Overdiagnosis of malaria in patients with severe febrile illness in Tanzania: a prospective study
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《英国医生杂志》
1 London School of Hygiene and Tropical Medicine, London WCIE 7HT, 2 Kilimanjaro Christian Medical Centre, Moshi, Tanzania, 3 National Institute of Medical Research, Dar es Salaam, Tanzania, 4 Mawenzi Hospital, Moshi, Kilimanjaro, Tanzania
Correspondence to: H Reyburn hugh.reyburn@lshtm.ac.uk
Abstract
In the year 2000 about 42% of hospital diagnoses and 32% of hospital deaths in Tanzania were attributed to malaria,1 a figure typical for countries in Africa where malaria is endemic.2 Despite this striking statistic, little is known about the accuracy of hospital diagnosis or the appropriateness of treatment. A recent study from Tanzania found that of 75 adults diagnosed and treated for cerebral malaria in a teaching hospital only two met World Health Organization criteria for the diagnosis,3 and two studies of district hospitals in Africa identified several problems with the organisation and planning of care.4 5
Given the high proportion of admissions attributed to malaria, overdiagnosis of malaria and consequent neglect of alternative diagnoses could lead to avoidable morbidity and mortality. In addition, overdiagnosis burdens health services with costs they can ill afford.6 Unreliable hospital data hamper health service planning and make progress towards targets such as those set by the Roll Back Malaria initiative impossible to assess. The spread of drug resistance means that there is a need to move to considerably more expensive drugs, but if a large proportion of the people treated for malaria do not have the disease this will substantially increase the costs of change.
Accuracy of hospital diagnosis of malaria is likely to depend on the epidemiological probability of the disease (defined by intensity of malaria transmission and age of patients) and is important as most of the population of sub-Saharan Africa live in areas of low or moderate malaria transmission.7 We prospectively examined the diagnosis and outcome in all patients admitted and treated for severe or potentially complicated malaria during one year in 10 hospitals serving people for areas with various transmission intensities. A clinician's decision to admit a patient for treatment of malaria defined those eligible for inclusion in the study.
Methods
A total of 17 313 cases were recruited into the study over one year (fig 1). Of these, 12 643 patients had a diagnosis of malaria but did not have any study criteria for severe disease, of whom 120 (1.0%) died.
Fig 1 Patients admitted to 10 hospitals with diagnosis of malaria over one year by outcome, presence of any P falciparum asexual parasites on the research blood slide, and case fatality
In total 4670 patients had at least one of the study criteria for severe disease and were admitted to hospital and treated for malaria, in 95% of cases with quinine. Of these patients, 196 (4.2%) had a missing or unreadable blood slide. Among the 4474 remaining patients, 2062 (46.1%) had a positive blood slide as determined by the presence of P falciparum asexual parasites on the research slide (slide positive). Most adults at every altitude band and most children under 5 years living above 600 metres had a negative slide (table 1). The proportion of patients with positive slides decreased systematically with increasing age and with increasing altitude of residence (fig 2).
Table 1 Patients admitted to hospital with diagnosis of malaria with at least one study criterion of severe disease by research blood slide result, age, and altitude (meters) of residence
Fig 2 Percentage of patients with at least one study criterion of severe disease who had a positive research blood slide for any P falciparum asexual parasites by age and altitude of residence
When we used logistic regression, controlled for clustering within hospitals and adjusted for differential sampling at one hospital, the odds of a positive slide decreased by 10% (odds ratio 0.90, 95% confidence interval 0.86 to 0.94, P < 0.001) with each 100 metre increase in altitude. Age had a significant effect in the model (P < 0.001). Compared with children under the age of 2 years, the odds of a positive slide was higher among 2-4 year olds (1.35, 0.96 to 1.89) and then declined with age to 0.74 (0.39 to 1.40) at 5-15 years and 0.24 (0.10 to 0.59) at over 15 years. Adjustment for the reported use of antimalarial drugs in the 48 hours before admission and rainy season did not alter the effect of age and altitude and neither factor had a significant association with slide result. There was no significant difference in distribution of the three main categories of severe disease (severe anaemia, respiratory distress, and altered consciousness) between slide positive and slide negative patients stratified by age group, except that in children under the age of 5 years severe anaemia was more common among slide positive patients (P < 0.001) and respiratory distress was more common among slide negative patients (P = 0.027) (table 2).
Table 2 Prevalence of selected clinical features by research blood slide result and age
The unadjusted odds of dying among slide negative patients was higher than among those who were slide positive (1.85, 1.37 to 2.49, P < 0.001), an effect observed across all age groups (table 3). Table 4 shows the odds ratios from a logistic regression model for mortality after adjustment for clustering within hospitals. Respiratory distress, severe anaemia, altered consciousness, age, and altitude of residence were all significantly associated with case fatality. After we controlled for these variables, those who were slide negative still had increased odds of dying but the difference was of borderline significance (1.55, 0.94 to 2.53, P = 0.08). After adjustment for the effect of the slide result, respiratory distress and altered consciousness were associated with the largest increase in the odds of a fatal outcome. Mortality increased with age and decreased with increasing altitude.
Table 3 Case fatality by research blood slide result and age among cases with at least one study criterion of severe disease
Table 4 Logistic regression model* of predictors of mortality among cases with at least one study criterion of severe disease
In 683/4474 (15%) patients there were discrepancies in the reading of the research slides between the first and second research microscopists. These slides were read again by a third microscopist. When we used the definitive agreed result as the reference, only 2949/4451 hospital slides were correct (66% agreement, = 0.33, P < 0.0001), with 988 false positive (39% of positives) and 514 false negative (27% of negatives). This equates to a sensitivity, specificity, and positive predictive value of hospital slides in this group of 75%, 59%, and 61%, respectively.
Of 2375 patients who were slide negative by research results, 1571(66.1%) were not treated with antibiotics in addition to the antimalarial drug. The research slide was not immediately available to clinicians as it was read later but the hospital slide result was available to clinical staff at the time of diagnosis. Patients with negative hospital slides were more likely to have received antibiotics (661/1897, 34.8%) compared with those with positives slides (500/2499, 20.0%) (2 = 122.1, 2 df, P < 0.001). Among patients with negative hospital slides, those who died were more likely to have received antibiotics than those who survived (2 = 13.5, 2 df, P < 0.001) (table 5).
Table 5 Number (%) of all cases and fatal cases treated with any antibiotic during hospital admission, according to hospital blood slide result and research blood slide result
Discussion
Ministry of Health. Health statistics abstract 2002. Burden of disease and health utilization statistics. Vol 1. Dar Es Salaam, Tanzania: Ministry of Health, 2002: 3-3.
World Health Organization. The Africa malaria report. Geneva: WHO, 2003: 1093. (WHO/CDS/MAL/2003.)
Makani J, Matuja W, Liyombo E, Snow RW, Marsh K, Warrell DA. Admission diagnosis of cerebral malaria in adults in an endemic area of Tanzania: implications and clinical description. QJM 2003;96: 355-62.
English M, Esamai F, Wasunna A, Were F, Ogutu B, Wamae A, et al. Assessment of inpatient paediatric care in first referral level hospitals in 13 districts in Kenya. Lancet 2004;363: 1948-53.
Nolan T, Angos P, Cunha AJ, Muhe L, Qazi S, Simoes EA, et al. Quality of hospital care for seriously ill children in less-developed countries. Lancet 2001;357: 106-10.
Jonkman A, Chibwe RA, Khoromana CO, Liabunya UL, Chapanda ME, Kandiero GE, et al. Cost-saving through microscopy-based versus presumptive diagnosis of malaria in adult outpatients in Malawi. Bull World Health Organ 1995;73: 223-7.
Snow RW, Craig M, Deichmann U, Marsh K. Estimating mortality, morbidity and disability due to malaria among Africa's non-pregnant population. Bull World Health Organ 1999;77: 624-40.
Bodker R, Akida J, Shayo D, Kisinza W, Msangeni HA, Pedersen EM, et al. Relationship between altitude and intensity of malaria transmission in the Usambara Mountains, Tanzania. J Med Entomol 2003;40: 706-17.
WHO. Severe falciparum malaria. Trans R Soc Trop Med Hyg 2000;94: 1-2.
Molyneux ME, Taylor TE, Wirima JJ, Borgstein A. Clinical features and prognostic indicators in paediatric cerebral malaria: a study of 131 comatose Malawian children. Q J Med 1989;71: 441-59.
WHO. Inegrated management of childhood illness. www.who.int/child-adolescenthealth/publications/IMCI/WHO_FCH_CAH_00.40.htm (accessed 7 Oct 2004).
Bryce J, el Arifeen S, Pariyo G, Lanata C, Gwatkin D, Habicht JP. Reducing child mortality: can public health deliver? Lancet 2003;362: 159-64.
World Health Organization. Africa malaria report 2003. Geneva: WHO, 2003. (WHO/CDS/MAL/2003.1093 ed.)
Bodker R. Variations in malaria risk in the Usambara Mountains, Tanzania. Charlottenlund, Denmark: Danish Bilharzia Laboratory, 2000: 56-84.
Planche T, Agbenyega T, Bedu-Addo G, Ansong D, Owusu-Ofori A, Micah F, et al. A prospective comparison of malaria with other severe diseases in African children: prognosis and optimization of management. Clin Infect Dis 2003;37: 890-7.
Marsh K, Forster D, Waruiru C, Mwangi I, Winstanley M, Marsh V, et al. Indicators of life-threatening malaria in African children. N Engl J Med 1995;332: 1399-404.
Schellenberg D, Menendez C, Kahigwa E, Font F, Galindo C, Acosta C, et al. African children with malaria in an area of intense Plasmodium falciparum transmission: features on admission to the hospital and risk factors for death. Am J Trop Med Hyg 1999;61: 431-8.
Smith T, Schellenberg JA, Hayes R. Attributable fraction estimates and case definitions for malaria in endemic areas. Stat Med 1994;13: 2345-58.
Mundy C, Ngwira M, Kadewele G, Bates I, Squire SB, Gilks CF. Evaluation of microscope condition in Malawi. Trans R Soc Trop Med Hyg 2000;94: 583-4.
WHO. Management of the child with severe infection or severe malnutrition. Geneva: WHO, 2000
English M, Berkley J, Mwangi I, Mohammed S, Ahmed M, Osire F, et al. Hypothetical performance of syndrome-based management of acute paediatric admissions of children aged more than 60 days in a Kenyan district hospital. Bull World Health Organ 2003;81: 166-73.(Hugh Reyburn, clinical se)
Correspondence to: H Reyburn hugh.reyburn@lshtm.ac.uk
Abstract
In the year 2000 about 42% of hospital diagnoses and 32% of hospital deaths in Tanzania were attributed to malaria,1 a figure typical for countries in Africa where malaria is endemic.2 Despite this striking statistic, little is known about the accuracy of hospital diagnosis or the appropriateness of treatment. A recent study from Tanzania found that of 75 adults diagnosed and treated for cerebral malaria in a teaching hospital only two met World Health Organization criteria for the diagnosis,3 and two studies of district hospitals in Africa identified several problems with the organisation and planning of care.4 5
Given the high proportion of admissions attributed to malaria, overdiagnosis of malaria and consequent neglect of alternative diagnoses could lead to avoidable morbidity and mortality. In addition, overdiagnosis burdens health services with costs they can ill afford.6 Unreliable hospital data hamper health service planning and make progress towards targets such as those set by the Roll Back Malaria initiative impossible to assess. The spread of drug resistance means that there is a need to move to considerably more expensive drugs, but if a large proportion of the people treated for malaria do not have the disease this will substantially increase the costs of change.
Accuracy of hospital diagnosis of malaria is likely to depend on the epidemiological probability of the disease (defined by intensity of malaria transmission and age of patients) and is important as most of the population of sub-Saharan Africa live in areas of low or moderate malaria transmission.7 We prospectively examined the diagnosis and outcome in all patients admitted and treated for severe or potentially complicated malaria during one year in 10 hospitals serving people for areas with various transmission intensities. A clinician's decision to admit a patient for treatment of malaria defined those eligible for inclusion in the study.
Methods
A total of 17 313 cases were recruited into the study over one year (fig 1). Of these, 12 643 patients had a diagnosis of malaria but did not have any study criteria for severe disease, of whom 120 (1.0%) died.
Fig 1 Patients admitted to 10 hospitals with diagnosis of malaria over one year by outcome, presence of any P falciparum asexual parasites on the research blood slide, and case fatality
In total 4670 patients had at least one of the study criteria for severe disease and were admitted to hospital and treated for malaria, in 95% of cases with quinine. Of these patients, 196 (4.2%) had a missing or unreadable blood slide. Among the 4474 remaining patients, 2062 (46.1%) had a positive blood slide as determined by the presence of P falciparum asexual parasites on the research slide (slide positive). Most adults at every altitude band and most children under 5 years living above 600 metres had a negative slide (table 1). The proportion of patients with positive slides decreased systematically with increasing age and with increasing altitude of residence (fig 2).
Table 1 Patients admitted to hospital with diagnosis of malaria with at least one study criterion of severe disease by research blood slide result, age, and altitude (meters) of residence
Fig 2 Percentage of patients with at least one study criterion of severe disease who had a positive research blood slide for any P falciparum asexual parasites by age and altitude of residence
When we used logistic regression, controlled for clustering within hospitals and adjusted for differential sampling at one hospital, the odds of a positive slide decreased by 10% (odds ratio 0.90, 95% confidence interval 0.86 to 0.94, P < 0.001) with each 100 metre increase in altitude. Age had a significant effect in the model (P < 0.001). Compared with children under the age of 2 years, the odds of a positive slide was higher among 2-4 year olds (1.35, 0.96 to 1.89) and then declined with age to 0.74 (0.39 to 1.40) at 5-15 years and 0.24 (0.10 to 0.59) at over 15 years. Adjustment for the reported use of antimalarial drugs in the 48 hours before admission and rainy season did not alter the effect of age and altitude and neither factor had a significant association with slide result. There was no significant difference in distribution of the three main categories of severe disease (severe anaemia, respiratory distress, and altered consciousness) between slide positive and slide negative patients stratified by age group, except that in children under the age of 5 years severe anaemia was more common among slide positive patients (P < 0.001) and respiratory distress was more common among slide negative patients (P = 0.027) (table 2).
Table 2 Prevalence of selected clinical features by research blood slide result and age
The unadjusted odds of dying among slide negative patients was higher than among those who were slide positive (1.85, 1.37 to 2.49, P < 0.001), an effect observed across all age groups (table 3). Table 4 shows the odds ratios from a logistic regression model for mortality after adjustment for clustering within hospitals. Respiratory distress, severe anaemia, altered consciousness, age, and altitude of residence were all significantly associated with case fatality. After we controlled for these variables, those who were slide negative still had increased odds of dying but the difference was of borderline significance (1.55, 0.94 to 2.53, P = 0.08). After adjustment for the effect of the slide result, respiratory distress and altered consciousness were associated with the largest increase in the odds of a fatal outcome. Mortality increased with age and decreased with increasing altitude.
Table 3 Case fatality by research blood slide result and age among cases with at least one study criterion of severe disease
Table 4 Logistic regression model* of predictors of mortality among cases with at least one study criterion of severe disease
In 683/4474 (15%) patients there were discrepancies in the reading of the research slides between the first and second research microscopists. These slides were read again by a third microscopist. When we used the definitive agreed result as the reference, only 2949/4451 hospital slides were correct (66% agreement, = 0.33, P < 0.0001), with 988 false positive (39% of positives) and 514 false negative (27% of negatives). This equates to a sensitivity, specificity, and positive predictive value of hospital slides in this group of 75%, 59%, and 61%, respectively.
Of 2375 patients who were slide negative by research results, 1571(66.1%) were not treated with antibiotics in addition to the antimalarial drug. The research slide was not immediately available to clinicians as it was read later but the hospital slide result was available to clinical staff at the time of diagnosis. Patients with negative hospital slides were more likely to have received antibiotics (661/1897, 34.8%) compared with those with positives slides (500/2499, 20.0%) (2 = 122.1, 2 df, P < 0.001). Among patients with negative hospital slides, those who died were more likely to have received antibiotics than those who survived (2 = 13.5, 2 df, P < 0.001) (table 5).
Table 5 Number (%) of all cases and fatal cases treated with any antibiotic during hospital admission, according to hospital blood slide result and research blood slide result
Discussion
Ministry of Health. Health statistics abstract 2002. Burden of disease and health utilization statistics. Vol 1. Dar Es Salaam, Tanzania: Ministry of Health, 2002: 3-3.
World Health Organization. The Africa malaria report. Geneva: WHO, 2003: 1093. (WHO/CDS/MAL/2003.)
Makani J, Matuja W, Liyombo E, Snow RW, Marsh K, Warrell DA. Admission diagnosis of cerebral malaria in adults in an endemic area of Tanzania: implications and clinical description. QJM 2003;96: 355-62.
English M, Esamai F, Wasunna A, Were F, Ogutu B, Wamae A, et al. Assessment of inpatient paediatric care in first referral level hospitals in 13 districts in Kenya. Lancet 2004;363: 1948-53.
Nolan T, Angos P, Cunha AJ, Muhe L, Qazi S, Simoes EA, et al. Quality of hospital care for seriously ill children in less-developed countries. Lancet 2001;357: 106-10.
Jonkman A, Chibwe RA, Khoromana CO, Liabunya UL, Chapanda ME, Kandiero GE, et al. Cost-saving through microscopy-based versus presumptive diagnosis of malaria in adult outpatients in Malawi. Bull World Health Organ 1995;73: 223-7.
Snow RW, Craig M, Deichmann U, Marsh K. Estimating mortality, morbidity and disability due to malaria among Africa's non-pregnant population. Bull World Health Organ 1999;77: 624-40.
Bodker R, Akida J, Shayo D, Kisinza W, Msangeni HA, Pedersen EM, et al. Relationship between altitude and intensity of malaria transmission in the Usambara Mountains, Tanzania. J Med Entomol 2003;40: 706-17.
WHO. Severe falciparum malaria. Trans R Soc Trop Med Hyg 2000;94: 1-2.
Molyneux ME, Taylor TE, Wirima JJ, Borgstein A. Clinical features and prognostic indicators in paediatric cerebral malaria: a study of 131 comatose Malawian children. Q J Med 1989;71: 441-59.
WHO. Inegrated management of childhood illness. www.who.int/child-adolescenthealth/publications/IMCI/WHO_FCH_CAH_00.40.htm (accessed 7 Oct 2004).
Bryce J, el Arifeen S, Pariyo G, Lanata C, Gwatkin D, Habicht JP. Reducing child mortality: can public health deliver? Lancet 2003;362: 159-64.
World Health Organization. Africa malaria report 2003. Geneva: WHO, 2003. (WHO/CDS/MAL/2003.1093 ed.)
Bodker R. Variations in malaria risk in the Usambara Mountains, Tanzania. Charlottenlund, Denmark: Danish Bilharzia Laboratory, 2000: 56-84.
Planche T, Agbenyega T, Bedu-Addo G, Ansong D, Owusu-Ofori A, Micah F, et al. A prospective comparison of malaria with other severe diseases in African children: prognosis and optimization of management. Clin Infect Dis 2003;37: 890-7.
Marsh K, Forster D, Waruiru C, Mwangi I, Winstanley M, Marsh V, et al. Indicators of life-threatening malaria in African children. N Engl J Med 1995;332: 1399-404.
Schellenberg D, Menendez C, Kahigwa E, Font F, Galindo C, Acosta C, et al. African children with malaria in an area of intense Plasmodium falciparum transmission: features on admission to the hospital and risk factors for death. Am J Trop Med Hyg 1999;61: 431-8.
Smith T, Schellenberg JA, Hayes R. Attributable fraction estimates and case definitions for malaria in endemic areas. Stat Med 1994;13: 2345-58.
Mundy C, Ngwira M, Kadewele G, Bates I, Squire SB, Gilks CF. Evaluation of microscope condition in Malawi. Trans R Soc Trop Med Hyg 2000;94: 583-4.
WHO. Management of the child with severe infection or severe malnutrition. Geneva: WHO, 2000
English M, Berkley J, Mwangi I, Mohammed S, Ahmed M, Osire F, et al. Hypothetical performance of syndrome-based management of acute paediatric admissions of children aged more than 60 days in a Kenyan district hospital. Bull World Health Organ 2003;81: 166-73.(Hugh Reyburn, clinical se)