. Attention maps of the CNN were analysed to understand regions in the CXR important to the AI algorithm in making a prediction. Results The precision of radiologists improved from 65.9 to 81.9% and recall improved from 17.5 to 71.75 when assistance with AI was provided. AI showed 92% accuracy in classifying “normal” CXR into COVID or non-COVID. Analysis of attention maps revealed attention on the cardiac shadow in these “normal” radiographs. Conclusion This study shows how deployment of an AI algorithm can complement a human expert in the determination of COVID status. Analysis of the detected features suggests possible subtle cardiac changes, laying ground for further investigative studies into possible cardiac changes. Key Points • Through an ambispective clinical study, we show how assistance with an AI algorithm can improve recall (sensitivity) and precision (positive predictive value) of radiologists in assessing CXR for possible COVID in comparison to RT-PCR. • We show that AI achieves the best results in images classified as “normal” by radiologists. We conjecture that possible subtle cardiac in the CXR, imperceptible to the human eye, may have contributed to this prediction. • The reported results may pave the way for a human computer collaboration whereby the expert with some help from the AI algorithm achieves higher accuracy in predicting COVID status on CXR than previously thought possible when considering either alone.

Background: There are studies available on the prevalence of coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM) in hospitalized patients but not on the incidence of CAM in post-discharge patients. The aim of our study was to find the incidence of CAM in the patients discharged from a COVID hospital. Material and Methods: Adult patients with COVID discharged between March 1, 2021 and June 30, 2021 were contacted and enquired about sign and symptoms of CAM. Data of all included patients were collected from electronic records. Results: A total of 850 patients responded, among which 59.4% were males, 66.4% patients had co-morbidities, and 24.2% had diabetes mellitus. Around 73% of patients had moderate to severe disease and were given steroids; however, only two patients developed CAM post discharge. Conclusion: The incidence of CAM post discharge was low in our study, which could be attributed to protocolized therapy and intensive monitoring.

Introduction: Catheter-associated urinary tract infections (CAUTIs) are one of the most common device-associated infections acquired in a hospital. Trauma patients are highly susceptible to CAUTI, as catheterization is a lifesaving measure often required for their management. This study focuses on the profile of CAUTI, the organism profile with antibiotic susceptibility patterns, and the clinical outcomes in the ICUs of a trauma care center. Methodology: A retrospective analysis of prospective surveillance data of patients in ICUs was done over a period of ten years (2010-2019) in a level 1 trauma center. A modified NHSN definition of CAUTI was used. Microbiological processing and antibiotic susceptibility profile was done based on standard guidelines. Clinical outcomes were considered for analysis. Results: A total of 10,732 patients were included in the study, accounting for 98,131 patient days and 78,126 urinary catheter days (UCD). Among 546 patients, 577 episodes of CAUTI were recorded, giving a CAUTI rate of 7.4/1,000 catheter days. The average length of stay (LOS) of patients was 19.9 days. There was a significant relationship between UCD and the development of CAUTI. Orthopedic and spinal injuries (91%) accounted for the maximum device utilization ratio, followed by polytrauma (90%), miscellaneous injuries (88%), and head injuries (69%). CAUTI episodes were the highest in head injury patients. Gram-negative organisms (53.4%) dominated the pathogen profile. The crude mortality was 25.1%. Conclusions: Surveillance of CAUTI with analysis of the organisms and the antibiotic susceptibility trend will help improve infection prevention practices and antibiotic stewardship programs in local hospital settings.

Thyroid storm (accelerated hyperthyroidism) is an uncommon life-threatening emergency. The diagnosis is difficult and at times delayed owing to atypical presentation. Early diagnosis is the key to its successful management. We came across a patient who had presentations of acute abdomen but later diagnosed in thyroid storm. Multiorgan involvement leads all resuscitative measures futile and prevented us to salvage the patient.

Background: In the fight against the pandemic, personal protective equipment (PPE) has played a vital role. However, working with PPE has its own difficulties and problems. The aim of this study was to find out the reasons of early doffing, that is, in doffing in emergency situations before the shift among healthcare workers (HCWs) working in PPE in the COVID areas in resource-limited settings. Methods: This cross-sectional, survey-based study was carried out on healthcare workers involved in direct care of patients with COVID-19 in tertiary care COVID center, India. The questionnaire was sent as a Google form through email and social media platforms like WhatsApp and Facebook. The data was reported as the mean ± SD for continuous variables and as the percentage for categorical variables. Findings: Among 252 healthcare workers who participated in the survey, 145 (57.5%) participants doffed early on 300 occasions. Out of these 145, 50% doffed early only once and rest doffed early multiple times. The most common reason of early doffing was found to be breach in PPE (15.33%) followed by fogging (14%) and headache (12%), and most commonly, breach was in mask or coverall/gown (32.6% each). Conclusion: Although PPE decreases the risk of infection, it is challenging for HCWs to work in PPE leading to instances of early doffing. The most common reason for early doffing in our study was the breach in PPE and the most common component of breach was found to be mask and coverall/gown. Therefore, we suggest that the proper sizes of the PPE should be made available and proper training in donning should be imparted to HCWs working in PPE.