HIV Infection and Excess Risk of Clinical Fractures
HIV Infection and Excess Risk of Clinical Fractures
The extensive nature of registers in Denmark covering contacts to the health sector offers good possibilities for studies on the occurrence of fractures. Using the unique 10-digit civil registry number that is assigned to all Danish citizens shortly after birth, a complete hospital discharge and prescription history can be established for each individual and valid linkage between population-based registries can be obtained. The unique civil registry number is used in all registers, that is, if a person buys a drug on prescription, the drug is registered as bought by this individual and the same applies for admissions to hospitals and contacts to general practitioners for reimbursement purposes. Because of the extensive nature of the registers, only a few values were missing for socioeconomic status, such as civil status, working status, and income.
This case–control study was performed within the Danish population that constituted approximately 5.3 million individuals during the study period.
The study was subject to control by the National Board of Health and the Danish Data Protection Agency.
This study was designed as a classical case–control study. Cases were all subjects, both genders and all ages, who sustained a fracture during the year 2000. Controls were matched subjects without a fracture in the same year using the criteria below. Exposure was use of drugs and diseases before the date of fracture or a matched index date in the controls. Information on fractures and diseases before the fracture was based on hospital records of in- and outpatients.
In Denmark, The National Hospital Discharge Register covers all contacts (on in- or outpatient basis) to the hospitals. The register was founded in 1977, but outpatient records were first completely incorporated from 1995. The files of The National Hospital Discharge Register include information on the civil registry number of the patient, date of discharge, and discharge diagnoses, assigned exclusively by the physician at discharge according to the Danish version of the International Classification of Diseases, eighth revision (ICD-8) until the end of 1993, and to the Danish version of the ICD, 10th revision (ICD-10). The register has nationwide coverage of public hospitals with an almost 100% completeness of recordings and a high precision of diagnoses, particularly for fracture diagnoses. Using The National Hospital Discharge Register, we identified all subjects, who had sustained a fracture between January 1, 2000, and December 31, 2000 (n = 124,655). The following end points were assessed: any clinical fracture, hip fracture (neck and pertrochanteric), distal forearm fracture, clinical spine fracture, and/or any nontraumatic fracture (any fracture not presenting with an accident mechanism code signaling a trauma of more than a fall at the same level or less as fracture energy). Based on accident codes and admission codes (eg, hospitalized from home), incident fractures were identified and separated from readmissions.
Using the Civil Registration System, which has electronic records on all changes in vital status, including change of address and date of death for the entire Danish population since 1968, we randomly selected up to 3 controls for each case, matched by gender, year of birth, and region. The controls were selected using the incidence density sampling technique.
Patients with a diagnosis of AIDS/HIV according to ICD-8 code 07983 and ICD-10: B20, B21, B22, B23, and B24, were identified from the National Hospital Discharge Register. Date of HIV clinical diagnosis was accounted for in time-varying models.
Using The National Hospital Discharge Register, we gathered information on the number of days spent in hospital the year preceding fracture (year 1999) and history of a fracture in the period 1977–2000. Similarly, data from the National Bureau of Statistics were obtained for a more accurate patient characterization, including income, social status, working status, and educational status in 1999. The National Health Organization Register information was then used to study number of contacts to general practitioners and practicing specialists for the period 1996–2000.
Information on alcoholism was collected as appearance of a diagnosis of alcoholism in the National Hospital Discharge Register or in the Psychiatric Central Register or a prescription of disulfiram in the Prescriptions database. Data on use of drugs with a potential effect on bone metabolism and/or fracture risk (corticosteroids, sedatives, opioids, antidepressants, anticonvulsants, and antipsychotics) were gathered from the Prescriptions database.
Data from different registers were merged at the National Bureau of Statistics, and for each subject, the 10-digit civil registry number was substituted by a unique anonymous ID.
The analyses of the association between HIV status and fractures in the year 2000 (cases versus controls) were carried out using crude and multivariable conditional logistic regression. The latter were adjusted for the following a priori–defined potential confounders: previous fracture, alcoholism, annual income in the previous year, use of corticosteroids, and sedatives. Furthermore, this logistic model for any fracture was adjusted for use of an a priori–defined list of drugs potentially involved in the causal pathway: opioids, antidepressants, anticonvulsants, and antipsychotics.
In addition, separate analyses for hip, forearm, and spine fracture cases and matched controls were also performed using these same methods. Stratified analyses for age strata (young age <40 years, middle age 40–60, and elderly >60 years) and gender were carried out, and potential interactions with these were tested for introducing multiplicative terms into the logistic model.
Finally, we studied the effect of time from HIV diagnosis on any fracture risk using a categorical variable for HIV-infected patients (up to 2 years, 2.1–4 years, 4.1–6 years, 6.1–7.5 years, and beyond 7.5 years) and fitted a smooth spline plot for visualization of this effect.
All these analyses were performed using STATA 12.0 (STATA Corp, College Station, Tex) and SPSS 19.0 (SPSS Inc, Chicago, Ill). SPSS was used to generate the datasets from raw data and check the completeness of data, whereas STATA was used for the actual statistical analyses.
No informed consent was required for this study, as we used exclusively routinely collected data.
Methods
Setting and Source of Data
The extensive nature of registers in Denmark covering contacts to the health sector offers good possibilities for studies on the occurrence of fractures. Using the unique 10-digit civil registry number that is assigned to all Danish citizens shortly after birth, a complete hospital discharge and prescription history can be established for each individual and valid linkage between population-based registries can be obtained. The unique civil registry number is used in all registers, that is, if a person buys a drug on prescription, the drug is registered as bought by this individual and the same applies for admissions to hospitals and contacts to general practitioners for reimbursement purposes. Because of the extensive nature of the registers, only a few values were missing for socioeconomic status, such as civil status, working status, and income.
This case–control study was performed within the Danish population that constituted approximately 5.3 million individuals during the study period.
The study was subject to control by the National Board of Health and the Danish Data Protection Agency.
Study Design
This study was designed as a classical case–control study. Cases were all subjects, both genders and all ages, who sustained a fracture during the year 2000. Controls were matched subjects without a fracture in the same year using the criteria below. Exposure was use of drugs and diseases before the date of fracture or a matched index date in the controls. Information on fractures and diseases before the fracture was based on hospital records of in- and outpatients.
Identification of Fracture Cases
In Denmark, The National Hospital Discharge Register covers all contacts (on in- or outpatient basis) to the hospitals. The register was founded in 1977, but outpatient records were first completely incorporated from 1995. The files of The National Hospital Discharge Register include information on the civil registry number of the patient, date of discharge, and discharge diagnoses, assigned exclusively by the physician at discharge according to the Danish version of the International Classification of Diseases, eighth revision (ICD-8) until the end of 1993, and to the Danish version of the ICD, 10th revision (ICD-10). The register has nationwide coverage of public hospitals with an almost 100% completeness of recordings and a high precision of diagnoses, particularly for fracture diagnoses. Using The National Hospital Discharge Register, we identified all subjects, who had sustained a fracture between January 1, 2000, and December 31, 2000 (n = 124,655). The following end points were assessed: any clinical fracture, hip fracture (neck and pertrochanteric), distal forearm fracture, clinical spine fracture, and/or any nontraumatic fracture (any fracture not presenting with an accident mechanism code signaling a trauma of more than a fall at the same level or less as fracture energy). Based on accident codes and admission codes (eg, hospitalized from home), incident fractures were identified and separated from readmissions.
Selection of Population-Based Controls
Using the Civil Registration System, which has electronic records on all changes in vital status, including change of address and date of death for the entire Danish population since 1968, we randomly selected up to 3 controls for each case, matched by gender, year of birth, and region. The controls were selected using the incidence density sampling technique.
Data on HIV Infection
Patients with a diagnosis of AIDS/HIV according to ICD-8 code 07983 and ICD-10: B20, B21, B22, B23, and B24, were identified from the National Hospital Discharge Register. Date of HIV clinical diagnosis was accounted for in time-varying models.
Potential Confounders
Using The National Hospital Discharge Register, we gathered information on the number of days spent in hospital the year preceding fracture (year 1999) and history of a fracture in the period 1977–2000. Similarly, data from the National Bureau of Statistics were obtained for a more accurate patient characterization, including income, social status, working status, and educational status in 1999. The National Health Organization Register information was then used to study number of contacts to general practitioners and practicing specialists for the period 1996–2000.
Information on alcoholism was collected as appearance of a diagnosis of alcoholism in the National Hospital Discharge Register or in the Psychiatric Central Register or a prescription of disulfiram in the Prescriptions database. Data on use of drugs with a potential effect on bone metabolism and/or fracture risk (corticosteroids, sedatives, opioids, antidepressants, anticonvulsants, and antipsychotics) were gathered from the Prescriptions database.
Statistical Analyses
Data from different registers were merged at the National Bureau of Statistics, and for each subject, the 10-digit civil registry number was substituted by a unique anonymous ID.
The analyses of the association between HIV status and fractures in the year 2000 (cases versus controls) were carried out using crude and multivariable conditional logistic regression. The latter were adjusted for the following a priori–defined potential confounders: previous fracture, alcoholism, annual income in the previous year, use of corticosteroids, and sedatives. Furthermore, this logistic model for any fracture was adjusted for use of an a priori–defined list of drugs potentially involved in the causal pathway: opioids, antidepressants, anticonvulsants, and antipsychotics.
In addition, separate analyses for hip, forearm, and spine fracture cases and matched controls were also performed using these same methods. Stratified analyses for age strata (young age <40 years, middle age 40–60, and elderly >60 years) and gender were carried out, and potential interactions with these were tested for introducing multiplicative terms into the logistic model.
Finally, we studied the effect of time from HIV diagnosis on any fracture risk using a categorical variable for HIV-infected patients (up to 2 years, 2.1–4 years, 4.1–6 years, 6.1–7.5 years, and beyond 7.5 years) and fitted a smooth spline plot for visualization of this effect.
All these analyses were performed using STATA 12.0 (STATA Corp, College Station, Tex) and SPSS 19.0 (SPSS Inc, Chicago, Ill). SPSS was used to generate the datasets from raw data and check the completeness of data, whereas STATA was used for the actual statistical analyses.
Ethics
No informed consent was required for this study, as we used exclusively routinely collected data.
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