Comparison of 24 vs 72-hour octreotide infusion in acute esophageal variceal hemorrhage - a multi-center, randomized clinical trial.

BACKGROUND: Current guidelines lack clarity about the optimal duration of octreotide therapy for patients with esophageal variceal hemorrhage (EVH). To address this lack of evidence, we conducted a randomized clinical trial (RCT) of 24-hours versus 72-hours continuous infusion of octreotide for patients with EVH. METHODS: This multi-center, prospective RCT (NCT03624517), randomized patients with EVH to 24-hour versus 72-hour infusion of octreotide. Patients were required to undergo esophageal variceal band ligation prior to enrollment. The primary endpoint was rebleeding rate at 72 hours. The study was terminated early due to an inability to recruit during and after the COVID-19 epidemic. RESULTS: For patients randomized to 72-hours (n = 19) of octreotide vs 24-hours (n = 15), there were no differences in the need for transfusion, average pRBC units transfused per patient (3 units vs 2 units), infection (5% vs 0%), mechanical ventilation (11% vs 7%), or the need for vasopressors (5% vs 3%), respectively (none of these differences were statistically significantly different). There were 2 re-bleeding events in the 72-hour group (11%), and no re-bleeding events in the 24-hour group (p = 0.49). 8/15 of patients receiving 24 hours of octreotide were discharged at or before hospital day 3 while none in the 72-hour group was discharged before day 3 (p < 0.001). There was one death (in the 72-hour group) within 30 days. CONCLUSIONS: A 24-hour infusion is non-inferior to a 72-hour infusion of octreotide for prevention of re-bleeding in patients with EVH. We propose that shortened octreotide duration may help reduce hospital stay and related costs in these patients.

A Prospective Study on Perfusion MRI Changes in Intracranial Meningiomas Following Gamma Knife Therapy.

BACKGROUND: Radiosurgery plays an important role as a treatment modality for intracranial meningiomas. Perfusion MR imaging can be performed by using arterial spin-labeling (ASL) which is a relatively new and advanced technique. OBJECTIVES: To assess the changes in perfusion parameters on ASL perfusion MRI in intracranial meningioma after radiosurgery and correlate with histopathological grade of meningioma. MATERIALS AND METHODS: In this Prospective study done at the our institute over a period of 20 months (Jan 2016-Aug 2017), patients with intracranial meningiomas had perfusion MRI with ASL sequence on GE Optima 450W®, 1.5T MRI (GE Medical Systems) prior to GKT and at 6 months after GKT were included in the study. RESULTS: Twenty-seven patients were included in this study. Mean cerebral blood flow (CBF) was higher in angiomatous meningiomas. Though mean values of average CBF, maximum, minimum, and SD derived from the ASL MR perfusion were relatively higher in post GKT group as compared to those obtained in pre-GKT but it was not clinically significant. Mean baseline volume of whole cohort was 5.71 cm3 and decreased significantly post GKT in a follow up of 6 months to 5.59 cm3 (P value 0.0018). On comparing volumes of primary and secondary group, volumes were not found be significantly decreased in primary group (P value = 0.1361), 0.1361), but significantly reduced in secondary group (7.13 vs 7.034 cm3) (P value of = 0.0038). CONCLUSION: Our preliminary observations support ASL as a sensitive MRI sequence for the evaluation of meningioma perfusion patterns.

Unforeseen outcomes: Unveiling cyst formation post stereotactic radiosurgery in brain arteriovenous malformations cases.

INTRODUCTION: Cyst formation after stereotactic radiosurgery (SRS) for brain arteriovenous malformations (AVMs) is a rare, delayed but important complication. Prompt recognition and appropriate treatment is essential for good outcome. METHODS: We analysed our institute's Gamma knife treatment records from 2008 to 2023 and analysed AVM treated patients by gamma knife radiosurgery (GKRS). Patients with cyst formation and with adequate follow up were identified. Clinical details, management and prognosis of these patients was studied in detail along with prior literature review. RESULTS: A total of 921 AVM patients were treated in the above period and 7 patients were identified with cyst formation. The mean nidus volume was 12.98 ml, the mean radio surgical marginal dose was 23.57 Gy and maximal dose 47.21 Gy. The mean interval gap between SRS and cyst detection was 6.45 years. The mean volume of cyst cavity formed was 47.85 ml. Patients presented either with features of raised intracranial pressure (3) or focal neurological deficits (3) or seizures (1). 3 patients had achieved angiographic nidus obliteration at the time of cyst detection. Treatment was mostly on surgical lines with cyst fenestration(2 patients), excision (3 patients) and emergency decompressive craniectomy (1 patient). 1 patient required additional Ommaya insertion. Conservative management was followed for 1 patient. Residual nidus was treated either by concomitant excision or embolization or redo GKRS. Favourable outcome was seen in 6 out of 7 patients (85.71%) post cyst management with symptomatic and radiological improvement whereas 1 patient (14.28%) died due to refractory status epilepticus secondary to malignant cerebral edema. CONCLUSION: Cyst formation after GKRS for AVM treatment is an often-neglected complication due to its low incidence and often long latency period. Long term follow up of patients is hence necessary for prompt recognition. Diagnostic DSA should be done in all patients with cysts to look for residual nidus. Asymptomatic ones can be followed up conservatively while surgical treatment is required for symptomatic cases. Ventricular diversion like Ommaya or cystoperitoneal shunt may be necessary in some cases. Treatment outcome is usually favourable provided timely detection is done.

Effect of Transcutaneous Electrical Nerve Stimulation of T6 Dermatome on Appetite and Weight Reduction in Obese Individuals: A Pilot Study.

BACKGROUND: Previous work demonstrated the beneficial effect of T6 dermatomal stimulation by the percutaneous method in managing obesity. However, a simple, cost-effective, and feasible intervention stimulating the dermatome can be a potential solution for obesity care. OBJECTIVE: The objective of this study was to find the effect of transcutaneous electrical nerve stimulation (TENS) of T6 dermatome on appetite and weight loss in obese individuals. MATERIAL AND METHODS: In this prospective single-arm experimental study, 20 obese patients received TENS treatment of T6 dermatome for 30 min, once a week and for 12 weeks. Outcome measures such as appetite level in the visual analog scale (VAS), weight in kg, and basal metabolic index (BMI) in kg/m2 were assessed at baseline, 12 weeks -post-intervention, and at 8 weeks of follow-up. RESULTS: A statistically significant difference in all the variables was found from baseline to 12 weeks of intervention (P < 0.001) and maintained till 8 weeks of follow-up. From pre- to post-treatment, the effect size for appetite reduction was large (>1) while for weight and BMI loss was (0.14, 0.16), respectively small. Additionally, a weak correlation was found between pre- and follow-up appetite and weight loss (r = 0.25, P = 0.294). CONCLUSIONS: Twelve weeks of TENS treatment of T6 dermatome showed a positive effect in reducing appetite with sustained reduction up to 8 weeks of follow-up even after completion of the intervention. However, in the absence of dietary modification, TENS treatment was associated with low effect sizes weight and BMI loss.

Surgical Management of Extradural Tumors at the Craniovertebral Junction - Insights from a Tertiary Care Center.

BACKGROUND: Craniovertebral junction (CVJ) tumors are challenging due to their unique anatomical location. This study aimed to evaluate the complexities in dealing with such precarious CVJ extradural lesions over the decade. METHODS: Twenty-seven patients of extradural CVJ tumors operated between 2009 and 2018 were included. The demographic details, neurological status, surgical approach, extent of resection, type of fixation, complications, and outcome at final follow-up were recorded for each patient. RESULTS: The mean age of the patients was 39.5 ± 20 years. Most (17/27) of the patients had involvement of a single level. Clivus was the most common (9/17) involved region followed by atlas (7/17) vertebrae. Majority of the patients (13/27) were operated through the posterior-only approach. About 15 patients (55.5%) had instability or extensive lesions that necessitated posterior fixation. None of the patients underwent anterior fixation. Gross and near total excision were achieved in 10 patients (37%) and 3 patients (11%) respectively while 14 patients underwent subtotal excision of tumor. On histopathological analysis, clival chordoma (8/27) was found to be the most common pathology followed by giant cell tumor (6/27), plasmacytoma (4/27), and multiple myeloma (2/27). Most patients (13 out of 27) had the same neurological status after the surgery. Six patients (22%) improved post-operatively with decreased weakness and spasticity. Thirteen (48%) patients underwent adjuvant radiotherapy. CONCLUSIONS: This retrospective study provides valuable insights into managing extradural CVJ tumors and highlights the importance of individualized approaches for optimal outcome.

Cisternostomy as an Adjuvant or Standalone Approach for Management of Traumatic Brain Injury: A Systematic Review and Network Meta-Analysis.

BACKGROUND: Traumatic brain injury (TBI) is a leading cause of morbidity in all age groups worldwide. Decompressive craniectomy (DC) is a salvage procedure in patients with TBI. The outcome and quality of life following DC is questionable. Basal cisternostomy (BC) has been proposed to reduce edema and lead to brain relaxation. It was initially used as an adjunct in TBI patients, thereby improving outcomes. With gaining popularity among neurosurgeons, BC was used as a standalone approach in TBI patients. This network meta-analysis aims to analyze the role of BC either as an adjunct or as a standalone approach in managing TBI patients. METHODS: A comprehensive search of electronic databases (PubMed and SCOPUS) was performed using the search strategy using the field terms and medical subheading terms (MeSH Terms) to retrieve studies describing the role of BC in patients with TBI either as an adjunct with DC or standalone treatment and their outcome. RESULTS: Thirty-one articles were selected for full-text review and 18 articles were selected for the final analysis. BC alone group was found to have minimum in-hospital mortality (odds ratio [OR], 0.348; 95% credible interval [CrI], 0.254 to 0.477) followed by DC combined with BC group (OR, 0.645; 95% CrI, 0.476 to 0.875). DC combined with the BC group was found to have a minimum duration of mechanical ventilation (OR, 0.114; 95% CrI, 0.005 to 2.451) followed by the BC alone group (OR, 0.604; 95% CrI, 0.024 to 15.346). DC combined with the BC group were found to have the maximum Glasgow Outcome Scale score (OR, 1.661; 95% CrI, 0.907 to 3.041) followed by the BC alone group (OR, 1.553; 95% CrI, 0.907 to 3.041). CONCLUSIONS: Our analysis showed that BC alone was associated with lower in-hospital mortality rates in TBI patients. DC with BC had decreased the requirement of mechanical ventilation. However, larger multi-centric studies from other parts of the world are required to confirm these findings.

Three dimensional convolutional neural network-based automated detection of midline shift in traumatic brain injury cases from head computed tomography scans.

Objectives: Midline shift (MLS) is a critical indicator of the severity of brain trauma and is even suggestive of changes in intracranial pressure. At present, radiologists have to manually measure the MLS using laborious techniques. Automatic detection of MLS using artificial intelligence can be a cutting-edge solution for emergency health-care personnel to help in prompt diagnosis and treatment. In this study, we sought to determine the accuracy and the prognostic value of our screening tool that automatically detects MLS on computed tomography (CT) images in patients with traumatic brain injuries (TBIs). Materials and Methods: The study enrolled TBI cases, who presented at the Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi. Institutional ethics committee permission was taken before starting the study. The data collection was carried out for over nine months, i.e., from January 2020 to September 2020. The data collection included head CT scans, patient demographics, clinical details as well as radiologist's reports. The radiologist's reports were considered the "gold standard" for evaluating the MLS. A deep learning-based three dimensional (3D) convolutional neural network (CNN) model was developed using 176 head CT scans. Results: The developed 3D CNN model was trained using 156 scans and was tested on 20 head CTs to determine the accuracy and sensitivity of the model. The screening tool was correctly able to detect 7/10 MLS cases and 4/10 non-MLS cases. The model showed an accuracy of 55% with high specificity (70%) and moderate sensitivity of 40%. Conclusion: An automated solution for screening the MLS can prove useful for neurosurgeons. The results are strong evidence that 3D CNN can assist clinicians in screening MLS cases in an emergency setting.

Re-Admissions of 'Unknown' Traumatic Brain Injury Patients - Inadequacy of Rehabilitative Services in a Developing Country.

BACKGROUND: In neurosurgical practice, continuous care after discharge and the ability to detect subtle indicators of clinical deterioration are mandatory to prevent the progression of a disease. The care of 'unknown' patients discharged to rehabilitation homes may not have this privilege, especially in resource-poor countries such as India. OBJECTIVE: We have attempted to study the causes and outcomes of re-admissions of 'unknown' patients with previous traumatic brain injury (TBI) to estimate the quality of nursing care in our rehabilitation centers. MATERIAL AND METHODS: The electronic hospital records of all consecutive 'unknown' TBI patients with unplanned re-admissions at our institute from January 2014 to December 2018 were retrospectively reviewed and analyzed for the factors determining the risk and outcomes of re-admission. RESULTS: Out of 245 patients sent to rehabilitation homes at discharge, 47 patients (19.18%) were re-admitted. A total of 33 patients (70%) were re-admitted between 1 month and 1 year. Out of these, 38 patients (80.9%) were re-admitted because of preventable causes. Fifteen patients (31.9%) died during the hospital stay. The rest of the 32 (68%) patients were discharged after the management of the concerned condition with an average hospital stay of 9 ± 11.1 days. The average Glasgow coma scale (GCS) at re-admission of the patients who died was 6 (range 3-11). Two patients were brought in the brain dead status, whereas 20 patients (42.6%) had a GCS of 5 or below at the time of re-admission. The risk of mortality among patients with non-preventable causes was 88.9% (8/9) compared to preventable causes 18.4% (7/38). However, preventable causes for re-admission are much more common, resulting in nearly a similar overall contribution to mortality. CONCLUSIONS: There is a high rate of mortality and morbidity in 'unknown' patients with TBI because of poor post-discharge care in developing countries. Because preventable causes are the major contributor to re-admissions, the re-admission rate is a good indicator of a lack of adequate rehabilitative services. The need for improving the post-discharge management of 'unknown' patients with TBI in resource-poor countries cannot be over-emphasized.

Correlation between Transcranial Ultrasound and CT Head to Detect Clinically Significant Conditions in Post-craniectomy Patients Performed by Emergency Physician: A Pilot Study.

Background: The main objective is to detect clinically significant conditions by transcranial ultrasound (TCS) in post-decompressive craniectomy (DC) patients who come to the emergency department. Materials and methods: This was a cross-sectional observational study. We studied 40 post-DC patients. After primary stabilization, TCS was done. Computer tomography of head was done within 2 hours of performing TCS. The correlation between both modalities were assessed by the measurement of lateral ventricle (LV) (Bland-Altman plot), Midline shift and mass lesion. Additionally, normal cerebral anatomy, 3rd and 4th ventricles and external ventricular drainage (EVD) catheter visualization were also done. Results: About 14/40 patients came with non-neurosurgical complaints and 26/40 patients came with neurosurgical complaints. Patients with non-neurosurgical complaints (4/14) had mass lesions and 1/14 had MLS. Patients with neurosurgical complaints (11/26) had mass lesions and about 5 patients had MLS. A good correlation was found between TCS and CT of head in measuring LV right (CT head = 17.4 ± 13.8 mm and TCS = 17.1 ± 14.8 mm. The mean difference (95% CI) = [0.28 (-1.9 to 1.33), ICC 0.93 (0.88-0.96)], Left [CT head = 17.8 ± 14.4 mm and TCS = 17.1 ± 14.2 mm, the mean difference (95% CI) 0.63 (-1.8 to 0.61), ICC 0.96 (0.93-0.98)], MLS [CT head = 6.16 ± 3.59 (n = 7) and TCS = 7.883 ± 4.17 (n = 6)] and mass lesions (kappa 0.84 [0.72-0.89] [95% CI] p-value < 0.001). The agreement between both modalities for detecting mass lesions is 93.75%. Conclusion: Point of care ultrasound (POCUS) is a bedside, easily operable, non-radiation hazard and dynamic imaging tool that can be used for TCS as a supplement to CT head in post-DC patients in emergency as well as in ICU. However, assessment of the ventricular system (pre/post-EVD insertion), monitoring of regression/progression of mass lesion, etc. can be done with TCS. Repeated scans are possible in less time which can decrease the frequency of CT head. How to cite this article: Chouhan R, Sinha TP, Bhoi S, Kumar A, Agrawal D, Nayer J, et al. Correlation between Transcranial Ultrasound and CT Head to Detect Clinically Significant Conditions in Post-craniectomy Patients Performed by Emergency Physician: A Pilot Study. Indian J Crit Care Med 2024;28(3):299-306.

PROTAC-Design-Evaluator (PRODE): An Advanced Method for In-Silico PROTAC Design.

PROTAC (proteolysis-targeting chimeras) is a rapidly evolving technology to target undruggable targets. The mechanism by which this happens is when a bifunctional molecule binds to a target protein and also brings an E3 ubiquitin ligase in proximity to trigger ubiquitination and degradation of the target protein. Yet, in-silico-driven approaches to design these heterobifunctional molecules that have the desired functional properties to induce proximity between the target protein and E3 ligase remain to be established. In this paper, we present a novel in-silico method for PROTAC design and to demonstrate the validity of our approach, we show that for a BRD4-VHL-PROTAC-mediated ternary complex known in the literature, we are able to reproduce the PROTAC binding mode, the structure of the ternary complex formed therein, and the free energy (ΔG) thermodynamics favoring ternary complexation through theoretical/computational methodologies. Further, we demonstrate the use of thermal titration molecule dynamics (TTMD) to differentiate the stability of PROTAC-mediated ternary complexes. We employ the proposed methodology to design a PROTAC for a new system of FGFR1-MDM2 to degrade the FGFR1 (fibroblast growth factor receptor 1) that is overexpressed in cancer. Our work presented here and named as PROTAC-Designer-Evaluator (PRODE) contributes to the growing literature of in-silico approaches to PROTAC design and evaluation by incorporating the latest in-silico methods and demonstrates advancement over previously published PROTAC in-silico literature.

Quantifiable identification of flow-limited ventilator dyssynchrony with the deformed lung ventilator model.

BACKGROUND: Ventilator dyssynchrony (VD) can worsen lung injury and is challenging to detect and quantify due to the complex variability in the dyssynchronous breaths. While machine learning (ML) approaches are useful for automating VD detection from the ventilator waveform data, scalable severity quantification and its association with pathogenesis and ventilator mechanics remain challenging. OBJECTIVE: We develop a systematic framework to quantify pathophysiological features observed in ventilator waveform signals such that they can be used to create feature-based severity stratification of VD breaths. METHODS: A mathematical model was developed to represent the pressure and volume waveforms of individual breaths in a feature-based parametric form. Model estimates of respiratory effort strength were used to assess the severity of flow-limited (FL)-VD breaths compared to normal breaths. A total of 93,007 breath waveforms from 13 patients were analyzed. RESULTS: A novel model-defined continuous severity marker was developed and used to estimate breath phenotypes of FL-VD breaths. The phenotypes had a predictive accuracy of over 97% with respect to the previously developed ML-VD identification algorithm. To understand the incidence of FL-VD breaths and their association with the patient state, these phenotypes were further successfully correlated with ventilator-measured parameters and electronic health records. CONCLUSION: This work provides a computational pipeline to identify and quantify the severity of FL-VD breaths and paves the way for a large-scale study of VD causes and effects. This approach has direct application to clinical practice and in meaningful knowledge extraction from the ventilator waveform data.

Hospitals Should Offer Straws Only on Demand to the Public and Patients-An Environmental and Patient Care Imperative.

Plastic straws have become the poster child of waste associated with unnecessary single-use plastics. The visibility of straws littering the land and marine environments has influenced proposals to decrease the use of plastic straws. These include bans on plastic straws at the city, state, and national levels and by many corporations. However, most hospitals continue to use plastic straws in hospital dining areas and for patients. Hospital dining areas are like other public dining areas, so eliminating plastic straws should be straightforward. Regarding the use of straws by patients, we review evidence and propose that patients should not be routinely given straws. Instead, physicians and nursing staff should request straws depending on the patient's medical needs. Plastic straws make up only a tiny fraction of hospital waste but can be a catalyst to create awareness and decrease unnecessary plastic use in other areas of the hospital. Mitigating climate change requires a concerted effort from hospital leadership and healthcare providers. Only then will hospitals be able to fulfill their climate pledge of net zero emissions by 2050.

A Novel Method for Prediction of Raised Intracranial Pressure Through Automated ONSD and ETD Ratio Measurement From Ocular Ultrasound.

The paper presents a novel framework for the prediction of the raised Intracranial Pressure (ICP) from ocular ultrasound images of traumatic patients through automated measurement of Optic Nerve Sheath Diameter (ONSD) and Eyeball Transverse Diameter (ETD). The measurement of ONSD using an ocular ultrasound scan is non-invasive and correlates with the raised ICP. However, the existing studies suggested that the ONSD value alone is insufficient to indicate the ICP condition. Since the ONSD and ETD values may vary among patients belonging to different ethnicity/origins, there is a need for developing an independent global biomarker for predicting raised ICP condition. The proposed work develops an automated framework for the prediction of raised ICP by developing algorithms for the automated measurement of ONSD and ETD values. It is established that the ONSD and ETD ratio (OER) is a potential biomarker for ICP prediction independent of ethnicity and origin. The OER threshold value is determined by performing statistical analysis on the data of 57 trauma patients obtained from the AIIMS, New Delhi. The automated OER is computed and compared with the conventionally measured ICP by determining suitable correlation coefficients. It is found that there is a significant correlation of OER with ICP (r = .81, p ≤ .01), whereas the correlation of ONSD alone with ICP is relatively less (r = .69, p = .004). These correlation values indicate that OER is a better parameter for the prediction of ICP. Further, the threshold value of OER is found to be 0.21 for predicting raised ICP conditions in this study. Scatter plot and Heat map analysis of OER and corresponding ICP reveal that patients with OER ≥ 0.21, have ICP in the range of 17 to 35 mm Hg. In the data available for this research work, OER ranges from 0.17 to 0.35.

Automated intracranial hemorrhage detection in traumatic brain injury using 3D CNN.

Objectives: Intracranial hemorrhage (ICH) is a prevalent and potentially fatal consequence of traumatic brain injury (TBI). Timely identification of ICH is crucial to ensure timely intervention and to optimize better patient outcomes. However, the current methods for diagnosing ICH from head computed tomography (CT) scans require skilled personnel (Radiologists and/or Neurosurgeons) who may be unavailable in all centers, especially in rural areas. The aim of this study is to develop a neurotrauma screening tool for identifying ICH from head CT scans of TBI patients. Materials and Methods: We prospectively collected head CT scans from the Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi. Approximately 738 consecutive head CT scans from patients enrolled in the department were collected for this study spanning a duration of 9 months, that is, January 2020 to September 2020. The metadata collected along with the head CT scans consisted of demographic and clinical details and the radiologist's report which was used as the gold standard. A deep learning-based 3D convolutional neural network (CNN) model was trained on the dataset. The pre-processing, hyperparameters, and augmentation were common for training the 3D CNN model whereas the training modules were set differently. The model was trained along with the save best model option and was monitored by validation metrics. The Institute Ethics Committee permission was taken before starting the study. Results: We developed a 3D CNN model for automatically detecting the ICH from head CT scans. The screening tool was tested in 20 cases and trained on 200 head CT scans, with 99 normal head CT and 101 CT scans with some type of ICH. The final model performed with 90% sensitivity, 70% specificity, and 80% accuracy. Conclusion: Our study reveals that the automated screening tool exhibits a commendable level of accuracy and sensitivity in detecting ICH from the head CT scans. The results indicate that the 3D CNN approach has a potential for further exploring the TBI-related pathologies.