{"title":"社论:评估 HBV 和 ACLF 患者的预后--合并症很重要。作者回复","authors":"Jiong Yu, Xinyi Chen, Guoqiang Cao, Qiaoling Pan, Chenjie Huang, Rui Luo, Xiaoqing Lu, Xiaoxiao Chen, Tan Li, Haijun Huang, Jian Wu, Lanjuan Li, Hongcui Cao","doi":"10.1111/apt.18392","DOIUrl":null,"url":null,"abstract":"<p>We extend our sincere gratitude to Dr. Francesco Paolo Russo and Alberto Ferrarese for their thorough evaluation and professional insights on our study [<span>1</span>]. We are gratified by their recognition of the potential of the age-adjusted Charlson Comorbidity Index for Hepatitis B Virus-Related Acute-on-Chronic Liver Failure (aCCI-HBV-ACLF) score in enhancing the accuracy of short-term and medium-term prognostic predictions, particularly in integrating comorbidity factors and reducing variability among clinicians [<span>2</span>].</p>\n<p>Previous research has established that multiple comorbidities are strongly associated with poor prognosis, with extrahepatic complications such as chronic renal failure and diabetes significantly elevating the mortality risk in patients with liver disease [<span>3-5</span>]. However, the relatively low incidence of these comorbidities presents challenges in fully incorporating them into prognostic models. Although the aCCI was initially designed for long-term prognostic evaluation, study has underscored its relevance in evaluating the prognosis of liver disease patients [<span>6</span>]. Similarly, our further analysis demonstrated that in the short-term prognosis of patients with HBV-related ACLF, nearly all comorbidities included in the aCCI are significantly correlated with short-term survival outcomes (Table 1). For instance, cardiovascular diseases were associated with a 287% increase in the 28-day mortality risk and a 267% increase in the 90-day mortality risk. Additionally, patients with chronic obstructive pulmonary disease, connective tissue diseases, diabetes, moderate to severe renal disease, tumours and haematological diseases exhibited substantially increased mortality risks. In contrast, although peptic ulcer disease showed a certain increase in risk, it did not reach statistical significance (<i>p</i> > 0.05).</p>\n<div>\n<header><span>TABLE 1. </span>Relationships between comorbidity and 28-day mortality and 90-day mortality in patients with HBV-ACLF.</header>\n<div tabindex=\"0\">\n<table>\n<thead>\n<tr>\n<th rowspan=\"2\">Variables</th>\n<th rowspan=\"2\">Total (<i>n</i>)</th>\n<th colspan=\"3\">28-day mortality</th>\n<th colspan=\"3\">90-day mortality</th>\n</tr>\n<tr>\n<th style=\"top: 41px;\">Events (%)</th>\n<th style=\"top: 41px;\">HR (95% CI)</th>\n<th style=\"top: 41px;\"><i>p</i> value</th>\n<th style=\"top: 41px;\">Events (%)</th>\n<th style=\"top: 41px;\">HR (95% CI)</th>\n<th style=\"top: 41px;\"><i>p</i> value</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td>Total</td>\n<td>1238</td>\n<td>295 (23.8)</td>\n<td></td>\n<td></td>\n<td>397 (32.1)</td>\n<td></td>\n<td></td>\n</tr>\n<tr>\n<td colspan=\"8\">Cardiovascular diseases<sup>a</sup></td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">Yes</td>\n<td>31</td>\n<td>22 (71.0)</td>\n<td rowspan=\"2\">3.87 (2.51, 5.98)</td>\n<td rowspan=\"2\">< 0.001</td>\n<td>24 (77.4)</td>\n<td rowspan=\"2\">3.67 (2.42, 5.56)</td>\n<td rowspan=\"2\">< 0.001</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">No</td>\n<td>1207</td>\n<td>273 (22.6)</td>\n<td>373 (30.9)</td>\n</tr>\n<tr>\n<td colspan=\"8\">COPD</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">Yes</td>\n<td>22</td>\n<td>15 (68.2)</td>\n<td rowspan=\"2\">4.02 (2.39, 6.76)</td>\n<td rowspan=\"2\">< 0.001</td>\n<td>15 (68.2)</td>\n<td rowspan=\"2\">3.29 (1.96, 5.52)</td>\n<td rowspan=\"2\">< 0.001</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">No</td>\n<td>1216</td>\n<td>280 (23.0)</td>\n<td>382 (31.4)</td>\n</tr>\n<tr>\n<td colspan=\"8\">Connective tissue disease</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">Yes</td>\n<td>25</td>\n<td>13 (52.0)</td>\n<td rowspan=\"2\">2.45 (1.41, 4.28)</td>\n<td rowspan=\"2\">< 0.001</td>\n<td>17 (68.0)</td>\n<td rowspan=\"2\">2.66 (1.64, 4.33)</td>\n<td rowspan=\"2\">< 0.001</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">No</td>\n<td>1213</td>\n<td>282 (23.2)</td>\n<td>380 (31.3)</td>\n</tr>\n<tr>\n<td colspan=\"8\">Ulcer disease</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">Yes</td>\n<td>27</td>\n<td>10 (37.0)</td>\n<td rowspan=\"2\">1.64 (0.87, 3.08)</td>\n<td rowspan=\"2\">0.124</td>\n<td>13 (48.2)</td>\n<td rowspan=\"2\">1.64 (0.94, 2.85)</td>\n<td rowspan=\"2\">0.079</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">No</td>\n<td>1211</td>\n<td>285 (23.5)</td>\n<td>384 (31.7)</td>\n</tr>\n<tr>\n<td colspan=\"8\">Diabetes</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">Yes</td>\n<td>116</td>\n<td>44 (37.9)</td>\n<td rowspan=\"2\">1.85 (1.34, 2.55)</td>\n<td rowspan=\"2\">< 0.001</td>\n<td>58 (50.0)</td>\n<td rowspan=\"2\">1.90 (1.43, 2.51)</td>\n<td rowspan=\"2\">< 0.001</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">No</td>\n<td>1122</td>\n<td>251 (22.4)</td>\n<td>339 (30.2)</td>\n</tr>\n<tr>\n<td colspan=\"8\">Moderate to severe kidney disease</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">Yes</td>\n<td>60</td>\n<td>38 (63.3)</td>\n<td rowspan=\"2\">4.54 (3.22, 6.39)</td>\n<td rowspan=\"2\">< 0.001</td>\n<td>45 (75.0)</td>\n<td rowspan=\"2\">4.32 (3.16, 5.90)</td>\n<td rowspan=\"2\">< 0.001</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">No</td>\n<td>1178</td>\n<td>257 (21.8)</td>\n<td>352 (29.9)</td>\n</tr>\n<tr>\n<td colspan=\"8\">Tumours and haematological diseases<sup>a</sup></td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">Yes</td>\n<td>43</td>\n<td>22 (51.2)</td>\n<td rowspan=\"2\">2.57 (1.67, 3.97)</td>\n<td rowspan=\"2\">< 0.001</td>\n<td>24 (55.8)</td>\n<td rowspan=\"2\">2.21 (1.46, 3.34)</td>\n<td rowspan=\"2\">< 0.001</td>\n</tr>\n<tr>\n<td style=\"padding-left:2em;\">No</td>\n<td>1195</td>\n<td>273 (22.9)</td>\n<td>373 (31.2)</td>\n</tr>\n</tbody>\n</table>\n</div>\n<div>\n<ul>\n<li>\n<i>Note:</i> Tumours and haematological diseases, including leukaemia, lymphoma, metastatic solid tumour and any tumour. </li>\n<li> Abbreviations: CI, confidence interval; COPD, chronic obstructive pulmonary disease; HBV-ACLF, hepatitis B virus-related acute-on-chronic liver failure; HR, hazard ratio. </li>\n<li title=\"Footnote 1\"><span>\n<sup>a</sup>\n</span> Cardiovascular diseases, including myocardial infarction, congestive heart failure, peripheral vascular disease and cerebrovascular disease. </li>\n</ul>\n</div>\n<div></div>\n</div>\n<p>We fully concur with the concern regarding the exclusion of liver transplant patients from the study population. Liver transplantation is a crucial therapeutic option for ACLF, demonstrating significant improvements in patient outcomes [<span>7, 8</span>]. Studies have demonstrated that liver transplantation markedly enhances survival rates compared to patients not receiving transplantation, with only a small proportion succumbing to surgical complications or postoperative issues [<span>9</span>]. Including liver transplant recipients in this study could disproportionately elevate the incidence of end-point events, potentially leading to an overestimation of associated risks. Moreover, differences in medical expertise and resources across centres can significantly influence transplant success rates and post-transplant survival outcomes. Critical determinants of transplantation outcomes include the quality of donor organs, the overall health status of recipients and the expertise of the surgical team [<span>10</span>]. Not all patients awaiting transplantation are eligible, and therefore, including liver transplant recipients might compromise the predictive accuracy of the model when applied to other medical centres. Consequently, liver transplant recipients were excluded from the model's development.</p>\n<p>We also acknowledge the potential influence of regional and racial variations on the generalisability of the aCCI-HBV-ACLF score. To address this, we aim to expand our data collection in future studies to validate the score in diverse populations. Once again, we are grateful for their in-depth review and constructive suggestions on our study. Their feedback has further illuminated the applicability and avenues for optimisation of the aCCI-HBV-ACLF score in different populations. We firmly believe that the aCCI-HBV-ACLF score can provide a more accurate prognostic assessment tool for the treatment and management of patients with ACLF in clinical practice.</p>","PeriodicalId":121,"journal":{"name":"Alimentary Pharmacology & Therapeutics","volume":"46 1","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Editorial: Assessing the Prognosis of Patients With HBV and ACLF—Comorbidities Matter. Authors' Reply\",\"authors\":\"Jiong Yu, Xinyi Chen, Guoqiang Cao, Qiaoling Pan, Chenjie Huang, Rui Luo, Xiaoqing Lu, Xiaoxiao Chen, Tan Li, Haijun Huang, Jian Wu, Lanjuan Li, Hongcui Cao\",\"doi\":\"10.1111/apt.18392\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>We extend our sincere gratitude to Dr. Francesco Paolo Russo and Alberto Ferrarese for their thorough evaluation and professional insights on our study [<span>1</span>]. We are gratified by their recognition of the potential of the age-adjusted Charlson Comorbidity Index for Hepatitis B Virus-Related Acute-on-Chronic Liver Failure (aCCI-HBV-ACLF) score in enhancing the accuracy of short-term and medium-term prognostic predictions, particularly in integrating comorbidity factors and reducing variability among clinicians [<span>2</span>].</p>\\n<p>Previous research has established that multiple comorbidities are strongly associated with poor prognosis, with extrahepatic complications such as chronic renal failure and diabetes significantly elevating the mortality risk in patients with liver disease [<span>3-5</span>]. However, the relatively low incidence of these comorbidities presents challenges in fully incorporating them into prognostic models. Although the aCCI was initially designed for long-term prognostic evaluation, study has underscored its relevance in evaluating the prognosis of liver disease patients [<span>6</span>]. Similarly, our further analysis demonstrated that in the short-term prognosis of patients with HBV-related ACLF, nearly all comorbidities included in the aCCI are significantly correlated with short-term survival outcomes (Table 1). For instance, cardiovascular diseases were associated with a 287% increase in the 28-day mortality risk and a 267% increase in the 90-day mortality risk. Additionally, patients with chronic obstructive pulmonary disease, connective tissue diseases, diabetes, moderate to severe renal disease, tumours and haematological diseases exhibited substantially increased mortality risks. In contrast, although peptic ulcer disease showed a certain increase in risk, it did not reach statistical significance (<i>p</i> > 0.05).</p>\\n<div>\\n<header><span>TABLE 1. </span>Relationships between comorbidity and 28-day mortality and 90-day mortality in patients with HBV-ACLF.</header>\\n<div tabindex=\\\"0\\\">\\n<table>\\n<thead>\\n<tr>\\n<th rowspan=\\\"2\\\">Variables</th>\\n<th rowspan=\\\"2\\\">Total (<i>n</i>)</th>\\n<th colspan=\\\"3\\\">28-day mortality</th>\\n<th colspan=\\\"3\\\">90-day mortality</th>\\n</tr>\\n<tr>\\n<th style=\\\"top: 41px;\\\">Events (%)</th>\\n<th style=\\\"top: 41px;\\\">HR (95% CI)</th>\\n<th style=\\\"top: 41px;\\\"><i>p</i> value</th>\\n<th style=\\\"top: 41px;\\\">Events (%)</th>\\n<th style=\\\"top: 41px;\\\">HR (95% CI)</th>\\n<th style=\\\"top: 41px;\\\"><i>p</i> value</th>\\n</tr>\\n</thead>\\n<tbody>\\n<tr>\\n<td>Total</td>\\n<td>1238</td>\\n<td>295 (23.8)</td>\\n<td></td>\\n<td></td>\\n<td>397 (32.1)</td>\\n<td></td>\\n<td></td>\\n</tr>\\n<tr>\\n<td colspan=\\\"8\\\">Cardiovascular diseases<sup>a</sup></td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">Yes</td>\\n<td>31</td>\\n<td>22 (71.0)</td>\\n<td rowspan=\\\"2\\\">3.87 (2.51, 5.98)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n<td>24 (77.4)</td>\\n<td rowspan=\\\"2\\\">3.67 (2.42, 5.56)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">No</td>\\n<td>1207</td>\\n<td>273 (22.6)</td>\\n<td>373 (30.9)</td>\\n</tr>\\n<tr>\\n<td colspan=\\\"8\\\">COPD</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">Yes</td>\\n<td>22</td>\\n<td>15 (68.2)</td>\\n<td rowspan=\\\"2\\\">4.02 (2.39, 6.76)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n<td>15 (68.2)</td>\\n<td rowspan=\\\"2\\\">3.29 (1.96, 5.52)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">No</td>\\n<td>1216</td>\\n<td>280 (23.0)</td>\\n<td>382 (31.4)</td>\\n</tr>\\n<tr>\\n<td colspan=\\\"8\\\">Connective tissue disease</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">Yes</td>\\n<td>25</td>\\n<td>13 (52.0)</td>\\n<td rowspan=\\\"2\\\">2.45 (1.41, 4.28)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n<td>17 (68.0)</td>\\n<td rowspan=\\\"2\\\">2.66 (1.64, 4.33)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">No</td>\\n<td>1213</td>\\n<td>282 (23.2)</td>\\n<td>380 (31.3)</td>\\n</tr>\\n<tr>\\n<td colspan=\\\"8\\\">Ulcer disease</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">Yes</td>\\n<td>27</td>\\n<td>10 (37.0)</td>\\n<td rowspan=\\\"2\\\">1.64 (0.87, 3.08)</td>\\n<td rowspan=\\\"2\\\">0.124</td>\\n<td>13 (48.2)</td>\\n<td rowspan=\\\"2\\\">1.64 (0.94, 2.85)</td>\\n<td rowspan=\\\"2\\\">0.079</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">No</td>\\n<td>1211</td>\\n<td>285 (23.5)</td>\\n<td>384 (31.7)</td>\\n</tr>\\n<tr>\\n<td colspan=\\\"8\\\">Diabetes</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">Yes</td>\\n<td>116</td>\\n<td>44 (37.9)</td>\\n<td rowspan=\\\"2\\\">1.85 (1.34, 2.55)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n<td>58 (50.0)</td>\\n<td rowspan=\\\"2\\\">1.90 (1.43, 2.51)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">No</td>\\n<td>1122</td>\\n<td>251 (22.4)</td>\\n<td>339 (30.2)</td>\\n</tr>\\n<tr>\\n<td colspan=\\\"8\\\">Moderate to severe kidney disease</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">Yes</td>\\n<td>60</td>\\n<td>38 (63.3)</td>\\n<td rowspan=\\\"2\\\">4.54 (3.22, 6.39)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n<td>45 (75.0)</td>\\n<td rowspan=\\\"2\\\">4.32 (3.16, 5.90)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">No</td>\\n<td>1178</td>\\n<td>257 (21.8)</td>\\n<td>352 (29.9)</td>\\n</tr>\\n<tr>\\n<td colspan=\\\"8\\\">Tumours and haematological diseases<sup>a</sup></td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">Yes</td>\\n<td>43</td>\\n<td>22 (51.2)</td>\\n<td rowspan=\\\"2\\\">2.57 (1.67, 3.97)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n<td>24 (55.8)</td>\\n<td rowspan=\\\"2\\\">2.21 (1.46, 3.34)</td>\\n<td rowspan=\\\"2\\\">< 0.001</td>\\n</tr>\\n<tr>\\n<td style=\\\"padding-left:2em;\\\">No</td>\\n<td>1195</td>\\n<td>273 (22.9)</td>\\n<td>373 (31.2)</td>\\n</tr>\\n</tbody>\\n</table>\\n</div>\\n<div>\\n<ul>\\n<li>\\n<i>Note:</i> Tumours and haematological diseases, including leukaemia, lymphoma, metastatic solid tumour and any tumour. </li>\\n<li> Abbreviations: CI, confidence interval; COPD, chronic obstructive pulmonary disease; HBV-ACLF, hepatitis B virus-related acute-on-chronic liver failure; HR, hazard ratio. </li>\\n<li title=\\\"Footnote 1\\\"><span>\\n<sup>a</sup>\\n</span> Cardiovascular diseases, including myocardial infarction, congestive heart failure, peripheral vascular disease and cerebrovascular disease. </li>\\n</ul>\\n</div>\\n<div></div>\\n</div>\\n<p>We fully concur with the concern regarding the exclusion of liver transplant patients from the study population. Liver transplantation is a crucial therapeutic option for ACLF, demonstrating significant improvements in patient outcomes [<span>7, 8</span>]. Studies have demonstrated that liver transplantation markedly enhances survival rates compared to patients not receiving transplantation, with only a small proportion succumbing to surgical complications or postoperative issues [<span>9</span>]. Including liver transplant recipients in this study could disproportionately elevate the incidence of end-point events, potentially leading to an overestimation of associated risks. Moreover, differences in medical expertise and resources across centres can significantly influence transplant success rates and post-transplant survival outcomes. Critical determinants of transplantation outcomes include the quality of donor organs, the overall health status of recipients and the expertise of the surgical team [<span>10</span>]. Not all patients awaiting transplantation are eligible, and therefore, including liver transplant recipients might compromise the predictive accuracy of the model when applied to other medical centres. Consequently, liver transplant recipients were excluded from the model's development.</p>\\n<p>We also acknowledge the potential influence of regional and racial variations on the generalisability of the aCCI-HBV-ACLF score. To address this, we aim to expand our data collection in future studies to validate the score in diverse populations. Once again, we are grateful for their in-depth review and constructive suggestions on our study. Their feedback has further illuminated the applicability and avenues for optimisation of the aCCI-HBV-ACLF score in different populations. We firmly believe that the aCCI-HBV-ACLF score can provide a more accurate prognostic assessment tool for the treatment and management of patients with ACLF in clinical practice.</p>\",\"PeriodicalId\":121,\"journal\":{\"name\":\"Alimentary Pharmacology & Therapeutics\",\"volume\":\"46 1\",\"pages\":\"\"},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2024-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Alimentary Pharmacology & Therapeutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/apt.18392\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alimentary Pharmacology & Therapeutics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/apt.18392","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Editorial: Assessing the Prognosis of Patients With HBV and ACLF—Comorbidities Matter. Authors' Reply
We extend our sincere gratitude to Dr. Francesco Paolo Russo and Alberto Ferrarese for their thorough evaluation and professional insights on our study [1]. We are gratified by their recognition of the potential of the age-adjusted Charlson Comorbidity Index for Hepatitis B Virus-Related Acute-on-Chronic Liver Failure (aCCI-HBV-ACLF) score in enhancing the accuracy of short-term and medium-term prognostic predictions, particularly in integrating comorbidity factors and reducing variability among clinicians [2].
Previous research has established that multiple comorbidities are strongly associated with poor prognosis, with extrahepatic complications such as chronic renal failure and diabetes significantly elevating the mortality risk in patients with liver disease [3-5]. However, the relatively low incidence of these comorbidities presents challenges in fully incorporating them into prognostic models. Although the aCCI was initially designed for long-term prognostic evaluation, study has underscored its relevance in evaluating the prognosis of liver disease patients [6]. Similarly, our further analysis demonstrated that in the short-term prognosis of patients with HBV-related ACLF, nearly all comorbidities included in the aCCI are significantly correlated with short-term survival outcomes (Table 1). For instance, cardiovascular diseases were associated with a 287% increase in the 28-day mortality risk and a 267% increase in the 90-day mortality risk. Additionally, patients with chronic obstructive pulmonary disease, connective tissue diseases, diabetes, moderate to severe renal disease, tumours and haematological diseases exhibited substantially increased mortality risks. In contrast, although peptic ulcer disease showed a certain increase in risk, it did not reach statistical significance (p > 0.05).
TABLE 1. Relationships between comorbidity and 28-day mortality and 90-day mortality in patients with HBV-ACLF.
Variables
Total (n)
28-day mortality
90-day mortality
Events (%)
HR (95% CI)
p value
Events (%)
HR (95% CI)
p value
Total
1238
295 (23.8)
397 (32.1)
Cardiovascular diseasesa
Yes
31
22 (71.0)
3.87 (2.51, 5.98)
< 0.001
24 (77.4)
3.67 (2.42, 5.56)
< 0.001
No
1207
273 (22.6)
373 (30.9)
COPD
Yes
22
15 (68.2)
4.02 (2.39, 6.76)
< 0.001
15 (68.2)
3.29 (1.96, 5.52)
< 0.001
No
1216
280 (23.0)
382 (31.4)
Connective tissue disease
Yes
25
13 (52.0)
2.45 (1.41, 4.28)
< 0.001
17 (68.0)
2.66 (1.64, 4.33)
< 0.001
No
1213
282 (23.2)
380 (31.3)
Ulcer disease
Yes
27
10 (37.0)
1.64 (0.87, 3.08)
0.124
13 (48.2)
1.64 (0.94, 2.85)
0.079
No
1211
285 (23.5)
384 (31.7)
Diabetes
Yes
116
44 (37.9)
1.85 (1.34, 2.55)
< 0.001
58 (50.0)
1.90 (1.43, 2.51)
< 0.001
No
1122
251 (22.4)
339 (30.2)
Moderate to severe kidney disease
Yes
60
38 (63.3)
4.54 (3.22, 6.39)
< 0.001
45 (75.0)
4.32 (3.16, 5.90)
< 0.001
No
1178
257 (21.8)
352 (29.9)
Tumours and haematological diseasesa
Yes
43
22 (51.2)
2.57 (1.67, 3.97)
< 0.001
24 (55.8)
2.21 (1.46, 3.34)
< 0.001
No
1195
273 (22.9)
373 (31.2)
Note: Tumours and haematological diseases, including leukaemia, lymphoma, metastatic solid tumour and any tumour.
a Cardiovascular diseases, including myocardial infarction, congestive heart failure, peripheral vascular disease and cerebrovascular disease.
We fully concur with the concern regarding the exclusion of liver transplant patients from the study population. Liver transplantation is a crucial therapeutic option for ACLF, demonstrating significant improvements in patient outcomes [7, 8]. Studies have demonstrated that liver transplantation markedly enhances survival rates compared to patients not receiving transplantation, with only a small proportion succumbing to surgical complications or postoperative issues [9]. Including liver transplant recipients in this study could disproportionately elevate the incidence of end-point events, potentially leading to an overestimation of associated risks. Moreover, differences in medical expertise and resources across centres can significantly influence transplant success rates and post-transplant survival outcomes. Critical determinants of transplantation outcomes include the quality of donor organs, the overall health status of recipients and the expertise of the surgical team [10]. Not all patients awaiting transplantation are eligible, and therefore, including liver transplant recipients might compromise the predictive accuracy of the model when applied to other medical centres. Consequently, liver transplant recipients were excluded from the model's development.
We also acknowledge the potential influence of regional and racial variations on the generalisability of the aCCI-HBV-ACLF score. To address this, we aim to expand our data collection in future studies to validate the score in diverse populations. Once again, we are grateful for their in-depth review and constructive suggestions on our study. Their feedback has further illuminated the applicability and avenues for optimisation of the aCCI-HBV-ACLF score in different populations. We firmly believe that the aCCI-HBV-ACLF score can provide a more accurate prognostic assessment tool for the treatment and management of patients with ACLF in clinical practice.
期刊介绍:
Alimentary Pharmacology & Therapeutics is a global pharmacology journal focused on the impact of drugs on the human gastrointestinal and hepato-biliary systems. It covers a diverse range of topics, often with immediate clinical relevance to its readership.