Risk predictors of progression to severe disease during the febrile phase of dengue: a systematic review and meta-analysis

Re-emergence of arbovirus diseases in the State of Rio de Janeiro, Brazil: The role of simultaneous viral circulation between 2014 and 2019

The burden of arbovirus diseases in Brazil has increased within the past decade due to the emergence of chikungunya and Zika and endemic circulation of all four dengue serotypes. Changes in temperature and rainfall patterns may alter conditions to favor vector-host transmission and allow for cyclic re-emergence of disease. We sought to determine the impact of climate conditions on arbovirus co-circulation in Rio de Janeiro, Brazil. We assessed the spatial and temporal distributions of chikungunya, dengue, and Zika cases from Brazil's national notifiable disease information system (SINAN) and created autoregressive integrated moving average models (ARIMA) to predict arbovirus incidence accounting for the lagged effect of temperature and rainfall. Each year, we estimate that the combined arboviruses were associated with an average of 8429 to 10,047 lost Disability-Adjusted Life Years (DALYs). After controlling for temperature and precipitation, our model predicted a three cycle pattern where large arbovirus outbreaks appear to be primed by a smaller scale surge and followed by a lull of cases. These dynamic arbovirus patterns in Rio de Janeiro support a mechanism of susceptibility enhancement until the theoretical threshold of population immunity allows for temporary cross protection among certain arboviruses. This suspected synergy presents a major public health challenge due to overlapping locations and seasonality of arbovirus diseases, which may perpetuate disease burden and overwhelm the health system.

A cross-sectional study to assess the epidemiological situation and associated risk factors of dengue fever; knowledge, attitudes, and practices about dengue prevention in Khyber Pakhtunkhwa Province, Pakistan

Background

Dengue fever has been responsible for around 12 countrywide large outbreaks in Pakistan, resulting in 286,262 morbidities and 1,108 deaths. Khyber Pakhtunkhwa (KP) is the most recently impacted province. This study aimed to investigate the molecular, epidemiological, and potential elements that contribute to increasing dengue transmission patterns, and knowledge, attitude, and practice (KAP) toward dengue in KP province.

Method

This cross-sectional community-based study was conducted (June-December, 2021) in two phases. Phase I involved the epidemiological (n = 5,242) and molecular analysis of DENV in 500 randomly collected blood samples of the 2021 dengue outbreak in KP. Phase II focused on assessing dengue-KAP levels in healthy communities (n = 14,745, aged >18 years), adopting a cross-sectional clustered multistage sampling in eight districts (dengue-hotspot vs. non-hotspot) of KP. Chi-square tests and logistic regression analysis were applied.

Results

Peshawar district had the highest dengue cases (60.0%) associated with the predominant co-circulation of DENV-2 (45.8%) and DENV-3 (50.4%) serotypes. A rise in cases was reported in October (41.8%) followed by September (27.9%) and August (14.4%; p < 0.001). Males (63.7%, p < 0.001) and individuals aged 16–30 years (37.0%, p < 0.001) were highly affected. General workers (18.0%), families with a monthly income of 10,000–20,000 Pak rupees (50.5%), unmarried (71.0%), uneducated (31%), families with higher human density (>10 individuals per household), and those (29.0%) who faced power outages for more than 7/24 h were the most affected. Moreover, co-morbidities like renal failure and bronchial asthma were associated with disease severity. A community survey on KAP revealed that an average of 74, 60, and 43% of the participants demonstrated good knowledge, attitudes, and dengue preventive practices, respectively.

Conclusion

Multiple poor socioeconomic elements are influencing dengue fever transmission in the province. Higher KAP levels may explain the low frequency of dengue in non-hotspot districts. Our study emphasizes the need for effective and long-term public health education, strengthened vector surveillance, and expanded laboratory capacity for better diagnosis and management of dengue cases to better predict the burden and seasonality of disease in the country.

[Important arboviral diseases in returning travelers: dengue, chikungunya and zika]

Arboviral infections are an important differential diagnosis in returning travelers with fever, muscle or joint pain and rash. Arboviruses have spread widely around the globe in the last decades. The most common arboviral infections in returning travelers from tropical and subtropical areas are dengue, chikungunya and zika. Their most important vectors, Aedes (Stegomyia) mosquito species, have adapted to the urban environment, which enabled arboviruses to establish urban transmission cycles. Population growth, urbanization, globalization, modern means of transportation and global warming are speeding up their spread.Laboratory confirmation of an arboviral infection can generally be obtained by direct virus detection (PCR, antigen test) in the first week of illness; from the second week of illness serology can be used. Treatment is mostly symptomatic.Dengue fever is the most common cause of fever in returning travelers from South-East Asia. Patients have to be educated about and observed for warning signs of severe dengue that can rarely develop around day 5 of the disease and is marked by a rise in hematocrit.Chikungunya mostly occurs in epidemics and is characterized by severe and often long-lasting arthritis.Preconceptional screening for zika virus infection is not recommended. Instead, travelers should delay conception for up to three months after returning from a zika endemic area.Dengue, chikungunya and zika vaccine development has been hampered by difficulties, for example antibody-dependent-enhancement or the unpredictability of outbreaks, and up to now no vaccines for travelers have been licensed. Yet several promising vaccine candidates are currently under development.

Warning Signs in Predicting Severe Pediatric Dengue Infection

Objective The uncertainty of dengue's progression from infection to its severe form represents a major health care challenge, especially in children. Clinical identification of impending clinical manifestations of severe dengue (SD), along with proper and immediate management, is crucial. Thus, this study assesses the ability of warning signs to predict SD infection in pediatric patients.

Methods This cross-sectional study utilized purposive sampling using medical records from January 2015 to December 2020. Children aged 0 to 18 years diagnosed with dengue fever and SD according to the World Health Organization's 2009 criteria were included.

Discussion Multivariate analysis revealed that abdominal pain (odds ratio [OR]: 16.34; 95% confidence interval [CI]: 3.78–70.64; p < 0.001), fluid accumulation (OR: 10.51, 95% CI: 1.17–94.3; p = 0.036), mucosal bleeding (OR: 4.77; 95% CI: 1.27–17.91; p = 0.021), lethargy (OR: 94.37; 95% CI: 4.92–180.79; p = 0.003), hepatomegaly (OR: 17.57; 95% CI: 2.14–144.13; p = 0.008), and increased hematocrit concurrent with a rapid decrease in platelets (OR: 6.89; 95% CI: 1.79–26.51, p = 0.005) were associated with SD infection, with a high quality of discrimination (area under the curve [AUC] = 0.96) and a high quality of fit (p = 0.73). Receiver operating characteristic analysis demonstrated that 1.5 warning signs was the optimal cut-off for predicting SD infection, with a sensitivity of 90.9 and a specificity of 89.8%.

Conclusion All six warning signs were significantly associated with SD infection. The optimal cut-off for predicting SD was 1.5 warning signs.

Study of Utility of Basic Arterial Blood Gas Parameters and Lactate as Prognostic Markers in Patients With Severe Dengue

Background

The importance of prognostication in critical care cannot be over-emphasized, especially in the context of diseases like dengue, as their presentation may vary from mild fever to critical life-threatening illness. With the help of prognostic markers, it is possible to identify patients at higher risk and thus improve their outcome with timely intervention. Basic arterial blood gas (ABG) parameters, i.e., potential of hydrogen (pH), partial pressure of oxygen (PO2), partial pressure of carbon dioxide (PCO2) and bicarbonate are useful parameters, especially in critical care medicine as they are known to vary with the severity of illness. Hyperlactatemia is often referred to as a “powerful predictor of mortality”. Basic ABG parameters and lactate have been used as an essential prognostic modality in critically ill patients for decades; however, the evidence remains limited for their role as prognostic markers in patients with severe dengue.

Method

We carried out an observational retrospective cohort study comprising 163 patients with severe dengue, admitted between July 2021 and November 2021 at Medical Intensive Care Unit (MICU) of Shri Ram Murti Smarak Institute of Medical Sciences (SRMS IMS), Bareilly, Uttar Pradesh, India. Basic ABG parameters and lactate levels at the time of admission to MICU were compared between survivor and non-survivor groups of patients with severe dengue in order to evaluate their prognostic utility as predictors of mortality.

Results

pH (p<0.0001), PO2 (p=0.01) and bicarbonate (<0.0001) levels were significantly lower, while PCO2 (p=0.002) and lactate (p<0.0001) levels were significantly higher in non-survivor group as compared to survivor group. Lactate was found to be the best prognostic marker with Area Under the Curve (AUC) of 88.7% on Receiver Operating Characteristics (ROC) analysis.

Conclusion

Basic arterial blood gas parameters and lactate can be used as feasible prognostic markers in patients with severe dengue.

Dynamic Changes of Platelet and Factors Related Dengue Haemorrhagic Fever: A Retrospective Study in Indonesian

Dengue is a viral infection caused by the dengue virus (DENV). Dengue infection is a self-limited acute febrile illness caused by four serotypes of DENV (DENV-1~4). Early recognition of high-risk patients would be helpful to reduce mortality rates and prevent severe dengue. Our study aimed to identify factors related to dengue hemorrhagic fever (DHF) based on admission-day data, and further to understand the distribution of biochemical laboratory data in dengue patients. This retrospective study was conducted in hospitals in Yogyakarta city, Indonesia, and involved febrile patients who were admitted to the hospital with a diagnosis of dengue during 2018 and 2020. Logistic regression models were used to identify variables related to DHF. In this study, 1087 patients were included as suspected dengue patients, among them 468 had dengue fever (DF) and 619 had DHF. Over half of the DHF patients were males (55.9%) with an average age of 17.9 years, and with a secondary infection (71.3%). By a multivariate analysis, on-admission laboratory data of thrombocytopenia and hemoglobin showed significant association with DHF. Furthermore, DHF patients had significantly prolonged hospitalizations compared to DF patients. In conclusion, on-admission platelet counts and hemoglobin laboratory data are useful as predictors of DHF especially for suspected dengue patients with the limitations of diagnostic tests.

An 8-gene machine learning model improves clinical prediction of severe dengue progression

BACKGROUND

Each year 3-6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed.

METHODS

We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were "locked" prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD.

RESULTS

We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2-100) sensitivity and 79.7% (95% CI 75.5-83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7-25.6) and 99.0% (95% CI 97.7-100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3-94.1) sensitivity and 39.7% (95% CI 34.7-44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression.

CONCLUSIONS

The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

Targeting the Annexin A1-FPR2/ALX pathway for host-directed therapy in dengue disease

Host immune responses contribute to dengue's pathogenesis and severity, yet the possibility that failure in endogenous inflammation resolution pathways could characterise the disease has not been contemplated. The pro-resolving protein Annexin A1 (AnxA1) is known to counterbalance overexuberant inflammation and mast cell (MC) activation. We hypothesised that inadequate AnxA1 engagement underlies the cytokine storm and vascular pathologies associated with dengue disease. Levels of AnxA1 were examined in the plasma of dengue patients and infected mice. Immunocompetent, interferon (alpha and beta) receptor one knockout (KO), AnxA1 KO, and formyl peptide receptor 2 (FPR2) KO mice were infected with dengue virus (DENV) and treated with the AnxA1 mimetic peptide Ac_2-26 for analysis. In addition, the effect of Ac_2-26 on DENV-induced MC degranulation was assessed in vitro and in vivo. We observed that circulating levels of AnxA1 were reduced in dengue patients and DENV-infected mice. Whilst the absence of AnxA1 or its receptor FPR2 aggravated illness in infected mice, treatment with AnxA1 agonistic peptide attenuated disease manifestationsatteanuated the symptoms of the disease. Both clinical outcomes were attributed to modulation of DENV-mediated viral load-independent MC degranulation. We have thereby identified that altered levels of the pro-resolving mediator AnxA1 are of pathological relevance in DENV infection, suggesting FPR2/ALX agonists as a therapeutic target for dengue disease.

A Population of CD4+CD8+ Double-Positive T Cells Associated with Risk of Plasma Leakage in Dengue Viral Infection

According to the WHO 2009 classification, dengue with warning signs is at the risk of developing severe form of dengue disease. One of the most important warning signs is plasma leakage, which can be a serious complication associated with higher morbidity and mortality. We report that the frequency of CD4+CD8+ double-positive (DP) T cells is significantly increased in patients at risk of developing plasma leakage. Transcriptomic analysis demonstrated that CD4+CD8+ DP cells were distinct from CD4+ Single Positive (SP) T cells but co-clustered with CD8+ SP cells, indicating a largely similar transcriptional profile. Twenty significant differentially expressed (DE) genes were identified between CD4+CD8+ DP and CD8+ SP cells. These genes encode OX40 and CCR4 proteins as well as other molecules associated with cell signaling on the cell surface (NT5E, MXRA8, and PTPRK). While comparing the profile of gene expression in CD4+CD8+ DP cells from patients with and without warning signs of plasma leakage, similar expression profile was observed, implying a role of CD4+CD8+ DP cells in plasma leakage through a quantitative increase rather than functional alteration. This study provided novel insight into the host immune response during the acute febrile phase of DENV infection and the role of CD4+CD8+ DP T cells in the pathogenesis of plasma leakage.

Successful Outpatient Management of Children at a Secondary Care Hospital in Pakistan in a Dengue Fever Epidemic and Their Clinical Outcomes

Background

There is limited published literature on the feasibility of WHO 2009 guidelines for the management of dengue fever (DF) in Pakistani children. This study aimed to assess the outcome of children with DF who received outpatient treatment according to these guidelines during a DF epidemic.

Method

This was a prospective cohort study conducted at Federal General Hospital, a secondary care hospital, Islamabad, Pakistan, from 1st August to 31st October 2019. Using WHO DF 2009 guidelines, children ≤13 years, diagnosed as confirmed DF (NS1 Ag +), were classified into the outpatient (DF) or the inpatient group (DF with warning signs or severe dengue (SD)). The inpatient group was admitted to the Pakistan Institute of Medical Sciences, a tertiary care hospital, and discharged on recovery. These children were followed for the primary outcome, i.e., recovery or hospitalization by day 14 of enrollment. Additionally, clinical and laboratory features (Hb, HCT, TLC, PLT, and ALT) of the patients in the outpatient who remained stable with those who progressed to inpatient care during follow-up were compared; also, time of recovery of blood counts was assessed.

Results

Of 93 children with DF, 87 (93.5%) received outpatient care at enrollment. Of these, 6 (7.8%) deteriorated by day 7 and were admitted to inpatient care. SD was present in 6/93 (6.4%) patients at presentation and were admitted. All children showed signs of recovery until day 14. Male gender (p=0.049), lower normal mean platelet (p=0.02), and high mean hematocrit (p=0.001) were associated with disease progression.

Conclusion

The majority of children with confirmed DF who received outpatient treatment according to WHO 2009 guidelines were successfully managed. Additionally, confirmed DF with warning signs or SD were admitted and recovered. Regular follow-ups according to the guidelines are pertinent. Thrombocytopenia and high HCT were associated with disease progression.

Clinical predictors of severe dengue: a systematic review and meta-analysis

Background

Severe dengue is a life-threatening complication; rapid identification of these cases, followed by adequate management is crucial to improve the clinical prognosis. Therefore, this study aimed to identify risk factors and predictors of severe dengue.

Methods

A literature search for studies reporting risk factors of severe dengue among individuals with dengue virus infection was conducted in PubMed, Scopus and Web of Science database from inception to December 31, 2020. Pooled odds ratios (ORs) for patients’ demographic characteristics, co-morbidities, and warning signs were estimated using an inverse variance heterogeneity model.

Results

We included 143 articles in the meta-analysis from a total of 13 090 articles retrieved from the literature search. The risk factors of severe dengue were: being a child [OR = 1.96; 95% confidence interval (CI): 1.22–3.13], secondary infection (OR = 3.23; 95% CI: 2.28–4.57), and patients with pre-existing diabetes (OR = 2.88; 95% CI: 1.72–4.81) and renal disease (OR = 4.54; 95% CI: 1.55–13.31). Warning signs strongly associated with severe disease were increased haematocrit with a concurrent decrease in platelet count (OR = 5.13; 95% CI: 1.61–16.34), abdominal pain (OR = 2.00; 95% CI: 1.49–2.68), lethargy (OR = 2.73; 95% CI: 1.05–7.10), vomiting (OR = 1.80; 95% CI: 1.43–2.26), hepatomegaly (OR = 5.92; 95% CI: 3.29–10.66), ascites (OR = 6.30; 95% CI: 3.75–10.60), pleural effusion (OR = 5.72; 95% CI: 3.24–10.10) and melena (OR = 4.05; 95% CI: 1.64–10.00).

Conclusions

Our meta-analysis identified children, secondary infection, diabetes and renal disease(s) as important predictors of severe dengue. Our finding also supports the predictive ability of the WHO warning signs to identify severe dengue. These findings are useful for clinicians to identify severe dengue for management and timely interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-021-00908-2.

Predictive markers for the early prognosis of dengue severity: A systematic review and meta-analysis

BACKGROUND

Predictive markers represent a solution for the proactive management of severe dengue. Despite the low mortality rate resulting from severe cases, dengue requires constant examination and round-the-clock nursing care due to the unpredictable progression of complications, posing a burden on clinical triage and material resources. Accordingly, identifying markers that allow for predicting disease prognosis from the initial diagnosis is needed. Given the improved pathogenesis understanding, myriad candidates have been proposed to be associated with severe dengue progression. Thus, we aim to review the relationship between the available biomarkers and severe dengue.

METHODOLOGY

We performed a systematic review and meta-analysis to compare the differences in host data collected within 72 hours of fever onset amongst the different disease severity levels. We searched nine bibliographic databases without restrictive criteria of language and publication date. We assessed risk of bias and graded robustness of evidence using NHLBI quality assessments and GRADE, respectively. This study protocol is registered in PROSPERO (CRD42018104495).

PRINCIPAL FINDINGS

Of 4000 records found, 40 studies for qualitative synthesis, 19 for meta-analysis. We identified 108 host and viral markers collected within 72 hours of fever onset from 6160 laboratory-confirmed dengue cases, including hematopoietic parameters, biochemical substances, clinical symptoms, immune mediators, viral particles, and host genes. Overall, inconsistent case classifications explained substantial heterogeneity, and meta-analyses lacked statistical power. Still, moderate-certainty evidence indicated significantly lower platelet counts (SMD -0.65, 95% CI -0.97 to -0.32) and higher AST levels (SMD 0.87, 95% CI 0.36 to 1.38) in severe cases when compared to non-severe dengue during this time window.

CONCLUSION

The findings suggest that alterations of platelet count and AST level-in the first 72 hours of fever onset-are independent markers predicting the development of severe dengue.

Different Profiles of Cytokines, Chemokines and Coagulation Mediators Associated with Severity in Brazilian Patients Infected with Dengue Virus

The incidence of dengue in Latin America has increased dramatically during the last decade. Understanding the pathogenic mechanisms in dengue is crucial for the identification of biomarkers for the triage of patients. We aimed to characterize the profile of cytokines (IFN-γ, TNF-α, IL-1β, IL-6, IL-18 and IL-10), chemokines (CXCL8/IL-8, CCL2/MCP-1 and CXCL10/IP-10) and coagulation mediators (Fibrinogen, D-dimer, Tissue factor-TF, Tissue factor pathway inhibitor-TFPI and Thrombomodulin) during the dengue-4 epidemic in Brazil. Laboratory-confirmed dengue cases had higher levels of TNF-α (p < 0.001), IL-6 (p = 0.005), IL-10 (p < 0.001), IL-18 (p = 0.001), CXCL8/IL-8 (p < 0.001), CCL2/MCP-1 (p < 0.001), CXCL10/IP-10 (p = 0.001), fibrinogen (p = 0.037), D-dimer (p = 0.01) and TFPI (p = 0.042) and lower levels of TF (p = 0.042) compared to healthy controls. A principal component analysis (PCA) distinguished between two profiles of mediators of inflammation and coagulation: protective (TNF-α, IL-1β and CXCL8/IL-8) and pathological (IL-6, TF and TFPI). Lastly, multivariate logistic regression analysis identified high aspartate aminotransferase-to-platelet ratio index (APRI) as independent risk factors associated with severity (adjusted OR: 1.33; 95% CI 1.03–1.71; p = 0.027), the area under the receiver operating characteristics curve (AUC) was 0.775 (95% CI 0.681–0.869) and an optimal cutoff value was 1.4 (sensitivity: 76%; specificity: 79%), so it could be a useful marker for the triage of patients attending primary care centers.

Anticipating the future: prognostic tools as a complementary strategy to improve care for patients with febrile illnesses in resource-limited settings

In low-income and middle-income countries, most patients with febrile illnesses present to peripheral levels of the health system where diagnostic capacity is very limited. In these contexts, accurate risk stratification can be particularly impactful, helping to guide allocation of scarce resources to ensure timely and tailored care. However, reporting of prognostic research is often imprecise and few prognostic tests or algorithms are translated into clinical practice.

Here, we review the often-conflated concepts of prognosis and diagnosis, with a focus on patients with febrile illnesses. Drawing on a recent global stakeholder consultation, we apply these concepts to propose three use-cases for prognostic tools in the management of febrile illnesses in resource-limited settings: (1) guiding referrals from the community to higher-level care; (2) informing resource allocation for patients admitted to hospital and (3) identifying patients who may benefit from closer follow-up post-hospital discharge. We explore the practical implications for new technologies and reflect on the challenges and knowledge gaps that must be addressed before this approach could be incorporated into routine care settings.

Our intention is that these use-cases, alongside other recent initiatives, will help to promote a harmonised yet contextualised approach for prognostic research in febrile illness. We argue that this is especially important given the heterogeneous settings in which care is often provided for patients with febrile illnesses living in low-income and middle-income countries.

Predictors of plasma leakage among dengue patients in Thailand: A plasma-leak score analysis

Delayed plasma leakage recognition could lead to improper fluid administration resulting in dengue shock syndrome, subsequently, multi-organ failure, and death. This prospective observational study was conducted in Bangkok, Thailand, between March 2018 and February 2020 to determine predictors of plasma leakage and develop a plasma leakage predictive score among dengue patients aged ≥15 years. Of 667 confirmed dengue patients, 318 (47.7%) developed plasma leakage, and 349 (52.3%) had no plasma leakage. Multivariate analysis showed three independent factors associated with plasma leakage, including body mass index ≥25.0 kg/m2 (odds ratio [OR] = 1.784; 95% confidence interval [CI] = 1.040-3.057; P = 0.035), platelet count <100,000/mm3 on fever days 3 to 4 (OR = 2.151; 95% CI = 1.269-3.647; P = 0.004), and aspartate aminotransferase or alanine aminotransferase ≥100 U/l on fever days 3 to 4 (OR = 2.189; 95% CI = 1.231-3.891; P = 0.008). Because these three parameters had evidence of equality, each independent factor was weighted to give a score of 1 with a total plasma-leak score of 3. Higher scores were associated with increased plasma leakage occurrence, with ORs of 2.017 (95% CI = 1.052-3.869; P = 0.035) for score 1, 6.158 (95% CI = 2.914-13.015; P <0.001) for score 2, and 6.300 (95% CI = 2.419-16.407; P <0.001) for score 3. The area under the receiver operating characteristics curves for predicting plasma leakage was good (0.677 [95% CI = 0.616-0.739]). Patients with a plasma-leak score ≥1 had high sensitivity (88.8%), and those with a plasma-leak score of 3 had high specificity (93.4%) for plasma leakage occurrence. This simple and easily accessible clinical score might help physicians provide early and timely appropriate clinical dengue management in endemic areas.

Diabetes comorbidities in low- and middle-income countries: An umbrella review

Background

Diabetes mellitus, particularly type 2 diabetes, is a major public health burden globally. Diabetes is known to be associated with several comorbidities in high-income countries. However, our understanding of these associations in low- and middle-income countries (LMICs), where the epidemiological transition is leading to a growing dual burden of non-communicable and communicable disease, is less clear. We therefore conducted an umbrella review to systematically identify, appraise and synthesise reviews reporting the association between diabetes and multiple key comorbidities in LMICs.

Methods

We searched Medline, Embase, Global Health, and Global Index Medicus from inception to 14 November 2020 for systematic reviews, with or without meta-analyses, of cohort, case-control or cross-sectional studies investigating the associations between diabetes and cardiovascular disease (CVD), chronic kidney disease (CKD), depression, dengue, pneumonia, and tuberculosis within LMICs. We sought reviews of studies focused on LMICs, but also included reviews with a mixture of high-income and at least two LMIC studies, extracting data from LMIC studies only. We conducted quality assessment of identified reviews using an adapted AMSTAR 2 checklist. Where appropriate, we re-ran meta-analyses to pool LMIC study estimates and conduct subgroup analyses.

Results

From 11 001 articles, we identified 14 systematic reviews on the association between diabetes and CVD, CKD, depression, or tuberculosis. We did not identify any eligible systematic reviews on diabetes and pneumonia or dengue. We included 269 studies from 29 LMICs representing over 3 943 083 participants. Diabetes was positively associated with all comorbidities, with tuberculosis having the most robust evidence (16 of 26 cohort studies identified in total) and depression being the most studied (186 of 269 studies). The majority (81%) of studies included were cross-sectional. Heterogeneity was substantial for almost all secondary meta-analyses conducted, and there were too few studies for many subgroup analyses.

Conclusions

Diabetes has been shown to be associated with several comorbidities in LMICs, but the nature of the associations is uncertain because of the large proportion of cross-sectional study designs. This demonstrates the need to conduct further primary research in LMICs, to improve, and address current gaps in, our understanding of diabetes comorbidities and complications in LMICs.