Our study made two notable findings: the first being description of aspects of severity of a severe dengue cohort; and the second, the rigorous building of a predictive model, which was selected by assessment and comparison of many models, that predicts death early at the recognition of severe dengue.
Our cohort bears some characteristics of Malaysia’s population. The National Health Morbidity Survey 2015 determined that 30.6% of the population were obese and 17.5% were diabetics, figures similar to this study [8].
The fatality rate of this study was 10.1%. Previous studies similar to ours had rates of 3.8% [9] and 18.6% [10] in Brazil. Amâncio et al. [10] non-survivors had median (IQR) AST 151 (43–474) U/L and mean (SD) platelet count 83.3 × 103/μL (76.2 × 103/μL); the other study [9] however, had no similar parameters for comparison. These levels were worse in our study. Other studies, which used ICU admission as the defining criterion of their cohorts, had case fatality rates of 23.1% [11] in Taiwan whilst in India rates were 11.1% [12] and 6.1% [13]. Chen et al. [11] had non-survivors with mean (SD) AST 3444.4 (4191.9) U/L and mean (SD) nadir platelet 3.5 × 103/μL (4.3 × 103/μL). In contrast, the non-survivors of our study had even higher peak AST level, suggesting a more severe cohort in ours.
Our study showed that about a third of patients presented as severe dengue upon admission to hospital whilst the remaining developed severe dengue after admission. Duration of fever onset to severe dengue diagnosis were shorter in those who presented as severe dengue as compared to those who developed severe dengue after admission, median(IQR) 4.38 [2] days vs median(IQR) 5.02(1.78) days, p = 0.003, respectively. Interestingly, there were no difference in mortality and in the duration of fever onset to admission between those who presented as severe dengue as compared to those who developed severe dengue after admission, p = 0.95 vs p = 0.29, respectively.
Guidelines in dengue have repeatedly highlighted that the timing of deterioration is around the time of defervescence and within the critical phase that ensues. It has also been noted that organ impairment follows the same timing. Intriguingly, we found that almost 60% of patients were still febrile at diagnosis of severe dengue; and the proportion of patients who were still febrile at diagnosis of severe dengue was statistically significantly more in those who survived as compared to those who died (Table 2). In fact, those who were febrile at diagnosis of severe dengue were less likely to die as compared to those who had defervesced, OR 0.29 (95% CI: 0.09–0.92, p = 0.03). The importance of timing of development of severe dengue in the course of illness needs to be further explored.
Our findings that nadir platelet occurred about a day after nadir WBC is consistent with a previous study [14]. However, another intriguing finding of our study is that the timing of peak serum creatinine coincided with nadir WBC in those who survived whereas in those who died it coincided with the later nadir platelet.
Based on our cohort, independent predictors of death at the time when the diagnosis of severe dengue was made were: lethargy, bleeding, pulse rate, serum bicarbonate and serum lactate. There have been only 2 studies so far, that examined factors associated with death among severe dengue patients, which used WHO 2009 classification. A study utilising notification database from Brazil [9] of mixed age groups showed age > 55 years (OR 4.98), gastrointestinal bleeding (OR 10.26), haematuria (OR 5.07), and thrombocytopenia (OR 2.55) were factors associated with death. However, exact timings of these parameters were not included. A second study [10] was of severe dengue patients admitted to ICU in Brazil. In this study of 97 patients admitted to ICU, parameters taken within 24 h of ICU admission that were found to be associated with death were: comorbidity of chronic renal disease (OR 15.6), presence of persistent vomiting (OR 4.25), lethargy (OR 3.23), dyspnoea (OR 3.27), elevated WBC, higher serum creatinine and lower serum albumin.
We found that the best prediction model to predict death at the time when the diagnosis of severe dengue was made is a model that incorporated serum bicarbonate and ALT levels taken at that time. This is rather fortuitous for a few reasons. Firstly, both serum bicarbonate and ALT are objective measures as opposed to subjective warning signs such as lethargy and bleeding which have inherent variability in establishing their presence and severity. Secondly, both are currently accessible laboratory tests.
A recent study on serum lactate in dengue [15] found that this biomarker is a good predictor of severe dengue (AUROC for peripheral venous lactate at admission was 0.84 [95% CI: 0.72–0.97]). In perspective, our study revealed that in predicting death, lactate-incorporated models had lower AUROCs as compared to those of bicarbonate-based models (Table 4). Additionally, we showed that nadir serum bicarbonate occurred earlier than highest serum lactate level (Table 2) in patients with severe dengue. In fact, at diagnosis of severe dengue, more patients had abnormal serum bicarbonate than abnormal serum lactate (46.7% vs 27.6%, respectively). These are important aspects to consider in clinical practice as earlier management will be more advantageous. Therefore, whilst lactate could be an additional alternative criterion to establish the diagnosis of severe dengue, our study suggests that lactate alone is not sufficient in prognostication of patients with severe dengue.
Unexpectedly, serum creatinine was not found to be an independent predictor of death by multivariate analysis. However, its incorporation into our models led to good AUROC performances.
Under the assumption that the time of recognition of severe dengue is approximately the actual time of development of severe dengue, we believe that prognosticating mortality in patients with severe dengue at the time of its recognition provides a sensible approach. We postulate that at this time, underlying pathophysiological processes which determine outcome would most likely have reach significance. Prognosticating prematurely before this moment may have little specificity, as the ultimate outcome determining processes may yet to occur. Prognosticating too late however is obviously futile. With our model management decisions may be better informed in terms of resource allocation, especially in conditions of high volume care. It has to be noted however that the underlying outcome determining pathophysiology has yet to be clearly elucidated. Further investigation into the kinetics of biochemistry with respect to timing of events in dengue, in particular the time of development of severe dengue, is needed and may perhaps fill this gap.
The main limitation of our study was the retrospective design. However, data accuracy was reasonable as management of patients followed standard management guidelines for dengue which have clear specifications of timing of blood investigations. Though only a single centre study, we believe the sample size was adequate as illustrated by the results of our findings. Finally, though we have rigorously built a predictive model and took steps to address overfitting, the actual performance of any model will vary according to the population it is applied on. As we have mentioned, our cohort is different from similar studies, hence our model will require population specific external validation and assessment.