背景
衰弱是一種與老化過程密切相關的多層面綜合症，它代表了老化、疾病以及一系列社會心理、行為和環境因素對健康和整體福祉的累積影響。研究顯示衰弱與不良的健康結果有關，這強調了在臨床和研究環境中評估老年人衰弱的重要性。我們的研究目的在於依據調查資料為參考標準，使用健康保險資料庫中的國際疾病分類代碼來建置以資料庫為基礎的衰弱指標。
方法
我們使用台灣地區中老年身心社會生活狀況長期追蹤調查（Taiwan Longitudinal Study on Aging, TLSA）調查資料庫建立以調查為基礎的衰弱指標作為參考標準。我們使用lasso迴歸模型來選擇 健保資料庫的國際疾病分類代碼作為自變數，以解釋以調查為基礎的衰弱指數。以資料庫為基礎的衰弱指標的計算方式為將lasso迴歸結果中各國際疾病分類代碼的系數相加。我們對不良健康結果的預測效度進行評估，並將以資料庫為基礎的衰弱指標與Charlson Comorbidity Index(CCI)及multimorbidity- Frailty Index (mFI)作比較，以評估其收斂效度。
結果
2011年TLSA共有3,727位參加者，問卷所得的資料用於建構以調查為基礎的衰弱指標。在2015年的TLSA中，共有8,300名受訪者，包括4,040名男性(48.7%)和 4,260 名女性(51.3%)。依據2011年所建置的以調查為基礎的衰弱指標計算2015年TLSA每位受訪者的以調查為基礎的衰弱指標，隨後與2015年的健保資料庫連結，以建立以資料庫為基礎的衰弱指標。利用lasso迴歸的結果，我們識別出152個 ICD代碼，用於建置以資料庫為基礎的衰弱指標。我們納入2015年 健保資料庫 3,057,705名65歲以上的族群，以進行以資料庫為基礎的衰弱指標驗證。我們比較了以資料庫為基礎的衰弱指標與mFI的預測能力。結果顯示，再入院率的預測值為 0.71，而mFI則為0.62；跌倒率的預測值為0.59，而mFI 則為0.54；一年死亡率的預測值為0.76，而mFI則為0.64；急診就診率的預測值為0.21，而mFI則為0.12；住院天數的預測值為0.18，而mFI則為0.09。在30天內再入院、急診就診及死亡率方面，CCI的預測效能與以資料庫為基礎的衰弱指標不相伯仲；但在跌倒及住院時間方面，CCI的預測能力則顯著下降。此外，CCI與多重用藥之間的相關性明顯比mFI和以資料庫為基礎的衰弱指標更強。
結論
以資料庫為基礎的衰弱指標和mFI都能測量衰弱程度；然而，以資料庫為基礎的衰弱指標結合了病人在 日常生活活動(Activity of Daily Living, ADL)和工具性日常生活活動量表(Instrumental Activity of Daily Living, IADL)方面的表現，同時使用以調查為基礎的衰弱指標作為參考標準，與mFI相比，對不良健康結果的預測能力更強。本研究中建構的單純以國際疾病分類來計算的以資料庫為基礎的衰弱指標 也能有效量化衰弱程度。

Background
Frailty is a multifaceted syndrome that is closely linked to the aging process, it represents the cumulative effects of aging, disease, and a range of psychosocial, behavioral, and environmental factors on health and overall well-being. Research indicates that frailty is associated with adverse health outcomes, underscoring the significance of assessing frailty in older adults within both clinical and research contexts. Our study aimed to use the data-driven with reference standard approach to develop a Claims-based Frailty Index (CFI) with International Classification of Disease (ICD) codes only.
Methods
We used the Taiwan Longitudinal Study on Aging (TLSA) survey database to establish Survey-based Frailty Index (SFI) as a reference standard. We performed a lasso regression model to select the ICD codes from NHID as independent variables to explain the SFI. CFI was calculated by summing the coefficients of each ICD code in the lasso regression results. We conducted an assessment of predictive validity concerning adverse health outcomes and evaluated the performance of our CFI in comparison to the Charlson Comorbidity Index (CCI) and the multimorbidity- Frailty Index (mFI) as a measure of convergent validity.
Results
The 2011 TLSA comprised a total of 3,727 participants, and the data obtained from the questionnaires were utilized to construct the SFI. In the 2015 TLSA, there were 8,300 respondents, including 4,040 males (48.7%) and 4,260 females (51.3%). The SFI for each respondent in the 2015 TLSA was calculated based on the SFI established in 2011.The respondents subsequently linked to the 2015 NHID to develop the CFI. Utilizing the results from lasso regression, we identified 152 ICD codes for the estimation of the CFI. The 2015 NHID included a cohort of 3,057,705 individuals aged 65 years and older for the purpose of CFI validation. We compared the predictive capabilities of the CFI in relation to the mFI. The findings indicated predictive values of 0.71 for readmission rates compared to 0.62 for mFI, 0.59 versus 0.54 for fall rates, 0.76 versus 0.64 for one-year mortality rates, 0.21 versus 0.12 for emergency room visit rates, and 0.18 versus 0.09 for days of hospitalization. The predictive performance of the CCI is comparable to that of the CFI regarding readmission within 30 days, emergency room visits, and mortality; however, it exhibits a significantly reduced predictive capability in relation to falls and hospital length of stay. Furthermore, the correlation between CCI and polypharmacy is notably stronger than that observed with the mFI and CFI.
Conclusion
Both the CFI and the mFI are capable of measuring frailty; however, the CFI, which integrates participants' performance in ADLs and IADLs through utilizing the SFI as a reference standard, demonstrates a superior predictive capacity for adverse health outcomes compared to the mFI. The ICD-only CFI constructed in this study was also effective in quantifying frailty.

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