Haplotype analysis of long-tailed macaques in TNB Bukit Selambau, Peninsular Malaysia, leads to inferences of fissionfusion social structure

Long-tailed macaques have been roaming near Tenaga National Berhad Bukit Selambau Solar(TBSS) causing human–macaque conflicts. This study reveals the social organization and genetic variation of these macaques. Macaques’ groups were determined via direct observation and closed circuit television. Genomic DNA from 29 fecal samples were extracted and proceeded with amplification of the D-loop region of mitochondrial DNA. There are four main groups of primates at TBSS. Some members of the Kuil group and the Pekan group shared haplotype 1, forming a fission-fusion society. This finding can be used for TNB in mitigation plans involving human– macaque conflict

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Haplotype analysis of long-tailed macaques in TNB Bukit Selambau, Peninsular Malaysia, leads to inferences of fissionfusion social structure

Long-tailed macaques have been roaming near Tenaga National Berhad Bukit Selambau Solar (TBSS) causing human–macaque conflicts. This study reveals the social organization and genetic variation of these macaques. Macaques’ groups were determined via direct observation and closedcircuit television. Genomic DNA from 29 fecal samples were extracted and proceeded with amplification of the D-loop region of mitochondrial DNA. There are four main groups of primates at TBSS. Some members of the Kuil group and the Pekan group shared haplotype 1, forming a fission-fusion society. This finding can be used for TNB in mitigation plans involving human– macaque conflict

Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

Background: COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods: This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results: Of 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83-0.93]). Conclusion: Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders

Liver injury in hospitalized patients with COVID-19: An International observational cohort study

Background: Using a large dataset, we evaluated prevalence and severity of alterations in liver enzymes in COVID-19 and association with patient-centred outcomes.MethodsWe included hospitalized patients with confirmed or suspected SARS-CoV-2 infection from the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) database. Key exposure was baseline liver enzymes (AST, ALT, bilirubin). Patients were assigned Liver Injury Classification score based on 3 components of enzymes at admission: Normal; Stage I) Liver injury: any component between 1-3x upper limit of normal (ULN); Stage II) Severe liver injury: any component & GE;3x ULN. Outcomes were hospital mortality, utilization of selected resources, complications, and durations of hospital and ICU stay. Analyses used logistic regression with associations expressed as adjusted odds ratios (OR) with 95% confidence intervals (CI).ResultsOf 17,531 included patients, 46.2% (8099) and 8.2% (1430) of patients had stage 1 and 2 liver injury respectively. Compared to normal, stages 1 and 2 were associated with higher odds of mortality (OR 1.53 [1.37-1.71]; OR 2.50 [2.10-2.96]), ICU admission (OR 1.63 [1.48-1.79]; OR 1.90 [1.62-2.23]), and invasive mechanical ventilation (OR 1.43 [1.27-1.70]; OR 1.95 (1.55-2.45). Stages 1 and 2 were also associated with higher odds of developing sepsis (OR 1.38 [1.27-1.50]; OR 1.46 [1.25-1.70]), acute kidney injury (OR 1.13 [1.00-1.27]; OR 1.59 [1.32-1.91]), and acute respiratory distress syndrome (OR 1.38 [1.22-1.55]; OR 1.80 [1.49-2.17]).ConclusionsLiver enzyme abnormalities are common among COVID-19 patients and associated with worse outcomes

Association of Country Income Level With the Characteristics and Outcomes of Critically Ill Patients Hospitalized With Acute Kidney Injury and COVID-19

Introduction: Acute kidney injury (AKI) has been identified as one of the most common and significant problems in hospitalized patients with COVID-19. However, studies examining the relationship between COVID-19 and AKI in low- and low-middle income countries (LLMIC) are lacking. Given that AKI is known to carry a higher mortality rate in these countries, it is important to understand differences in this population. Methods: This prospective, observational study examines the AKI incidence and characteristics of 32,210 patients with COVID-19 from 49 countries across all income levels who were admitted to an intensive care unit during their hospital stay. Results: Among patients with COVID-19 admitted to the intensive care unit, AKI incidence was highest in patients in LLMIC, followed by patients in upper-middle income countries (UMIC) and high-income countries (HIC) (53%, 38%, and 30%, respectively), whereas dialysis rates were lowest among patients with AKI from LLMIC and highest among those from HIC (27% vs. 45%). Patients with AKI in LLMIC had the largest proportion of community-acquired AKI (CA-AKI) and highest rate of in-hospital death (79% vs. 54% in HIC and 66% in UMIC). The association between AKI, being from LLMIC and in-hospital death persisted even after adjusting for disease severity. Conclusions: AKI is a particularly devastating complication of COVID-19 among patients from poorer nations where the gaps in accessibility and quality of healthcare delivery have a major impact on patient outcomes

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use

Implementation of Recommendations on the Use of Corticosteroids in Severe COVID-19

Importance: Research diversity and representativeness are paramount in building trust, generating valid biomedical knowledge, and possibly in implementing clinical guidelines. Objectives: To compare variations over time and across World Health Organization (WHO) geographic regions of corticosteroid use for treatment of severe COVID-19; secondary objectives were to evaluate the association between the timing of publication of the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial (June 2020) and the WHO guidelines for corticosteroids (September 2020) and the temporal trends observed in corticosteroid use by region and to describe the geographic distribution of the recruitment in clinical trials that informed the WHO recommendation. Design, setting, and participants: This prospective cohort study of 434 851 patients was conducted between January 31, 2020, and September 2, 2022, in 63 countries worldwide. The data were collected under the auspices of the International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC)-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Analyses were restricted to patients hospitalized for severe COVID-19 (a subset of the ISARIC data set). Exposure: Corticosteroid use as reported to the ISARIC-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Main outcomes and measures: Number and percentage of patients hospitalized with severe COVID-19 who received corticosteroids by time period and by WHO geographic region. Results: Among 434 851 patients with confirmed severe or critical COVID-19 for whom receipt of corticosteroids could be ascertained (median [IQR] age, 61.0 [48.0-74.0] years; 53.0% male), 174 307 (40.1%) received corticosteroids during the study period. Of the participants in clinical trials that informed the guideline, 91.6% were recruited from the United Kingdom. In all regions, corticosteroid use for severe COVID-19 increased, but this increase corresponded to the timing of the RECOVERY trial (time-interruption coefficient 1.0 [95% CI, 0.9-1.2]) and WHO guideline (time-interruption coefficient 1.9 [95% CI, 1.7-2.0]) publications only in Europe. At the end of the study period, corticosteroid use for treatment of severe COVID-19 was highest in the Americas (5421 of 6095 [88.9%]; 95% CI, 87.7-90.2) and lowest in Africa (31 588 of 185 191 [17.1%]; 95% CI, 16.8-17.3). Conclusions and relevance: The results of this cohort study showed that implementation of the guidelines for use of corticosteroids in the treatment of severe COVID-19 varied geographically. Uptake of corticosteroid treatment was lower in regions with limited clinical trial involvement. Improving research diversity and representativeness may facilitate timely knowledge uptake and guideline implementation

Thrombotic and hemorrhagic complications of COVID-19 in adults hospitalized in high-income countries compared with those in adults hospitalized in low- and middle-income countries in an international registry

Background: COVID-19 has been associated with a broad range of thromboembolic, ischemic, and hemorrhagic complications (coagulopathy complications). Most studies have focused on patients with severe disease from high-income countries (HICs). Objectives: The main aims were to compare the frequency of coagulopathy complications in developing countries (low- and middle-income countries [LMICs]) with those in HICs, delineate the frequency across a range of treatment levels, and determine associations with in-hospital mortality. Methods: Adult patients enrolled in an observational, multinational registry, the International Severe Acute Respiratory and Emerging Infections COVID-19 study, between January 1, 2020, and September 15, 2021, met inclusion criteria, including admission to a hospital for laboratory-confirmed, acute COVID-19 and data on complications and survival. The advanced-treatment cohort received care, such as admission to the intensive care unit, mechanical ventilation, or inotropes or vasopressors; the basic-treatment cohort did not receive any of these interventions. Results: The study population included 495,682 patients from 52 countries, with 63% from LMICs and 85% in the basic treatment cohort. The frequency of coagulopathy complications was higher in HICs (0.76%-3.4%) than in LMICs (0.09%-1.22%). Complications were more frequent in the advanced-treatment cohort than in the basic-treatment cohort. Coagulopathy complications were associated with increased in-hospital mortality (odds ratio, 1.58; 95% CI, 1.52-1.64). The increased mortality associated with these complications was higher in LMICs (58.5%) than in HICs (35.4%). After controlling for coagulopathy complications, treatment intensity, and multiple other factors, the mortality was higher among patients in LMICs than among patients in HICs (odds ratio, 1.45; 95% CI, 1.39-1.51). Conclusion: In a large, international registry of patients hospitalized for COVID-19, coagulopathy complications were more frequent in HICs than in LMICs (developing countries). Increased mortality associated with coagulopathy complications was of a greater magnitude among patients in LMICs. Additional research is needed regarding timely diagnosis of and intervention for coagulation derangements associated with COVID-19, particularly for limited-resource settings

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients