COVID-19-Associated Tension Pneumothorax in Mechanically Ventilated Patients: A Case Series

Severe acute respiratory syndrome management secondary to coronavirus (SARS-CoV-2) has been overwhelming for healthcare systems. Patients with SARS-CoV-2 infection can present with symptoms ranging from a mild flu-like illness to acute respiratory distress syndrome (ARDS). Patients who develop coronavirus disease 2019 (COVID-19) infection and present with hypoxic respiratory failure requiring mechanical ventilation typically follow ARDS physiology. Many of them develop complications including pneumothorax, pneumomediastinum, and pneumopericardium. In this case series, we present multiple instances where patients with severe COVID-19 infections developed tension pneumothoraces during their hospital course.

Thyroid Storm in a Patient on Chronic Amiodarone Treatment

Amiodarone is a class III antiarrhythmic drug with a structure comparable to thyroid hormone and 37% iodine content by weight. In addition to direct drug cytotoxicity on thyroid cells, amiodarone deiodination in the body releases an excessive amount of iodine, which can impair thyroid function and cause hypothyroidism or thyrotoxicosis, including thyroid storm in susceptible individuals. In this report, we discuss the case of a 52-year-old woman who experienced a thyroid storm after being treated with amiodarone, eventually leading to her death.

Prediction of COVID-19 severity from clinical and biochemical markers: a single-center study from Saudi Arabia

OBJECTIVE

It is known that the severity of COVID-19 is linked to the prognosis of patients; therefore, an early identification is required for patients who are likely to develop severe or critical COVID-19 disease. The purpose of this study is to propose a statistical method for identifying the severity of COVID-19 disease by using clinical and biochemical laboratory markers.

PATIENTS AND METHODS

A total of 48 clinically and laboratory-confirmed cases of COVID-19 were obtained from King Fahad Hospital, Medina (KFHM) between 27th April 2020 to 25th May 2020. The patients' demographics and severity of COVID-19 disease were assessed using 39 clinical and biochemical features. After excluding the demographics, 35 predicting features were included in the analysis (diabetes, chronic disease, viral and bacterial co-infections, PCR cycle number, ICU admission, clot formation, cardiac enzymes elevation, hematology profile, sugar levels in the blood, as well as liver and kidney tests, etc.). Logistic regression, stepwise logistic regression, L-2 logistic regression, L-2 stepwise logistic regression, and L-2 best subset logistic regression were applied to model the features. The consistency index was used with kernel Support-Vector Machines (SVM) for the identification of associated markers.

RESULTS

L-2 best subset logistic regression technique outperformed all other fitted models for modeling COVID-19 disease severity by achieving an accuracy of 88% over the test data. Consistency index over L-2 best subset logistic regression identified 14 associated markers that can best predict the COVID-19 severity among COVID-19 patients.

CONCLUSIONS

By combining a variety of laboratory markers with L-2 best subset logistic regression, the current study has proposed a highly accurate and clinically interpretable model of predicting COVID-19 severity.

“We can’t breathe!” – A dilemma faced by Total Technologies (Pvt.) Ltd. amid oxygen cylinder crisis

Learning outcomes

This case study aims to be taught at an MBA level. Students who are majoring in the supply chain would benefit the most from this case study. This case study has elements of logistics management, supply chain management, supply chain strategies, warehouse and logistics and responsible supply chain. The learning outcome of this case study could be seen if the students identify the gaps in the real market setting and come up with strategies that would connect and/or fill the areas missing. Teaching objective 1: students should be able to identify unstable demand scenarios and learn how demand collaboration could be implemented in that setting. Teaching objective 2: students should identify how a transparent and interconnected supply chain, both upstream and downstream, can be created. Teaching objective 3: students should be able to understand the role of a responsible supply chain and to define the role and responsibility of each party. Teaching objective 4: students should be able to learn the dynamics of safety stocks, reorder points and incorporate that in warehouse management decisions.

Case overview/synopsis

Based in Lahore, Pakistan, Total Technologies (Pvt.) Ltd is a company that supplies medical equipment and provides solutions in the health-care industry. This case explores the supply chain issues faced by Tallat Mehmood, who is the Managing Director of the company, during the third wave of the COVID-19 pandemic in April 2021. Oxygen cylinders have become the need of the hour as more and more patients need oxygen. The supply of medical gases across Pakistan has become a logistical issue, causing hospital reserves to be drained without timely replenishment. Increasing the number of beds in hospitals, with limited oxygen outlets, has increased the demand for oxygen cylinders. Operating under unstable demand and not being able to meet it has caused Tallat to realize that the company is out of its comfort zone and is not responding well to the environment. The company needs to redesign the supply chain as well as collaborate with the supplier and buyer to provide better levels of service.

Complexity academic level

Masters level supply chain courses.

Supplementary materials

Teaching Notes are available for educators only.

Subject code

CSS 9: Operations and logistics.

Drinking water quality of various sources in Peshawar, Mardan, Kohat and Swat districts of Khyber Pakhtunkhwa province, Pakistan

Abstract The present study involves the chemical and bacteriological analysis of water from different sources i.e., bore, wells, bottle, and tap, from Peshawar, Mardan, Swat and Kohat districts of Khyber Pakhtunkhwa (KP) province, Pakistan. From each district, 50 water samples (10 samples from each source), regardless of urban and rural status, were collected from these sources and analysed for sulphates, nitrates, nitrites, chlorides, total soluble solids and coliforms (E. coli). Results indicated that majority of the water sources had unacceptable E. coli count i.e.> 34 CFU/100mL. E. coli positive samples were high in Mardan District, followed by Kohat, Swat and Peshawar district. Besides this, the some water sources were also chemically contaminated by different inorganic fertilizers (nitrates/nitrites of sodium, potassium) but under safe levels whereas agricultural and industrial wastes (chloride and sulphate compounds) were in unsafe range. Among all districts, the water quality was found comparatively more deteriorated in Kohat and Mardan districts than Peshawar and Swat districts. Such chemically and bacteriologically unfit water sources for drinking and can cause human health problems.

COVID-19-Associated Spontaneous Pneumomediastinum and Pneumopericardium: Review of Case Series

Coronavirus disease 2019 (COVID-19) and its spectrum of respiratory illnesses ranging from mild to severe and critically ill have been well established. Spontaneous pneumomediastinum and pneumopericardium (PP) appear to be less reported entities and have been found to be reported complications in COVID-19 infection. Pneumomediastinum (PM) and PP are characterized by the presence of air in the mediastinal and pericardial cavity, respectively. Although, generally, secondary to trauma or underlying lung conditions like asthma, bronchiolitis obliterans, and blunt trauma, it can also occur spontaneously without an evident primary cause. PM and PP are increasingly reported complications in COVID-19 patients adversely affecting clinical outcomes. We present a case series of patients with spontaneous pneumomediastinum and pneumopericardium in the presence of underlying COVID-19 infection and their management at our academic medical center.

Automated detection of diabetic retinopathy using machine learning classifiers

OBJECTIVE

Diabetic Retinopathy (DR) is a highly threatening microvascular complication of diabetes mellitus. Diabetic patients must be screened annually for DR; however, it is practically not viable due to the high volume of patients, lack of resources, economic burden, and cost of the screening procedure. The use of machine learning (ML) classifiers in medical science is an emerging frontier and can help in assisted diagnosis. The few available proposed models perform best when used in similar population cohorts and their external validation has been questioned. Therefore, the purpose of our research is to classify the DR using different ML methods on Saudi diabetic data, propose the best method based on accuracy and identify the most discriminative interpretable features using the socio-demographic and clinical information.

PATIENTS AND METHODS

This cross-sectional study was conducted among 327 diabetic patients in Almajmaah, Saudi Arabia. Socio-demographic and clinical data were collected using a systematic random sampling technique. For DR classification, ML algorithm including, linear discriminant analysis, support vector machine, K nearest neighbor, random forest and its variate ranger random forest classifiers were used through cross-validation resampling procedure.

RESULTS

In classifying DR, ranger random forest outperforms the other methods by accurately classifying 86% of the DR patients on the test data. HbA1c (p<0.001) and duration of diabetes (p<0.001) were the most influential risk factor that best discriminated the DR patients. Other influential risk factors were the body mass index (p<0.001), age-onset (p<0.001), age (p<0.001), systolic blood pressure (p<0.05), and the use of medication (p<0.05) that significantly discriminated the DR patients.

CONCLUSIONS

Based on the present study findings, integrating ophthalmology and ML can transform diagnosing the disease pattern that can help generate a compelling clinical effect. ML can be used as an added tool for clinical decision-making and must not be the sole substitute for a clinician. We will work to examine the classification performance of multi-class data using more sophisticated ML methods.

Tocilizumab for the Treatment of COVID-19-Induced Cytokine Storm and Acute Respiratory Distress Syndrome: A Case Series From a Rural Level 1 Trauma Center in Western Pennsylvania

An outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2, initially in December 2019 at Wuhan, China, subsequently spread around the world. We describe a case series of COVID-19 patients treated at our academic medical center with focus on cytokine storm and potential therapeutic role of tocilizumab. A 59-year-old female admitted for shortness of breath (SOB), productive cough, fever, and nausea in the setting of COVID-19 pneumonia. Oxygen saturation was 81% necessitating supplemental oxygen. She was transferred to intensive care unit (ICU) for worsening hypoxia; intubated and received tocilizumab following which her oxygen requirements improved. A 52-year-old female admitted from an outside hospital with SOB, intubated for worsening hypoxia, in the setting of COVID-19 pneumonia. She received tocilizumab 400 mg intravenous for 2 doses on ICU admission, with clinical improvement. A 56-year-old female hospitalized with worsening SOB, fever, and cough for 8 days saturating 88% on room air in the setting of COVID-19 pneumonia. Worsening hypoxia necessitated high flow nasal cannula. She was transferred to the ICU where she received 2 doses of tocilizumab 400 mg intravenous. She did not require intubation and was transitioned to nasal cannula. A hyperinflammatory syndrome may cause a life-threatening acute respiratory distress syndrome in patients with COVID-19 pneumonia. Tocilizumab is the first marketed interleukin-6 blocking antibody, and through targeting interleukin-6 receptors likely has a role in treating cytokine storm. We noted clinical improvement of patients treated with tocilizumab.

Pkm2 Regulates Cardiomyocyte Cell Cycle and Promotes Cardiac Regeneration

BACKGROUND

The adult mammalian heart has limited regenerative capacity, mostly attributable to postnatal cardiomyocyte cell cycle arrest. In the last 2 decades, numerous studies have explored cardiomyocyte cell cycle regulatory mechanisms to enhance myocardial regeneration after myocardial infarction. Pkm2 (Pyruvate kinase muscle isoenzyme 2) is an isoenzyme of the glycolytic enzyme pyruvate kinase. The role of Pkm2 in cardiomyocyte proliferation, heart development, and cardiac regeneration is unknown.

METHODS

We investigated the effect of Pkm2 in cardiomyocytes through models of loss (cardiomyocyte-specific Pkm2 deletion during cardiac development) or gain using cardiomyocyte-specific Pkm2 modified mRNA to evaluate Pkm2 function and regenerative affects after acute or chronic myocardial infarction in mice.

RESULTS

Here, we identify Pkm2 as an important regulator of the cardiomyocyte cell cycle. We show that Pkm2 is expressed in cardiomyocytes during development and immediately after birth but not during adulthood. Loss of function studies show that cardiomyocyte-specific Pkm2 deletion during cardiac development resulted in significantly reduced cardiomyocyte cell cycle, cardiomyocyte numbers, and myocardial size. In addition, using cardiomyocyte-specific Pkm2 modified RNA, our novel cardiomyocyte-targeted strategy, after acute or chronic myocardial infarction, resulted in increased cardiomyocyte cell division, enhanced cardiac function, and improved long-term survival. We mechanistically show that Pkm2 regulates the cardiomyocyte cell cycle and reduces oxidative stress damage through anabolic pathways and β-catenin.

CONCLUSIONS

We demonstrate that Pkm2 is an important intrinsic regulator of the cardiomyocyte cell cycle and oxidative stress, and highlight its therapeutic potential using cardiomyocyte-specific Pkm2 modified RNA as a gene delivery platform.

Cardiovascular Risk Reduction Associated with Pharmacological Weight Loss: A Meta-Analysis

BACKGROUND

Obesity is a growing pandemic that is associated with multiple cardiovascular disease (CVD) risk factors such as hypertension, diabetes, dyslipidemia and obstructive sleep apnea. With the increase in obesity rates where nearly two thirds of Americans are either obese or overweight, there has been an increase in the use of pharmacological therapy weight loss. While these therapies have shown benefit in weight reduction, the clinical impact these pharmacological agents on overall CVD outcomes has yet to be determined.

AIM

We aimed to assess the effect of pharmacological agents used for weight reduction on CVD risk and all-cause mortality.

METHODS

We conducted a meta-analysis of peer-reviewed literature that evaluated the impact of anti-obesity drugs on cardiovascular outcomes. Key words used included: "orlistat", "lorcaserin", "phentermine/topiramate" or "naltrexone/bupropion" and "cardiovascular outcomes" among others. We reviewed 791 articles, only 47 studies were randomized controlled trials and only 7 studies fulfilled all the inclusion criteria including, quantitative data on cardiovascular risk factors such as, Hemoglobin A1C (A1C), changes in body mass index (BMI), blood pressure and CVD morbidity and mortality. Data was retrieved from these studies and evaluated with comprehensive meta-analysis software^® to assess pooled effects for medical management versus placebo.

RESULTS

There were 7 studies included in the final analysis, with a total of 18,598 subjects, of which 8,685 were in the intervention (INT) group and 9,913 in the control (CTRL) group. For all cause mortality, there were 45 events in the INT and 55 in the CTRL groups, suggesting no significant difference between the two groups (OR: 0.843, 95%CI: 0.571-1.244, Z: -0.860, P: 0.390). For CVD mortality, there were 17 events in the INT and 36 events in the CTRL groups suggesting a significant mortality benefit in the INT group (OR:0.496, 95% CI: 0.282-0.873, Z: -2.433, P: 0.015). There was a significant absolute reduction in A1C in the INT group (Hg: -0.238, 95%CI: -0.291 to -0.186, Z: -8.937, P< 0.001). The percentage weight reduction was significantly higher for the INT group compared to the CTRL group (Hg: -0.431, 95%CI: -0.477 to -0.385, Z: -18.472, P< 0.001) and the blood pressure reduction was higher for the INT group compared to the CTRL group. (Hg: -0.052, 95%CI: -0.101- -0.003, Z: -2.086, P: 0.037). The heterogeneity observed for our meta analysis is Q: 1.884, df: 6, P: 0.930.

CONCLUSIONS

Our study demonstrated the favorable and significant effect of pharmacological weight reduction strategies on weight loss, blood pressure reduction, glycemic control (A1C reduction), and CVD mortality.While weight loss without pharmacological means has been shown to reduce CVD risk, the mechanism by which weight loss medications impact CVD risk reduction could be a direct effect of these agents or merely an effect of weight reduction itself. Weight loss has been noted to modify risk factors via improving insulin sensitivity, reducing inflammation, decreasing blood pressure and modifying the lipid profile, In addition, the mechanism of action of the medications are not directly anti-inflammatory, and do not directly modify insulin sensitivity, blood pressure or the lipid profile. Thus, it is most likely that the benefit on cardiovascular disease from these therapies is via weight reduction and not direct medication effect.Given the limited efficacy of the lifestyle modification on sustained weight loss and the surgical risk and limited availability of bariatric surgical options. Our data suggests pharmacological weight loss therapy may be a valuable treatment option to reduce CVD risk in obese patients. Further research is needed to clarify the effects these therapies on overall mortality and evaluate the mechanisms by which these medications reduce CVD risk factors and mortality.

Nonpharmacologic and Medication Minimization Strategies for the Prevention and Treatment of ICU Delirium: A Narrative Review

Delirium is a multifactorial entity, and its understanding continues to evolve. Delirium has been associated with increased morbidity, mortality, length of stay, and cost for hospitalized patients, especially for patients in the intensive care unit (ICU). Recent literature on delirium focuses on specific pharmacologic risk factors and pharmacologic interventions to minimize course and severity of delirium. While medication management clearly plays a role in delirium management, there are a variety of nonpharmacologic interventions, pharmacologic minimization strategies, and protocols that have been recently described. A PubMed search was performed to review the evidence for nonpharmacologic management, pharmacologic minimization strategies, and prevention of delirium for patients in the ICU. Recent approaches were condensed into 10 actionable steps to manage delirium and minimize medications for ICU patients and are presented in this review.

Assessment of acute head injury in an emergency department population using sport concussion assessment tool - 3rd edition

Sport Concussion Assessment Tool version 3 (SCAT-3) is one of the most widely researched concussion assessment tools in athletes. Here normative data for SCAT3 in nonathletes are presented. The SCAT3 was administered to 98 nonathlete healthy controls, as well as 118 participants with head-injury and 46 participants with other body trauma (OI) presenting to the ED. Reference values were derived and classifier functions were built to assess the accuracy of SCAT3. The control population had a mean of 2.30 (SD = 3.62) symptoms, 4.38 (SD = 8.73) symptom severity score (SSS), and 26.02 (SD = 2.52) standardized assessment of concussion score (SAC). Participants were more likely to be diagnosed with a concussion (from among healthy controls) if the SSS > 7; or SSS ≤ 7 and SAC ≤22 (sensitivity = 96%, specificity = 77%). Identification of head injury patients from among both, healthy controls and body trauma was possible using rule SSS > 7 and headache or pressure in head present, or SSS ≤ 7 and SAC ≤ 22 (sensitivity = 87%, specificity = 80%). In this current study, the SCAT-3 provided high sensitivity to discriminate acute symptoms of TBI in the ED setting. Individuals with a SSS > 7 and headache or pressure in head, or SSS ≤ 7 but with a SAC ≤ 22 within 48-hours of an injury should undergo further testing.

Effects of Varying Levels of Fungal (Arachniotus sp.) Treated Wheat Straw as an Ingredient of Total Mixed Ration on Growth Performance and Nutrient Digestibility in Nili Ravi Buffalo Calves

The study was carried out to explore the effects of replacing wheat straw with fungal treated wheat straw as an ingredient of total mixed ration (TMR) on the growth performance and nutrient digestibility in Nili Ravi buffalo male calves. Fungal treated wheat straw was prepared using Arachniotus sp. Four TMRs were formulated where wheat straw was replaced with 0 (TMR1), 33 (TMR2), 67 (TMR3), and 100% (TMR4) fungal treated wheat straw in TMR. All TMRs were iso-caloric and iso-nitrogenous. The experimental TMRs were randomly assigned to four groups of male calves (n = 6) according to completely randomized design and the experiment continued for four months. The calves fed TMR2 exhibited a significant improve in dry matter intake, average daily weight gain, feed conversion ratio and feed economics compared to other groups. The same group also showed higher digestibility of dry matter, crude protein, neutral-, and acid detergent fibers than those fed on other TMRs. It is concluded that TMR with 33% fungal-treated wheat straw replacement has a potential to give an enhanced growth performance and nutrient digestibility in male Nili Ravi buffalo calves.

Actual and projected incidence rates for chronic subdural hematomas in United States Veterans Administration and civilian populations

OBJECT

Chronic subdural hematomas (SDHs) are more common among veterans and elderly persons than among members of the general population; however, precise incidence rates are unknown. The purposes of this study were 1) to determine the current incidence of chronic SDH in a US Veterans Administration (VA) population and 2) to create a mathematical model for determining the current and future incidence of chronic SDH as a function of population age, sex, and comorbidity in the United States VA and civilian populations.

METHODS

To determine the actual number of veterans who received a radiographic diagnosis and surgical treatment for SDH during 2000-2012, the authors used the VISN03 VA database. On the basis of this result and data from outside the United States, they then created a mathematical model accounting for age, sex, and alcohol consumption to predict the incidence of SDH in the VA and civilian populations during 2012-2040.

RESULTS

Of 875,842 unique (different patient) visits to a VA hospital during the study period, 695 new SDHs were identified on CT images. Of these 695 SDHs, 203 (29%) required surgical drainage. The incidence rate was 79.4 SDHs per 100,000 persons, and the age-standardized rate was 39.1±4.74 SDHs per 100,000 persons. The authors' model predicts that incidence rates of chronic SDH in aging United States VA and civilian populations will reach 121.4 and 17.4 cases per 100,000 persons, respectively, by 2030, at which time, approximately 60,000 cases of chronic SDH will occur each year in the United States.

CONCLUSIONS

The incidence of chronic SDH is rising; SDH is projected to become the most common cranial neurosurgical condition among adults by the year 2030.

Eye tracking detects disconjugate eye movements associated with structural traumatic brain injury and concussion

Disconjugate eye movements have been associated with traumatic brain injury since ancient times. Ocular motility dysfunction may be present in up to 90% of patients with concussion or blast injury. We developed an algorithm for eye tracking in which the Cartesian coordinates of the right and left pupils are tracked over 200 sec and compared to each other as a subject watches a short film clip moving inside an aperture on a computer screen. We prospectively eye tracked 64 normal healthy noninjured control subjects and compared findings to 75 trauma subjects with either a positive head computed tomography (CT) scan (n=13), negative head CT (n=39), or nonhead injury (n=23) to determine whether eye tracking would reveal the disconjugate gaze associated with both structural brain injury and concussion. Tracking metrics were then correlated to the clinical concussion measure Sport Concussion Assessment Tool 3 (SCAT3) in trauma patients. Five out of five measures of horizontal disconjugacy were increased in positive and negative head CT patients relative to noninjured control subjects. Only one of five vertical disconjugacy measures was significantly increased in brain-injured patients relative to controls. Linear regression analysis of all 75 trauma patients demonstrated that three metrics for horizontal disconjugacy negatively correlated with SCAT3 symptom severity score and positively correlated with total Standardized Assessment of Concussion score. Abnormal eye-tracking metrics improved over time toward baseline in brain-injured subjects observed in follow-up. Eye tracking may help quantify the severity of ocular motility disruption associated with concussion and structural brain injury.