Usefulness of clinical algorithm as screening process to detected malaria in low-to-moderate transmission areas of scarce health related resources

Abstract

Introduction-In areas of low-to-moderate risk of malaria transmission, the World Health Organization recommends parasitic confirmation before treatment. Such areas have usually low budget for health care and malaria diagnosis is mostly based on clinical assumption. Algorithms have been developed to improve health care providers' identification of clinical malaria and could be used as screening to reduce the number of individuals requiring parasitic confirmation before treating.Methods-Prospective clinical and parasitological data were collected from inhabitants of four villages from March 1984 through March 1985. Symptoms and signs recorded by physicians were used in multivariate models to test the best predictors of malaria. Sensitivity and specificity were calculated for various cut-offs of scores and compared to clinical diagnosis.Results-A total of 8.941 individuals were evaluated during the 1-year period of data collection. The overall prevalence of malaria parasitemia was 19.7% (n = 1762). Of the 4280 people evaluated during the high season period, 24% (n = 1024) presented any parasitemia, 55.3% (566/1024) due to Plasmodium falciparum. The final clinical algorithm included history of fever, rigors, headache, absence of myalgia, backache or cough, nausea or vomiting, and splenomegaly on examination as predictable variables. At a cut-off score of 2.0, the sensitivity of the algorithm was higher for the entire sample (57% vs. 43%), for high season period (70% vs. 53%), for children less than 6 years of age (59% vs. 40%), for individuals with parasitemia due to P. falciparum (65% vs. 48%), and for high P. falciparum parasitemic individuals at high season (84% vs. 68%). However, specificity was usually lower unless a higher cut off was used, in which case the gain in sensitivity by using the algorithm was reduced.Conclusion-In low-to-moderate transmission areas in which health related resources are scarce, a clinical algorithm increases the identification of real cases of malaria and could be used as screening for further parasitic identification.

Efficacy and Safety of Artemether-Lumefantrine in the Treatment of Acute, Uncomplicated Plasmodium falciparum Malaria: A Pooled Analysis

“…These results are consistent with those of other studies that demonstrated excellent safety and tolerability of AL 11,28,53,54. Most of the frequently reported adverse events were typical signs and symptoms of malaria 55. There were few serious adverse events or deaths, and serious adverse events were only rarely suspected to be related to AL therapy.…”

Patient-, health worker-, and health facility-level determinants of correct malaria case management at publicly funded health facilities in Malawi: results from a nationally representative health facility survey

“…Even with systematic elicitation of symptoms, purely clinical diagnostic algorithms for malaria generally do not perform well [ 10 , 24 ]. In addition to general non-specificity and overlap with multiple other potential causes, the symptoms of malaria have significant overlap with pneumonia symptoms in children [ 25 , 26 ] and other febrile illnesses in all ages.…”

Challenges in the Determination of Early Predictors of Cerebral Malaria: Lessons from the Human Disease and the Experimental Murine Models

“…In practice, the clinical diagnosis of CM, severe malaria and even malaria infection in endemic areas is difficult [51][52][53] . A study in Tanzania showed that 54% of people treated for severe malaria had no parasitemia [53] , revealing a high sensitivity and low specificity for the definition of 'severe malaria'.…”

“…One way of improving the clinical diagnosis of CM is to rationalize the diagnosis process by constructing clinical algorithms. It has previously been shown that this approach can increase the accuracy of the diagnosis of malaria [52,61,[84][85][86][87][88][89][90][91][92] , and of anemia in a malariaendemic area [93] . Tangpukdee et al [94] proposed a score to estimate the risk of uncomplicated P. falciparum infection to develop into a severe form of malaria using the same approach.…”