Managing Severe Acute Asthma Exacerbation in Pregnancy during the COVID-19 Pandemic: A Case Report from a Resource-limited Setting

BACKGROUND: One-third of pregnant women will experience worsening asthma requiring emergency hospitalization. However, no report comprehensively discussed the management of asthma attacks in pregnant women in impoverished settings. We attempt to illuminate what general practitioners can do to stabilize and improve the outcome of severe acute asthma exacerbations in primary care with resource limitations. CASE REPORT: A nulliparous 29-year-old woman in her 21st week of pregnancy presented severe acute asthma exacerbation in moderate persistent asthma with uncontrolled asthma status along with gestational hypertension, uncompensated metabolic acidosis with a high anion gap, anemia, respiratory infection, and asymptomatic bacteriuria, all of which influenced her exacerbations. This patient was admitted to our resource-limited subdistrict hospital in Indonesia during the COVID-19 pandemic for optimal stabilization. Crystalloid infusions, oxygen supplementation, nebulized beta-agonist with anticholinergic agents, inhaled corticosteroids, intravenous methylprednisolone, broad-spectrum antibiotics, subcutaneous terbutaline, mucolytics, magnesium sulphate, oral antihypertensives, and continuous positive airway pressure were used to treat her life-threatening asthma. After she was stabilized, we referred the patient to a higher-level hospital with more advanced pulmonary management under the supervision of a multidisciplinary team to anticipate the worst scenario of pregnancy termination. CONCLUSION(S): Limitations in primary care, including the lack of sophisticated intensive care units and laboratory panels, may complicate challenges in managing severe acute asthma exacerbation during pregnancy. To enhance maternal-fetal outcomes, all multidisciplinary team members should be well-informed about key asthma management strategies during pregnancy using evidence-based guidelines regarding the drug, rationale, and safety profile.Copyright © 2023 Muhammad Habiburrahman, Triya Damayanti, Mohammad Adya Firmansha Dilmy, Hariyono Winarto.

Analyses of kidney biomarkers in patients with sars-cov-2 (Covid-19)

The new coronavirus was first reported in China and caused a widespread global outbreak of pneumonia that spread rapidly across this country and many other countries. Acute kidney injury is one of the important complications of COVID-19, which has been shown in some cases. Exploring the diagnostic features of biomarkers of kidney function in COVID-19 patients may lead to better patient management. We collected laboratory data from 206 people with confirmed COVID-19 disease and evaluated their renal biomarkers, Blood Urea Nitrogen (BUN), and creatinine. The age range of the patients was almost 62 years old. The mean age in the dead patients and recovered patients was 71 and 54 years old, respectively. The average LDH value was 755 U/L, and creatine phosphokinase (CPK) was 267 U/L in the patients. The average BUN was 59.1 U/L, and creatinine was 1.5 U/L in COVID-2019 patients. Among all 193 patients, laboratory results revealed that 163 (85.4%) patients had an elevated BUN level. Based on creatinine levels for total patients, laboratory results revealed that 49 (25.4%) patients had an elevated value. The average BUN value in dead patients was 85 mg/dL, while in recovered patients was 40.5 mg/dL (P<0.0001). Also, the average creatinine level in dead patients was 1.86 mg/dL, while in recovered patients was 1.24 mg/dL (P=0.0004). Inflammation following COVID-19 disease causes kidney damage and elevated urea and creatinine levels, which may increase the risk of death in these patients.Copyright © 2023 Tehran University of Medical Sciences.

Laboratory characteristics among patients with COVID-19: a single-center experience from Khartoum, Sudan

Background: COVID19 is associated with a number of laboratory characteristics and changes with different levels of prognostic significance. We report changes in lab findings between severe and non-severe COVID-19 in patients that had molecular testing of nasopharyngeal swabs in Khartoum, Sudan Material(s) and Method(s): This was a descriptive cross-sectional study, conducted from Jan to May 2021. It included 66 preidentified COVID19 patients who attended the isolation center at Jabra Hospital in Khartoum the capital city of Sudan. Participants were enrolled for CBC, D-dimer and C-Reactive Protein testing. Among these participants, 21(31.8%) had severe COVID19 pneumonia.. Data were analysed using SPSS version 24, and the independent sample t-test was used to compare severe and non-sever cases. Result(s): The mean values for all cases showed a mild decrease in Hb (9.53+/-1.83 g/dl), MCHC (28.3+/-2.91 g/dl);lymphocytes % (19.8 +/-6.82);increased RDW-SD (50.1+/-5.70 fL), D-dimer (4.2+/-3.73 mug/ml) and CRP (107.2+/-61.21 mg/dl). There were significant d/span>differences in the laboratory findings between severe and non-severe COVID-19 cases in total WBCs (p value = .001), lymphocyte % (p value = .000), neutrophil % (p value=.038), RDW-SD (p value = .044), D-dimer (p value = .029) and CRP (p value = .044). Conclusion(s): The laboratory findings of CBC, D-dimer and CRP provide an essential contribution to predicti COVID-19 severity and prognosis.Copyright © 2023 Mohamed EAA et al.

Lab Parameter among Corona Patients

Introduction: The COVID-19 pandemic has been raging across the globe since early January 2020. Various geographical regions have been passing multiple swells of upsurge of cases which aren't matched temporally as well as in severity. The diapason of the complaint ranges from asymptomatic to severe life-hanging complaint. Advanced age and the presence of comorbidities similar as cardiovascular complaint, diabetes mellitus, hypertension, chronic lung complaint, chronic kidney complaint, cancer, and obesity are among the major threat factors for severe disease. Aims and objectives: Significance of lab parameter among Corona Patients. Materials and methods: The covid- 19 opinion was verified by reverse transcription- polymerase chain reaction (RT- PCR) assay of nasopharyngeal swab sample. Hematology blood samples were used to analyze by flow cytometry. Biochemical samples were used to analyze by completely auto analyzer diagnostic outfit. Serology tests were carried out the styles based on indirect ELISA technique, immune plates are coated with a admixture of purified viral antigen and probe using the patient serum. Results: It is found that there is statistically significant (p-value<0.05) mean difference within the lab parameters (IL-6, LDH and Ferritin) in Covid patients using the Post Hoc Analysis. It is also found that there statistically significant (p-value<0.05) mean difference between RBC, Hb level, Hematocrit, MCV, MCH, MCHC, Platelet, RDW, PCT and NL ratio while Age, WBC, MPV, M(Monocyte), E(Eosinophil), B(Basophil), D-dimer and PDW were found to be statistically insignificant (p-value>0.05) with respect to gender. Discussion: CBC, D- dimer, IL-6, LDH and Ferritin were analysed and found associated with adverse outcomes. There is significant association of age, gender, comorbidity. Conclusion: High NLR at admission associated with a higher mortality. Laboratory features (e.g., IL-6, LDH, Ferritin D-dimer etc.) were associated with poor outcomes.

Dynamic Changes in Routine Laboratory Parameters with COVID-19: In-depth Analysis of 17 Patients Requiring Critical Care

—Dynamic changes in routine blood parameters in COVID-19 patients might be helpful to prognosticate deterioration in COVID-19 patients and evaluate treatment effect. Our study aimed to evaluate the temporal changes in red blood cell indices (MCV, MCH, MCHC, RDW) in COVID-19 patients and the association of other relevant clinical parameters. We analysed 17 medical records of COVID-19 patients in retrospect who required critical care from 1 January 2020 until 28 February 2021 in Hospital Tuanku Fauziah, Perlis, Malaysia. Data extracted include details with regards to escalation and de-escalation of oxygen therapy, clinical and laboratory parameters. There were three time points of interest in our study: (i) admission (Adm), (ii) highest mode of oxygen therapy (HighM), and (iii) weaned off oxygen therapy (WeanOxy). The result showed that the mean duration to clinical deterioration requiring the highest mode of oxygen delivery was 2.3 ±1.85 days and the highest escalation device for oxygen delivery was high flow nasal cannula (n=7, 41.2%). There was no statistically significant difference in RDW, MCV, MCH, and MCHC at different clinical time points, p>0.05. However, there was a statistically significant increment in TWBC trend between Adm-HighM-WeanOxy, χ2(2)=7.023, p=0.030. Our study did not find evidence of structural RBC changes reflected in RBC indices. However, recovery from COVID-19 was reflected in the rise of TWBC and ANC, similar to that observed with other viral illnesses.

Haematological changes & inhospital mortality in severe COVID -19

COVID-19 is an acute respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first detected in China (December 2019) but now widespread. The aim of this study was to investigate the main haematological changes in severe cases of COVID-19 and if full blood count results at admission can be used to determine in-hospital mortality risk. This retrospective observational study included laboratory results of confirmed cases of hospitalised patients with SARS-CoV2 infection in Jersey between March and December 2020 (subject to inclusion criteria), split into two subgroups based on outcome (non-survivors versus survivors). Statistically significant changes between groups were defined by probability ( p ) <0.05, using t -test, Mann-Whitney test, or X2 /Fisher exact test, as appropriate. Multivariate and univariate logistic models were used to determine risk factors for in-hospital mortality. A total of 81 cases (out of 113 available cases) were included in this study: median age: 75 years;48 patients were men (59.3%);27 non-survivors (33.3%) and 18 (22%) required intensive care. Non-survivors showed the following statistically significant changes compared to survivors: non-survivors were older (median age: 82 vs. 74 years, p = 0.003);70.4% presented with marked lymphopenia (median: 0.63 vs. 0.99 × 109 /l, p = 0.025), 55.6% with raised creatinine (median: 103.0 μmol/l, p = 0.024), 40.7% with elevated white blood cells (WBC) (median: 9.5 vs. 7.3 × 109 /l, p = 0.042) and 14.8% with lower mean cell haemoglobin concentration (MCHC) (32.99 vs. 33.79 g/dl, p = 0.030). Univariate analysis showed age ≥ 82 years was significantly associated with death (odds ratio [OR] = 4.210, p = 0.005). Multivariate logistic analysis identified the following risk factors for in-hospital mortality: lymphocytes <0.85 × 109 /l (OR = 6.694, p = 0.004), WBC >9.5 × 109 /l (OR = 4.855, p = 0.015) and creatinine >100 μmol/l (OR = 3.280, p = 0.049). Full blood count results on hospital admission can be used to identify COVID-19 patients with higher mortality risk. Inhospital mortality risk was shown to be 6.7 times higher in patients presenting with a lymphocyte count <0.85 × 109 /l, 4.9 times higher in patients presenting with a WBC >9.5 × 109 /l and 3.3 times higher for those presenting with creatinine levels over 100 μmol/l. Age ≥ 82 years was significantly associated with death. Additionally, this study suggests male gender is a risk factor for hospital admission in COVID-19.

Clinicohaematological Patterns of Anemia and Correlation with Clinical Conditions in Children Aged 5 to 12 Years in Tertiary Care Centre

Objective: To classify the haematological pattern, severity of anemia in children 5-12 years age admitted and to find its correlation with the clinical conditions. Methods Crossectional study of 160 patients in two years was done. Patients satisfying the inclusion criteria were selected for study. Relevant clinical data were recorded in a structured proforma including detailed history was recorded with particular symptoms suggestive of anemia such as weakness and easily fatigability, breathlessness on exertion and pica. A thorough clinical examination of every child was done followed by routine investigations for anemia Results Patients between 7-8 year were found to be the most affected. Anemia was found to be more common in female children as compared to male children (F:M=1.13). Anemia is more common in undernourished child. Most common presenting symptoms were gastrointestinal including vomiting, diarrhea and pain abdomen. Most common sign was Pallor followed by other common signs included signs of dehydration associated with diarrhea, hepatosplenomegaly. microcytic hypochromic anemia was the most common morphological type of anemia and macrocytic anemia was the least common.Thalassemia cases were most common among hemolytic anemias. Iron Deficiency Anemia (Nutritional Anemia) was the most common etiology of anemia. Conclusion Dietary deficits affect children aged 5 to 12, creating financial, emotional, and psychological burden for patients and their families, as well as depleting critical national resources. As a result, screening for these illnesses, as well as early detection of anemia and related problems, is essential.

Early prediction of COVID-19 mortality risk based on demographic, vital sign and blood test

Background: Early prediction of the outcome situation of COVID-19 patients can decrease mortality risk by assuring efficient resource allocation and treatment planning. This study introduces a very accurate and fast system for the prediction of COVID-19 outcomes using demographic, vital signs, and laboratory blood test data. Methods: In this analytic study, which is done from May 2020 to June 2021 in Tehran, 41 features of 244 COVID-19 patients were recorded on the first day of admission to the Masih Daneshvari Hospital. These features were categorized into eight different groups, demographic and patient history features, vital signs, and six different groups of laboratory blood tests including complete blood count (CBC), coagulation, kidney, liver, blood gas, and general. In this study, first, the significance of each of the extracted features and then the eight groups of features for prediction of mortality outcomes were considered, separately. Finally, the best combination of different groups of features was assessed. The statistical methods including the area under the receiver operating characteristic curve (AUC-ROC) based on binary Logistic Regression classification algorithm were used for evaluation. Results: The results revealed that red cell distribution width (RDW), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and mean corpuscular volume (MCV) in CBC features have the highest AUC with values of 85.29, 80.96, 79.94 and 79.70, respectively. Then, blood oxygen saturation level (SPO2) in vital features has a higher AUC with a value of 79.28. Moreover, combinations of features in the CBC group have the highest AUC with a value of 95.57. Then, coagulation and vital signs groups have the highest AUC with values of 85.20 and 83.84, respectively. Finally, triple combinations of features in CBC, vital signs, and coagulation groups have the highest AUC with the value of 96.54. Conclusion: Our proposed system can be used as an assistant acceptable tool for triage of COVID-19 patients to determine which patient will have a higher risk for hospitalization and intensive care in medical environments.

HEMATOBIOCEMICAL AND HISTOPATHOLOGICAL STUDIES ON THE EFFECTS OF RAJ NIRWAN BATI (A NOVEL ALLOVEDIC DRUG) IN WISTAR RATS

Objective: To see the effects of Raj Nirwan Bati (RNB) on the hematobiochemical parameters, coagulation tests, and histopathological changes in the lungs, liver, kidneys and spleen and also to evaluate the immunomodulatory activity of RNBin Wistar rats. Methods: A total of 24 adult albino Wistar rats (of bodyweight 200-250 g) of either sex were divided into 3 groups. In the normal control group (n=8), no drug was administered and in the rest of the groups (A and B), RNB@ 26 mg/kg body weight./day and 260 mg/kg body weight/day respectively were administered orally for a period of 14 d. The blood samples were collected from the jugular vein at zero d (before drug administration) and after the 14th d of drug administration in both groups (A and B). The organ samples (lungs, liver, kidneys, and spleen) were collected after euthanizing the rats using Ketamine anesthesia overdose intraperitoneally (IP) after the 14th d of drug administration. White Blood Cells (WBC), Red Blood Cells (RBC), Hemoglobin (Hb), Hematocrit (HCT), Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin(MCH), Mean Corpuscular Hemoglobin Concentration(MCHC), number of platelets, Differential Leucocyte Count(DLC) i.e. the percentage of neutrophils, lymphocytes, eosinophils, monocytes and basophils, neutrophil adhesion percentage, Prothrombin test (PT), Activated Partial Thromboplastin Time (APTT), fibrinogen, D-dimer, Lactate Dehydrogenase (LDH), urea, creatinine, Aspartate Amino Transferase (AST), Alanine amino Transferase (ALT), Alkaline Phosphatase (ALP), C-Reactive Protein (CRP) were evaluated and histological examination of organs were done. Results: After statistical analysis, it was found that the decrease in TLC, RBC, Hb, HCT, and LDH in Wistar rats after RNB intervention in Group A as compared to that of before RNB intervention, was found to be statistically significant (P=0.001, P=0.002, P=0.001, P=0.039, and P=0.008). On the other hand, an increase was observed in MCV, Urea, Creatinine and ALT values in the Wistar rats after RNB intervention in Group ‘A’ as compared to that of before RNB intervention and this increase in values was statistically significant (P=0.007, P=0.001, P<0.001 and P=0.038). After RNB intervention in Group B, the increase in MCH, fibrinogen concentration, and monocytes percentage, was found to be statistically significant (P=0.004, P=0.033, and P=0.001) as well as the decrease in PT and APTT was statistically significant (P=0.007and P=0.002). After comparing the Mean Hematobiochemical and coagulation test parameters in the rats of Group A and Group B, after RNB intervention, it was observed that the concentration of Urea, Creatinine, APTT, and D-dimer were less in Group B as compared to that of Group A and this difference was statistically significant(P<0.001, P<0.001, P<0.001 and P=0.022). Histologically the findings in the lungs of group B were more distortion of lung architecture, most of the alveoli become collapse and make emphysematous changes, more diffuse inflammatory infiltrate within interalveolar septa and around bronchioles as compared to Group A. In the liver of group B rats, the histological findings were mild to moderate distortion of lobular architecture, healthy hepatocytes with more activation of kupffer cells as well as larger and more aggregates of inflammatory cells as compared to group A. Histological findings of kidneys in group A and group B rats were similar to that of control group rats. Conclusion: The results suggest that the RNB is having an immunomodulatory effect. It might be helpful in the restoration of coagulation factors and can help treat the COVID patients. No harmful effects on the lungs, liver, kidney, and spleen were seen. These findings may act as baseline data for planning further clinical trials in human study subjects to evaluate the effects on various comorbidities.

Hematological Predictors of COVID-19 Severity

Introduction: COVID-19 pandemic has placed the health systemworldwide in unprecedented stress, therefore, prompt identification and management of patients having severe disease is essential fortriaging of patients at the time of admission.Aims &Objectives: To identify hematological biomarkers ofCOVID-19 disease severity in patients admitted in a tertiary carehospital.Materials &Methods: A retrospective study was conducted over aperiod of 17 months (20th March 2020-19 August 2021) on 7416COVID-19 patients. Patients with cancers, pregnancy and chronichematological diseases were excluded from the study. Patients wereclassified clinically as per severity of disease as non-severe (asymptomatic, mild, moderate) or severe and their hematological parameterswere analyzed.Mann-Whitney test was used to compare between the groups. Optimal predictive cut off points for the variables were defined by receiveroperating characteristic (AUC) curve to dichotomize the variables.Univariate analysis was performed to screen out independent variables to be used in the binary logistic regression (BLR). A p valueof< = 0.05 was considered as statistically significant.Result: Age, duration of hospital stay, RBC count, WBC, Plateletcount, RDW, Neutrophils %, Absolute neutrophil count (ANC),Absolute monocyte count (AMC), NLR, PLR, NMR were statisticallyhigher whereas hemoglobin, hematocrit, MCHC, lymphocyte %,Absolute lymphocyte count (ALC), Eosinophils %, Absolute eosinophil count (AEC), Monocytes %, Basophils %, Absolute Basophilcount (ABC) and Lymphocyte Monocyte ratio (LMR) were lower insevere group. MCV and MCHC were not significant, so wereexcluded from the logistic regression model. All variables were significant in univariate analysis. Age (>42 yrs), duration of hospitalstay (>10 days), RBC count (B 4.33 106/lL),WBC count (> 7.73103/lL), RDW (>14.8%), Neutrophils (>71.7%), Eosinophils(B 0.3%), Monocytes (B 5%), ALC (B 1.01 103/lL), LMR(B 3.125) with adjusted odd ratio of 1.8, 1.5, 1.3,1.3, 1.4, 2.0, 2.1, 1.5,2.0 and 1.3 respectively were found to be significant predictors ofseverity.Conclusions: Age, duration of hospital stay, RBC count, WBC,RDW, Neutrophils %, Eosinophils %, Monocytes %, ALC, LMRshould be assessed and monitor at the earliest to halt unfavorableoutcome of mortality or morbidity.

Hematologic parameters as potential diagnostic tools for COVID-19 in emergency setting

Currently, the real-time reverse transcription-polymerase chain reaction test is the gold stan-dard for diagnosing COVID-19. However, real-time reverse transcription-polymerase chain reaction requires a long turnaround time, expensive equipment, specialized laboratory, and trained personnel. Thus, accessible, fast, and accurate tests are needed, especially in emergency settings. This study aims to evaluate roles and cut off points in hematological parameters for COVID-19 screening in emergency settings. We retrospectively evaluated hematological features in 250 patients who have visited the emergency department with suspect COVID-19 infection. Hematological parameters were compared in patients with positive and negative COVID-19 group. Receiver operating characteristic curves were made to determine significant hematological parameter cutoff point for diagnosing COVID-19 patients. Comparisons between positive and negative COVID-19 groups revealed there was no statisti-cal significant difference (p>0.05) between test groups regarding eosinophil, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, throm-bocytes, red blood cell distribution width, erythrocyte sedimentation rate, sodium, potassium, calcium, and high-sensitivity C-reactive protein. Significant differences (p<0.05) were found between test groups regarding hemoglobin, leukocyte, neutrophil, lymphocyte, monocyte, basophil, hematocrit, erythrocyte, mean platelet volume, neutrophil-lymphocyte ratio, absolute lymphocyte count, platelet-to-lymphocyte ratio, and monocyte-lymphocyte ratio. The highest area under the curve was found in lymphocyte with cut off point ≥17.6 (area under curve: 0.721;p=0.000;95% confidence interval: 0.656-0.785). Blood test analysis might be used as a screening method for COVID-19 using certain hematologi-cal parameters. It is instrumental in the emergency department, which needs a fast screening method.

Routine laboratory parameters predict serious outcome as well as length of hospital stay in COVID-19.

OBJECTIVES: To validate C-reactive protein (CRP), red cell distribution width (RDW), and neutrophil lymphocyte ratio (NLR) for both serious outcomes and length of hospital stay (LOS) among hospitalized coronavirus disease-19 (COVID-19) patients. METHODS: Laboratory data of adult COVID-19 patients (n=74) was collected in this retrospective cohort. Logistic regression was employed for risk factor evaluation and receiver operating curve was used for comparison of these risk factors for the prediction of serious outcome. Multiple regression was applied to determine the association between routine analytes and LOS. RESULTS: Higher levels of CRP (3 times), white blood cells (20%), and neutrophil counts (40%) were seen in the serious category. Odds ratio for CRP for the serious outcome was 1.052 (p=0.007) and RDW for the serious outcome was 1.218 (p=0.040) in unadjusted model and odds ratio for CRP for the serious outcome was 1.048 (p=0.024) and for RDW 1.286 (p=0.023) in adjusted model. In a multivariate regression analysis for the LOS of the unadjusted models consisting of NLR, monocyte lymphocyte ratio (MLR) and platelet lymphocyte ratio (PLR), the beta coefficients (BC) for the CRP were 0.006 (NLR), 0.005 (MLR) and 0.006 (PLR), whereas -0.029 (NLR), -0.034 (MLR) and -0.027 (PLR) were BCs for mean corpuscular hemoglobin concentration (MCHC). Additionally, in adjusted models, the BCs for MCHC were -0.044 (NLR), -0.047 (MLR) and -0.043 (PLR). However, the CRP was consistent with 0.004 (BC) in all models. CONCLUSION: We observed that CRP is a better predictor than RDW and NLR for serious outcome among COVID-19 patients. Besides, CRP was positively, whereas MCHC was negatively associated with LOS.

Artificial intelligence in clinical care amidst COVID-19 pandemic: A systematic review.

The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in>3 million deaths so far. Improving early screening, diagnosis and prognosis of the disease are critical steps in assisting healthcare professionals to save lives during this pandemic. Since WHO declared the COVID-19 outbreak as a pandemic, several studies have been conducted using Artificial Intelligence techniques to optimize these steps on clinical settings in terms of quality, accuracy and most importantly time. The objective of this study is to conduct a systematic literature review on published and preprint reports of Artificial Intelligence models developed and validated for screening, diagnosis and prognosis of the coronavirus disease 2019. We included 101 studies, published from January 1st, 2020 to December 30th, 2020, that developed AI prediction models which can be applied in the clinical setting. We identified in total 14 models for screening, 38 diagnostic models for detecting COVID-19 and 50 prognostic models for predicting ICU need, ventilator need, mortality risk, severity assessment or hospital length stay. Moreover, 43 studies were based on medical imaging and 58 studies on the use of clinical parameters, laboratory results or demographic features. Several heterogeneous predictors derived from multimodal data were identified. Analysis of these multimodal data, captured from various sources, in terms of prominence for each category of the included studies, was performed. Finally, Risk of Bias (RoB) analysis was also conducted to examine the applicability of the included studies in the clinical setting and assist healthcare providers, guideline developers, and policymakers.