RESULTSWe assessed mortality rates

RESULTS

We assessed mortality rates (overall and by subgroup) in the study sample as well as relationships between the different categories of variables assessed.

Baseline Predictors of Mortality

Of the 1326 participants, 131 (9.9%) died over the course of the 9-year study (11.0 per 1000 person-years). Table 1 presents mortality rates and bivariate odds of mortality over the course of the study as a function of sociodemographic characteristics and functioning at intake. Being older than 30 years nearly doubled the risk of mortality (OR=1.98), whereas being African American was associated with reduced odds of mortality (OR=0.52).

The risk of mortality increased with more years of alcohol use and more years of opioid use prior to baseline. We also found positive relationships between mortality and a longer amount of time from first use to first seeking treatment and having a history of overdose or delirium tremens. In addition, individuals with physical disabilities, chronic medical illnesses (e.g., seizures, asthma, emphysema, high blood pressure, heart disease, cirrhosis, pancreatitis, diabetes), hospitalizations in the 6 months before intake, and Addiction Severity Index medical composite scores above the median were at significantly increased risk of mortality, as were those who were living alone, were living below the poverty line (as defined by the US Department of Health and Human Services52), had engaged in any illegal acts for money, or had been charged with a violent act in the 6 months before intake.

Predictors of Sustained Abstinence

Although percentage of time abstinent in the overall sample increased from 55% during the 6 months before intake to 79% at the end of the study period, only 418 of the 1222 participants (34%) included in the multivariate analysis achieved 1 or more years of abstinence. Odds ratios for the multivariate logistic regression tests associated with sustained abstinence or death in the subsequent 12 months are displayed in Table 2. The rows show the predictors that were significant in the multivariate model after stepwise selection. The predictors are organized by time frame: baseline, months 0 to 6 (initial treatment response), and months 7 to 96 (long-term response). At baseline all measures from Table 1 were considered, but only those that remained statistically significant in the multivariate model are included in Table 2. For the latter 2 time periods, we also considered number of substance abuse treatment episodes, percentage of time in treatment and in the hospital, and involvement in illegal activity for money.

Examination of the model including proximal measures revealed that no baseline risk factors were significantly related to the likelihood of achieving sustained abstinence. However, a higher number of substance abuse treatment episodes during the first 6 months of the study (OR=1.32 per episode) and a longer amount of time spent in treatment over the course of the study (OR=1.42) increased the likelihood of achieving sustained abstinence. By comparison, after the first 6 months of the study, the likelihood of sustaining abstinence decreased as the number of subsequent treatment episodes increased (OR=0.75 per episode), the percentage of time spent hospitalized increased (OR=0.14 per 10-percentage-point change), and the percentage of days involved in illegal activity for money increased (OR=0.77 per 10-percentage-point change).

Predicting Time to Mortality

Table 2 also provides odds ratios significantly associated with mortality in the subsequent 12 months. This analysis included all of the variables from the baseline model just discussed, percentage of time abstinent in the initial and subsequent periods (as measures of harm reduction), and years of sustained abstinence at the final observation before mortality or the final observation minus 1 year. Mortality in the subsequent 12 months was associated with older age at intake (OR=1.82), the presence of a preexisting chronic illness (OR=1.85), and the amount of time a person engaged in illegal activity for money in the 6 months prior to intake (OR=1.14).

Although none of the initial treatment response variables remained significant in the multivariate model, mortality in the subsequent 12 months was associated with percentage of time spent in the hospital (OR=14.45) and in substance abuse treatment (OR=1.68) over the long term (months 7-96). We interpreted these 2 findings as markers of nonresponse to treatment. Over the long term, the likelihood of mortality decreased with additional substance abuse treatment episodes (OR=0.68), more time abstinent (OR=0.74), and more years of continuous abstinence (OR=0.81). Thus, the extent to which people with substance abuse problems were readmitted combined with their response to treatment (as both a percentage of time and a continuous period) was associated with a reduced risk of mortality.

Relationships Between Risk, Treatment, Abstinence, and Mortality

Figure 1 provides a graphic summary of the numeric findings presented in Table 2 to help illustrate the complex relationships described here. A complex relationship existed between treatment, abstinence, and mortality in the multivariate analyses. The likelihood of mortality decreased directly as the total number of treatment episodes increased (OR=0.68 per episode) but increased with increasing percentage of time in treatment (OR=1.68 per 10- percentage-point change). Treatment also had an indirect effect via the reduced risk of mortality associated with both continuous abstinence (OR=0.81 per year) and percentage of time abstinent, even when it was episodic (OR=0.74 per 10-percentage-point change). The likelihood of sustained abstinence increased with increases in the number of treatment episodes in the first 6 months (OR=1.32 per additional episode) and in the percentage of time in treatment over the study period (OR=1.42 per 10-percentage-point change). However, the number of times a person returned to treatment between 6 months and 8 years after intake was associated with a lower likelihood of eventually achieving sustained abstinence (OR=0.75 per additional episode). Thus, the timing of readmission matters.

We used Baron and Kenny's approach to assess the extent to which years of sustained abstinence mediated the relationships between risk, treatment, and mortality.51 According to the first criterion, the hypothesized mediator (years of abstinence) and each of the other predictors had to be significantly related to the dependent variable (mortality). The second criterion required 1 or more of the predictors to have a significant relationship with the mediator. As shown in Table 2 and Figure 1, these 2 criteria were met for a subset of 3 variables: percentage of time hospitalized, number of substance abuse treatment episodes, and percentage of time in treatment (10-percentagepoint units).

The third criterion required a change in 1 or more of the relationships between these predictors and mortality when the model was estimated with and without the mediator (data not shown); it also required that there be a better overall fit with the mediator in the model. The odds ratios for predicting mortality in the subsequent 12 months changed significantly (from the model without the mediator to the model with the mediator in Figure 1) for each of these variables (from 18.4 to 14.45 for percentage of time hospitalized, from 0.71 to 0.68 for number of substance abuse treatment episodes in months 7 to 96, and from 1.63 to 1.68 for percentage of time in substance abuse treatment). Moreover, including years of sustained abstinence improved the overall model fit with respect to predicting mortality in the subsequent12 months (χ21=12.11, P

Hasil (Bahasa Indonesia) 1:

RESULTSWe assessed mortality rates (overall and by subgroup) in the study sample as well as relationships between the different categories of variables assessed.Baseline Predictors of MortalityOf the 1326 participants, 131 (9.9%) died over the course of the 9-year study (11.0 per 1000 person-years). Table 1 presents mortality rates and bivariate odds of mortality over the course of the study as a function of sociodemographic characteristics and functioning at intake. Being older than 30 years nearly doubled the risk of mortality (OR=1.98), whereas being African American was associated with reduced odds of mortality (OR=0.52).The risk of mortality increased with more years of alcohol use and more years of opioid use prior to baseline. We also found positive relationships between mortality and a longer amount of time from first use to first seeking treatment and having a history of overdose or delirium tremens. In addition, individuals with physical disabilities, chronic medical illnesses (e.g., seizures, asthma, emphysema, high blood pressure, heart disease, cirrhosis, pancreatitis, diabetes), hospitalizations in the 6 months before intake, and Addiction Severity Index medical composite scores above the median were at significantly increased risk of mortality, as were those who were living alone, were living below the poverty line (as defined by the US Department of Health and Human Services52), had engaged in any illegal acts for money, or had been charged with a violent act in the 6 months before intake.Predictors of Sustained AbstinenceAlthough percentage of time abstinent in the overall sample increased from 55% during the 6 months before intake to 79% at the end of the study period, only 418 of the 1222 participants (34%) included in the multivariate analysis achieved 1 or more years of abstinence. Odds ratios for the multivariate logistic regression tests associated with sustained abstinence or death in the subsequent 12 months are displayed in Table 2. The rows show the predictors that were significant in the multivariate model after stepwise selection. The predictors are organized by time frame: baseline, months 0 to 6 (initial treatment response), and months 7 to 96 (long-term response). At baseline all measures from Table 1 were considered, but only those that remained statistically significant in the multivariate model are included in Table 2. For the latter 2 time periods, we also considered number of substance abuse treatment episodes, percentage of time in treatment and in the hospital, and involvement in illegal activity for money.Examination of the model including proximal measures revealed that no baseline risk factors were significantly related to the likelihood of achieving sustained abstinence. However, a higher number of substance abuse treatment episodes during the first 6 months of the study (OR=1.32 per episode) and a longer amount of time spent in treatment over the course of the study (OR=1.42) increased the likelihood of achieving sustained abstinence. By comparison, after the first 6 months of the study, the likelihood of sustaining abstinence decreased as the number of subsequent treatment episodes increased (OR=0.75 per episode), the percentage of time spent hospitalized increased (OR=0.14 per 10-percentage-point change), and the percentage of days involved in illegal activity for money increased (OR=0.77 per 10-percentage-point change).Predicting Time to MortalityTable 2 also provides odds ratios significantly associated with mortality in the subsequent 12 months. This analysis included all of the variables from the baseline model just discussed, percentage of time abstinent in the initial and subsequent periods (as measures of harm reduction), and years of sustained abstinence at the final observation before mortality or the final observation minus 1 year. Mortality in the subsequent 12 months was associated with older age at intake (OR=1.82), the presence of a preexisting chronic illness (OR=1.85), and the amount of time a person engaged in illegal activity for money in the 6 months prior to intake (OR=1.14).Although none of the initial treatment response variables remained significant in the multivariate model, mortality in the subsequent 12 months was associated with percentage of time spent in the hospital (OR=14.45) and in substance abuse treatment (OR=1.68) over the long term (months 7-96). We interpreted these 2 findings as markers of nonresponse to treatment. Over the long term, the likelihood of mortality decreased with additional substance abuse treatment episodes (OR=0.68), more time abstinent (OR=0.74), and more years of continuous abstinence (OR=0.81). Thus, the extent to which people with substance abuse problems were readmitted combined with their response to treatment (as both a percentage of time and a continuous period) was associated with a reduced risk of mortality.Relationships Between Risk, Treatment, Abstinence, and MortalityFigure 1 provides a graphic summary of the numeric findings presented in Table 2 to help illustrate the complex relationships described here. A complex relationship existed between treatment, abstinence, and mortality in the multivariate analyses. The likelihood of mortality decreased directly as the total number of treatment episodes increased (OR=0.68 per episode) but increased with increasing percentage of time in treatment (OR=1.68 per 10- percentage-point change). Treatment also had an indirect effect via the reduced risk of mortality associated with both continuous abstinence (OR=0.81 per year) and percentage of time abstinent, even when it was episodic (OR=0.74 per 10-percentage-point change). The likelihood of sustained abstinence increased with increases in the number of treatment episodes in the first 6 months (OR=1.32 per additional episode) and in the percentage of time in treatment over the study period (OR=1.42 per 10-percentage-point change). However, the number of times a person returned to treatment between 6 months and 8 years after intake was associated with a lower likelihood of eventually achieving sustained abstinence (OR=0.75 per additional episode). Thus, the timing of readmission matters.We used Baron and Kenny's approach to assess the extent to which years of sustained abstinence mediated the relationships between risk, treatment, and mortality.51 According to the first criterion, the hypothesized mediator (years of abstinence) and each of the other predictors had to be significantly related to the dependent variable (mortality). The second criterion required 1 or more of the predictors to have a significant relationship with the mediator. As shown in Table 2 and Figure 1, these 2 criteria were met for a subset of 3 variables: percentage of time hospitalized, number of substance abuse treatment episodes, and percentage of time in treatment (10-percentagepoint units).The third criterion required a change in 1 or more of the relationships between these predictors and mortality when the model was estimated with and without the mediator (data not shown); it also required that there be a better overall fit with the mediator in the model. The odds ratios for predicting mortality in the subsequent 12 months changed significantly (from the model without the mediator to the model with the mediator in Figure 1) for each of these variables (from 18.4 to 14.45 for percentage of time hospitalized, from 0.71 to 0.68 for number of substance abuse treatment episodes in months 7 to 96, and from 1.63 to 1.68 for percentage of time in substance abuse treatment). Moreover, including years of sustained abstinence improved the overall model fit with respect to predicting mortality in the subsequent12 months (χ21=12.11, P<.01). Thus, years of sustained abstinence qualified as a significant mediator of mortality risk in the subsequent 12 months.

Hasil (Bahasa Indonesia) 2:

HASIL Kami menilai tingkat kematian (secara keseluruhan dan dengan subkelompok) dalam sampel penelitian serta hubungan antara berbagai kategori variabel yang dinilai. Dasar Prediktor Mortalitas Dari 1.326 peserta, 131 (9,9%) meninggal selama 9 tahun studi (11,0 per 1.000 orang-tahun). Tabel 1 menyajikan tingkat kematian dan peluang bivariat kematian selama studi sebagai fungsi karakteristik sosiodemografi dan berfungsi pada asupan. Menjadi lebih tua dari 30 tahun hampir dua kali lipat risiko kematian (OR = 1,98), sedangkan menjadi Afrika Amerika dikaitkan dengan kemungkinan penurunan mortalitas (OR = 0,52). Risiko kematian meningkat dengan tahun lagi penggunaan alkohol dan tahun lagi opioid menggunakan sebelum baseline. Kami juga menemukan hubungan yang positif antara kematian dan jumlah waktu yang lebih lama dari penggunaan pertama yang pertama mencari pengobatan dan memiliki sejarah overdosis atau delirium tremens. Selain itu, individu dengan cacat fisik, penyakit medis yang kronis (misalnya, kejang, asma, emfisema, tekanan darah tinggi, penyakit jantung, sirosis, pankreatitis, diabetes), rawat inap dalam 6 bulan sebelum intake, dan Ketergantungan Indeks Keparahan komposit medis skor di atas median berada di meningkat secara signifikan risiko kematian, seperti mereka yang hidup sendiri, hidup di bawah garis kemiskinan (seperti yang didefinisikan oleh Departemen Kesehatan dan Manusia Services52), telah terlibat dalam setiap tindakan ilegal untuk uang, atau telah dibebankan dengan tindak kekerasan dalam 6 bulan sebelum asupan. Prediktor Pantang berkelanjutan Meskipun persentase waktu berpuasa dalam sampel keseluruhan meningkat dari 55% selama 6 bulan sebelum asupan hingga 79% pada akhir masa studi, hanya 418 dari 1222 peserta (34%) termasuk dalam analisis multivariat mencapai 1 tahun atau lebih pantang. Odds rasio untuk tes regresi logistik multivariat terkait dengan pantang berkelanjutan atau kematian dalam 12 bulan berikutnya akan ditampilkan pada Tabel 2. baris menunjukkan prediktor yang signifikan dalam model multivariat seleksi bertahap. Prediktor yang diselenggarakan oleh kerangka waktu: awal, bulan 0 sampai 6 (respon pengobatan awal), dan bulan 7-96 (jangka panjang respon). Pada awal semua tindakan dari Tabel 1 dianggap, tetapi hanya mereka yang tetap signifikan secara statistik dalam model multivariat termasuk dalam Tabel 2. Untuk 2 yang terakhir periode waktu, kami juga dianggap jumlah tahapan pengobatan penyalahgunaan zat, persentase waktu dalam perawatan dan di rumah sakit, dan keterlibatan dalam kegiatan ilegal uang. Pemeriksaan model termasuk langkah-langkah proksimal mengungkapkan bahwa tidak ada faktor risiko pada awal secara signifikan terkait dengan kemungkinan mencapai pantang berkelanjutan. Namun, jumlah yang lebih tinggi dari tahapan pengobatan penyalahgunaan zat selama 6 bulan pertama penelitian (OR = 1,32 per episode) dan jumlah yang lebih lama waktu yang dihabiskan dalam pengobatan selama penelitian (OR = 1,42) meningkatkan kemungkinan mencapai pantang berkelanjutan. Sebagai perbandingan, setelah 6 bulan pertama penelitian, kemungkinan mempertahankan pantang menurun jumlah tahapan pengobatan selanjutnya meningkat (OR = 0,75 per episode), persentase waktu yang dihabiskan di rumah sakit meningkat (OR = 0,14 per 10-percentage- Perubahan titik), dan persentase hari terlibat dalam kegiatan ilegal uang meningkat (OR = 0.77 per 10 persentase poin perubahan). Memprediksi Waktu untuk Mortality Table 2 juga menyediakan odds ratio secara signifikan dikaitkan dengan kematian dalam 12 bulan berikutnya. Analisis ini mencakup semua variabel dari model dasar yang baru saja dibahas, persentase waktu berpuasa pada periode awal dan selanjutnya (sebagai ukuran pengurangan dampak buruk), dan tahun berkelanjutan pantang pada pengamatan terakhir sebelum kematian atau pengamatan akhir minus 1 tahun . Kematian dalam 12 bulan berikutnya dikaitkan dengan usia yang lebih tua di intake (OR = 1,82), kehadiran penyakit kronis yang sudah ada sebelumnya (OR = 1,85), dan jumlah waktu orang yang terlibat dalam kegiatan ilegal uang dalam 6 bulan sebelum asupan (OR = 1,14). Meskipun tidak ada variabel respon pengobatan awal tetap signifikan dalam model multivariat, angka kematian dalam 12 bulan berikutnya dikaitkan dengan persentase waktu yang dihabiskan di rumah sakit (OR = 14,45) dan dalam perawatan penyalahgunaan zat ( OR = 1,68) dalam jangka panjang (bulan 7-96). Kami ditafsirkan 2 temuan ini sebagai penanda response terhadap pengobatan. Selama jangka panjang, kemungkinan kematian menurun dengan episode tambahan pengobatan penyalahgunaan zat (OR = 0,68), lebih banyak waktu berpuasa (OR = 0,74), dan tahun lagi pantang terus menerus (OR = 0,81). Dengan demikian, sejauh mana orang dengan masalah penyalahgunaan zat yang diterima kembali dikombinasikan dengan respon mereka terhadap pengobatan (baik sebagai persentase waktu dan jangka waktu terus menerus) dikaitkan dengan penurunan risiko kematian. Hubungan Antara Risiko, Pengobatan, Pantang, dan Kematian Gambar 1 memberikan ringkasan grafis dari temuan numerik disajikan dalam Tabel 2 untuk membantu menggambarkan hubungan yang kompleks dijelaskan di sini. Sebuah hubungan yang kompleks ada antara pengobatan, pantang, dan kematian dalam analisis multivariat. Kemungkinan kematian menurun secara langsung sebagai jumlah tahapan pengobatan meningkat (OR = 0,68 per episode) namun meningkat dengan meningkatnya persentase waktu dalam pengobatan (OR = 1,68 per 10- perubahan persentase poin). Pengobatan juga memiliki efek tidak langsung melalui penurunan risiko kematian terkait dengan kedua pantang terus menerus (OR = 0,81 per tahun) dan persentase waktu berpuasa, bahkan ketika itu episodik (OR = 0,74 perubahan per 10-poin persentase). Kemungkinan berkelanjutan pantang meningkat dengan peningkatan jumlah episode pengobatan dalam 6 bulan pertama (OR = 1.32 per episode tambahan) dan persentase waktu dalam pengobatan selama periode penelitian (OR = 1.42 per 10-poin persentase perubahan ). Namun, berapa kali seseorang kembali ke pengobatan antara 6 bulan dan 8 tahun setelah asupan dikaitkan dengan kemungkinan lebih rendah dari pada akhirnya mencapai pantang berkelanjutan (OR = 0,75 per episode tambahan). Dengan demikian, waktu hal diterima kembali. Kami menggunakan pendekatan Baron dan Kenny untuk menilai sejauh mana tahun berkelanjutan pantang dimediasi hubungan antara risiko, pengobatan, dan mortality.51 Menurut kriteria pertama, mediator hipotesis (tahun pantang) dan masing-masing prediktor lain harus secara signifikan berhubungan dengan variabel dependen (mortalitas). Kriteria kedua diperlukan 1 atau lebih prediktor untuk memiliki hubungan yang signifikan dengan mediator. Seperti terlihat pada Tabel 2 dan Gambar 1, 2 kriteria tersebut dipenuhi untuk subset dari 3 variabel:. Persentase waktu dirawat di rumah sakit, jumlah tahapan pengobatan penyalahgunaan zat, dan persentase waktu dalam pengobatan (unit 10-percentagepoint) Kriteria ketiga yang diperlukan perubahan dalam 1 atau lebih dari hubungan antara prediktor dan kematian ini ketika model diperkirakan dengan dan tanpa mediator (data tidak ditampilkan); itu juga mengharuskan ada sebuah keseluruhan lebih cocok dengan mediator dalam model. Odds ratio untuk memprediksi kematian dalam 12 bulan berikutnya berubah secara signifikan (dari model tanpa mediator untuk model dengan mediator pada Gambar 1) untuk masing-masing variabel (18,4-14,45 untuk persentase waktu dirawat di rumah sakit, 0,71-0,68 untuk jumlah tahapan pengobatan penyalahgunaan zat dalam beberapa bulan 7-96, dan 1,63-1,68 untuk persentase waktu dalam penyalahgunaan zat pengobatan). Selain itu, termasuk tahun berkelanjutan pantang meningkatkan keseluruhan model fit sehubungan dengan memprediksi kematian dalam bulan subsequent12 (χ21 = 12.11, P <.01). Dengan demikian, tahun berkelanjutan pantang memenuhi syarat sebagai mediator signifikan risiko kematian dalam 12 bulan berikutnya.