JP3735660B2 - 患者の血液サンプルの血糖値測定と予測による患者の健康状態のモニター方法 - Google Patents
患者の血液サンプルの血糖値測定と予測による患者の健康状態のモニター方法 Download PDFInfo
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Description
本発明は、患者の血液サンプルの血糖値を測定することによって患者の健康状態をモニターする方法に関する。本発明はさらに患者の健康状態をモニターするためのモニター装置に関するものであり、該装置には、患者の血液サンプル中の血糖値を示す測定結果を受信するための手段及び測定時刻を示すデータと共に第1のメモリー手段中に該測定結果を格納するための手段が含まれる。
先行技術の記載
周知のように、糖尿病患者の健康状態のモニターは主として患者の血糖値の定期的な測定に基づいている。患者の血糖値が明確に許容範囲内にあり、患者の薬物療法が最適であることを確かめるために糖尿病治療には定期的な測定と測定結果の定期的なモニターが必要とされる。
現在のヘルスケア・システムでは、糖尿病治療を専門とする人が直接継続的に患者の健康状態をモニターすることは財政的並びに実際的理由のために不可能であり、患者の健康状態のモニターは患者自身に依存する部分が大きい。したがって患者自身が定期的に、すなわち一日に6回から8回もの頻度で測定を行わなければならない。患者を治療する医師が患者の健康状態の進展についてのデータを長期間にわたって入手することができるように、患者は測定結果の記録をつけ、医師が後でそれを調べることができるようにしなければならない。
比較的多数の糖尿病患者が例えば心臓血管疾患、神経障害あるいは失明などの2次疾患(これらの疾患も少なからぬ社会的コストを生み出す原因となるものであるが)も患っているという事実によっても、現在医師たちが糖尿病患者を十分に効果的に治療できないこと、あるいは、患者がセルフケアを行うのを助けることができないことが明らかに示されている。その1つの理由として、一人の各医師が非常に多数の患者を治療する場合が多く、そのため、一人一人の患者個人と医師との触れ合いが不十分となって、医師が一人一人の患者の健康状態の進展を十分効果的にモニターすることができないということが挙げられる。
DE-A-4221848は、埋め込まれた酵素による血糖値用電極のような体内の血糖値測定装置を較正する方法を開示している。基準モジュールは、生物学的システムのモデルを使用して予測血糖値を生成するために使用される。このモデルに必要とされる入力パラメータは、食物、インシュリン及び物理的なロードパラメータである。基準モジュールは初期設定用モジュールを使用して初期化される。予測血糖値は体内測定装置によって測定された血糖値と比較され、その比較の結果が適応モジュールにおいて、測定装置を較正するために使用される。予測血糖値モデルを計算するために使用される上述のモデルは、初期化した後に固定化される。
発明の概要
本発明の目的は糖尿病患者の治療を促進し改善することであり、以前より効果的に患者が自身をケアできる方法を提供することである。患者の血糖値の振る舞いに関する適応型数理モデルを定式化し、該モデルが少なくとも患者の食餌療法、薬物療法及び運動療法を考慮し、該モデルによって与えられる予測値を測定された血糖値g(ti)と比較することを含み、前記比較の結果に基づいて該数理モデルを補正し、かつ、患者に前記数理モデルを利用するための手段を提供し、それによって患者が自身で自分の血糖値の振る舞いに基づいて理解すべき治療効果をモニターし、予測できるようにすることを特徴とする本発明の方法によって本目的は達成される。
本発明のもう一つの目的は患者の治療を促進し改善するモニター装置を提供することである。この目的は、該モニター装置が、少なくとも患者の食餌療法、薬物療法及び運動療法に関するデータを受信し、前記第1のメモリー手段に前記データを格納するための手段を有するものと、前記第1のメモリー手段に格納された前記データに基づいて予測値を計算するためのデータ処理手段であって、前記予測値が所定の時刻における患者の予測血糖値を示すものと、計算された予測値と前記所定の時刻に計算された患者の実際の血糖値との差を計算し、予測値のその後の計算において前記差を考慮に入れるために、予測値を計算するデータ処理手段が利用する前記数理モデルを補正するための補正手段とを有することを特徴とする本発明のモニター装置によって達成される。
本発明の基礎となる考えは、適応型数理モデルが患者の血糖値の振る舞いに関して定式化されたとき、そして、該装置に入力されたデータに基づいて、患者の血糖値を説明する予測値を計算するためのデータ処理手段、及び前回の予測値と実際の測定結果との間の差に基づいて予測値を計算するために用いられる該モデルを補正するための補正手段を有するモニター装置を患者が与えられたとき、患者は以前よりよく自分のケアができ、自分自身の健康状態の進展をモニターし予測できるという考えである。なぜなら、患者は、このモニター装置によって、予測可能な薬物療法、食餌療法及び運動療法に基づいて自分の血糖値がどのように変化しそうであるかをよりよく評価することができるからである。換言すれば、もし予測値が悪くなった場合、患者は例えば自分の医師に連絡し薬物療法の変更の可能性について話し合ったり、あるいは例えば自分の食餌療法の変更などを行うことができる。
この補正手段のおかげで、該モニター装置は適応性のあるものになる。すなわち、データ処理手段によって利用される数理モデルの中に問題の患者の特性を考慮することにより、前回の予測値と実際の測定結果との間の差を長期的に利用して問題の患者のための数理モデルを展開することができる。予測値を計算するために利用されるこの数理モデルがこの補正手段の働きのおかげで長期的に非常に正確であるということが判明すれば、すなわち予測値と後で測定される実際の値との間の差がゼロに近づけば、患者は、本発明のモニター装置によるいくつかの測定値をスキップすることさえできる。なぜなら、期待される食餌療法、薬物療法及び運動療法によって血糖値の進展を該装置で正確に予測することができるからである。血糖値の測定はかなり複雑なものなので、このことによって患者の状況は相当楽になる。
したがって、本発明の方法及びモニター装置は以下の主要な利点を有するものである。すなわち、本方法及びモニター装置によって患者は自分の血糖値の進展を以前よりよく評価することができるので、患者のセルフケアは格段に改善し楽になる。例えばトレンド分析などのために後日医師が利用できるデータを該モニター装置のメモリから読むことができるので医師は、患者の健康状態についてのより詳細でより正確なデータを入手できる。このモニター装置のおかげで、毎日の血糖値測定の回数を長期的に減らすことができる。
本発明のモニター装置の1つの好適な実施例では、該モニター装置は無線データ伝送を利用する通信装置を介して患者が通信する病院などのデータ処理装置から成る。本発明のこの実施例では、患者は、自分が現在いる場所に拘らずモニター装置へ必要なデータを伝送することが可能とある。この実施例ではまた、医師は、患者と医師との間での診察のアポイントメントや電話さえも必要とせず、所望に応じて患者の健康状態に関する直近のデータをモニターすることができる。
本発明のモニター装置のもう一つの好適な実施例では、モニター装置と血糖値の測定に適した測定装置とが一体化して通信装置、好適には無線データ伝送を利用する移動電話となっている。本発明のこの実施例によって、たった一つの装置で十分なので、患者はいくつかのばらばらの人目につく装置を携帯することから解放される。また、この実施例では、患者は、自分のいる場所に拘らず治療してくれている医師に自分の健康状態に関するデータを通信装置を介して継続的に伝送することができ、また、医師は患者の健康状態の進展をモニターすることができ、必要な場合には移動電話によって直接患者に連絡をとることさえできる。この実施例では、予測値の計算は、患者が現在移動電話システムのシャドウエリアにいるかどうかには当然左右されない。なぜなら、予測値の計算は患者が携帯しているモニター装置内ですべて行われるからである。患者が計算の時点でシャドウエリアにいる場合には、患者は後で、そう望む場合には、自分を治療してくれている医師が利用できるデータ処理システムへ、患者がモニター装置に入力しそのメモリに格納されたデータを伝送することができる。
本発明のモニター装置の好適な実施例は従属請求の範囲第3項乃至第7項に開示されている。
【図面の簡単な説明】
以下に、添付図面で例示する本発明のいくつかの好適な実施例を用いてより詳細に、例を挙げて本発明を説明する。
図1は本発明のモニター装置の第1の好適な実施例を例示する。
図2及び3は本発明のモニター装置の第2の好適な実施例を例示する。
図4は予測値の計算を例示する。
好適な実施例の説明
図1は、本発明のモニター装置の第1の好適な実施例を例示する。図1に示すケースでは、該モニター装置は病院のデータ処理システム9及びそこで使われるアプリケーション・ソフトウェアから成る。
図1に示す状況で、患者は、データをモニター装置9へ入力することができる手段として移動電話1を利用することができる。ある時刻、例えば5時間後の可能な血糖値を出すために患者がモニター装置9に予測値を計算させたいとき、患者は、少なくとも最近(最新)の測定結果と測定時刻(測定結果に関するデータが以前にモニター装置に入力されていなかった場合)、予測値を計算するための、期待される薬物療法、食餌療法、運動療法及び時刻(すなわちこの例では5時間後)に関するデータを移動電話1のキーボードを介してモニター装置9へ入力する。もし移動電話が一体化した血糖値測定用の測定装置を有していれば、測定結果や測定時刻は移動電話1のメモリ内に格納できるので入力する必要はない。例によって、GSM移動電話システム(Groupe Special Mobile)の移動電話であると仮定されている移動電話1は、この入力されたデータをショートメッセージ3の形で基地局4へ伝送する。基地局4は、基地局コントローラ5、移動サービス交換センター(MSC)6及びゲートウェイセンター7を介してこのメッセージを移動システムのショートメッセージサービスセンター(SMSC)8へ発信する。GSMシステム及びそのショートメッセージサービスについては、例えば、M. Mouly and M. -B. Pautet, Palaiseau著「移動通信のためのGSMシステム」(France、1992、ISBN: 2-9507190-0-7)により詳細に説明されている。したがってこれに関連してはこれ以上詳細には説明しない。
ショートメッセージサービスセンター8は、患者の移動電話1から直接病院のデータ処理システム9へ受信されたショートメッセージを伝送するようにプログラムされている。したがって患者を治療する医師は、患者の現在いる位置に拘らず、いつでも患者に関する直近のデータにアクセスすることができる。
モニター装置9は、そのトランシーバーユニット15を介して患者から送られてきたデータを受信すると、コンピュータのハードディスク内のファイルなどから成る第1のメモリー手段10にそのデータを格納する。それから計算器12は、該第1のメモリー手段に格納されたデータに基づいて予測値の計算を開始する。この計算中、計算器12は第2のメモリー手段11に格納された補正係数をも考慮に入れる。第1のメモリー手段10と第2のメモリー手段11とは例えば、同じメモリー・チップ中に物理的に位置する別々の記憶場所から成るものであってもよいし、あるいは、同じコンピュータハードディスク中に場所を占める別々のファイルから成るものであってもよい。図3と関連させながらより詳細に予測値の計算について説明する。
予測値が計算されたとき、モニター装置9は、ショートメッセージの形で患者の移動電話1へ予測値を伝送し、患者はその予測値によって自分の血糖値が次の5時間の間許容範囲内に留まることを確信することができる。これに反して、その予測値によって血糖値が例えば次の5時間の間不都合に変化しそうなことが示された場合には、患者は自分の食餌療法、運動療法あるいは薬物療法さえも変更することを検討することもできるし、また、新しい変更データをモニター装置へ入力し、その変更が血糖値に及ぼす影響を示す新しい予測値を入手することができる。
次に患者が血糖値を測定し、測定値と測定時刻に関するデータをモニター装置9へ入力すると、該装置はこのデータを第1のメモリー手段10の中へ格納し、また、予測値を計算するために用いられる数理モデルを補正するためにこのデータを利用する。
直近の測定時刻が計算器12がすでに以前に予測値を計算した時刻に対応している場合には計算器12はメモリ10からこの予測値を検索し、それを補正器13へ送る。次いで補正器13は予測値とその測定値との差を計算する。この差に基づいて、補正器13は、予測値を計算するために用いられる補正係数を変更し、もし計算器がメモリー手段10に格納された同じ初期値とこの新しい補正係数とを用いて新しい予測値を計算した場合に予測値と測定値との差が前よりも小さくなるようにする。この新しい補正係数は第2のメモリー手段11に格納され、そこから計算器12は予測値の次の計算のためにこの新しい補正係数を検索する。
直近の測定時刻が計算器12がすでに以前に予測値を計算した時刻に対応していない場合には、メモリー手段10に格納されたデータに基づいて計算器12はまずこの測定時刻に対する新しい予測値を計算する。次いで、補正器13は予測値と測定値との差及び新しい補正係数を上記の方法で計算する。
例えば一日のある時刻に対して計算された測定値と予測値との差が長期的に(数週間の間)繰り返しゼロに非常に近づいている場合、モニター装置9による、一日のその時刻に対する予測値は十分に正確であると考えることができる。このような場合、モニター装置9は、前述の時刻にその血糖値を測定する必要はないことを例えばショートメッセージなどで患者に示唆することができる。したがって、毎日の必要な測定が一日に1、2回位までに僅かになるまで数理モデルが十分に正確であることが証明されると患者は毎日の測定回数を一度に1回に減らすことができる。これによって、バランスをとるために現在必要とされる一日に6〜8回の測定に比べると患者の毎日の生活は格段に楽になる。
図2と3に、本発明のモニター装置の第2の好適な実施例を例示する。図2と3に示すケースでは、モニター装置9’は移動電話に接続されている。
移動電話MSは例えば従来のGSM移動電話などでもよく、その電池収納スペースには、電池及び予測値の計算に必要な構成部品の双方が一体化して含まれているユニット14’が従来の電池の代わりに含まれる。これらの構成部品には例えば計算器12’、補正器13’及びメモリー手段10’と11’などが含まれる。ユニット14’は移動電話MSの通信バスに接続されているので移動電話のキーボード15’を用いて予測値の計算に必要なデータを計算器12’に入力することができる。それに応じて、計算器12’は移動電話のディスプレイ16’を介して計算された予測値をユーザーに送ることができる。したがって、予測値の計算には別個のデータ処理装置との通信を必要とせず、モニター装置9’は、モニター装置に入力されたデータに基づいて独立して予測値を計算することができる。しかし、患者が希望すれば、患者は最新の測定結果を含む自分がモニター装置へ入力したデータをショートメッセージを用いて自分を治療してくれている医師が利用できるデータ処理システムへ伝送することもできる。
ユニット14’には血液サンプルの血糖値を測定するためそれ自体周知の一体化した測定装置(図示せず)も含まれることが望ましい。それによって患者はいくつかの別々の器具を持ち運ぶ必要がなくなり、移動電話/モニター装置だけで十分となる。
図4に予測値の計算を例示する。本発明によって、予測値の計算はそれ自体周知のどんな適応型数理モデルでも利用することができ、計算された予測値と実際の測定結果との差をこの数理モデルの補正のために利用することが可能となり、計算された予測値と実際の測定結果との差が長期的に最小になるようにすることができる。換言すれば、この数理モデルは、ある一定の初期値が変化したとき患者の系、すなわち血糖値がどのように変動するかを”学習する”ことができる。本発明のモニター装置で利用可能なそれ自体周知の数理モデルの一例としていわゆるWidrowの適応型LMS(最小平均二乗(Least Means Square))アルゴリズムがある。
図4で、予測値を計算すべき時刻ti、最新の測定結果、測定時刻、並びに患者の評価された薬物療法、食餌療法及び運動療法についてのデータを含む基礎データXが数理モデルHへ入力されている。図4の数理モデルは、糖尿病の人の血糖値は通常ある一定の正確さをもつ一定の毎日のパターンに従う、すなわち該血糖値は糖尿病患者の毎日のルーチンにほぼ同じように日々従うという事実を利用するものである。したがって、初期値と実際の測定値の記録をつけることによって異なる初期値が血糖値に及ぼす影響を長期間モニターすることができる。したがってこの数理モデルはこのモデルがより正確な予測値を提供するように修正することができる。実際、この修正は、例えば毎日のルーチンのそれぞれの時刻に対して別個の補正テーブルを設け、それぞれの初期値にはそれ自身の補正係数、すなわち例えば、予測値を計算するときに利用される重み係数を設け、計算された予測値と実際の測定値との間の実際の差が判明するとその重み係数の値を変更するという方法によって行われる
図4に示す状況では、時刻tiに対する予測値は例えば公式
から計算することができる。次いでこの計算された予測値は、患者の時刻tiにおける実際の測定値が入手されるまでメモリに格納される。実際の測定値g(ti)がわかると、予測値と測定値との差はすなわち
で計算される。この差は数理モデルHを補正するために利用され、例えば、このモデルで使われる補正係数は公式hik+1=hik+2*μ*e(ti)*xi(ti)によって補正される。ここで、hikは時刻tiでの計算に用いられる初期値xiの重み係数であり、μは、ただ一回だけの計算に基づいてこのモデルが根本的に変化するものではなく、この係数が最適値へ向かって比較的小さなステップ幅で変化することを保証する小さな正の定数である。
上記の説明及び関連図は単に本発明を例示することを意図したものにすぎないと理解されるべきである。本請求の範囲に開示した本発明の範囲と精神から逸脱せず、本発明の異なる変形と改変を行えることは当業者には明らかであろう。
Claims (7)
- 患者の血液中の血糖値を予測するためのモニター装置において、
患者の血液サンプル中の血糖値を示す測定結果を受信し、第1のメモリー手段(10,10’)中に測定時刻を示すデータと一緒に前記測定結果を格納するための手段(15,15’)であって、前記モニター装置が、少なくとも患者の食餌療法、薬物療法及び運動療法に関するデータを受信し、前記第1のメモリー手段(10,10’)に前記データを格納するための手段(15,15’)を有するものと、
前記第1のメモリー手段(10,10’)に格納された前記データに基づいて予測値
を計算するためのデータ処理手段(11,12,11’,12’)であって、前記予測値が所定の時刻における患者の予測血糖値を示すものと、
計算された予測値
と前記所定の時刻に計算された患者の実際の血糖値g(ti)との差を計算し、予測値のその後の計算において前記差を考慮に入れるために、予測値を計算するデータ処理手段(11,12,11’,12’)が利用する前記数理モデルを補正するための補正手段(13,13’)とを有することを特徴とするモニター装置。 - 請求項2に記載のモニター装置において、
前記データ処理手段は、予測値の計算において利用される補正係数を保持するための第2のメモリー手段(11,11’)であって、前記データ処理手段(12,12’)が、前記第1のメモリー手段(10,10’)中に格納された前記データに対応する前記補正係数を前記第2のメモリー手段(11,11’)から検索し、予測値の計算において前記補正係数を利用するようにされているものをそなえ、
前記補正手段(13,13’)は、前記予測値
と前記所定の時刻に測定された前記血糖値g(ti)との差を最小にするための前記計算で利用される前記補正係数の値を変更し、前記第2のメモリー手段(11,11’)に前記の変更された補正係数を格納するようにされていることを特徴とするモニター装置。 - 請求項2又は3に記載のモニター装置において、
データを受信するための前記手段(15,15’)、前記データ処理手段(11,12,11’,12’)、及び前記補正手段(13,13’)が病院、ヘルスケアセンターなどのデータ処理システム(9)によって提供され、
前記装置が更に、患者が利用でき、かつ無線データ伝送リンクを利用する通信装置(1)を有するとともに、前記測定結果、測定時刻、食餌療法、薬物療法及び運動療法に関するデータを受信するための前記手段(15)が、前記通信装置(1)から前記データを受信するための手段を有し、前記モニター装置が、患者が利用できる前記通信装置(1)へ計算された予測値
を伝送するための送信機手段を有することを特徴とするモニター装置。 - 前記モニター装置が、患者の血液サンプルの血糖値を測定し、前記第1のメモリー手段(10’)中に測定結果の測定時刻を示す前記データを格納するための測定ユニットを有することを特徴とする請求項2又は3に記載のモニター装置。
- 前記モニター装置が前記測定ユニットに接続された通信装置(MS)を有し、前記通信装置(MS)がセルラー無線システムの移動電話または双方向ページャーを有し、前記モニター装置が更に、データ伝送リンクを介して、前記第1のメモリー手段(10’)に格納された前記データを患者を治療する人が利用できるデータ処理システムへ伝送するための手段を有することを特徴とする請求項5に記載のモニター装置。
- 前記測定ユニットと前記通信装置とが組合されたエレメントを構成し、移動電話又は双方向ページャーの電池と前記測定ユニットとが、移動電話又は双方向ページャーの電池収納スペースの中にぴったりと収まる1つの構成部品(14’)として一体化されていることを特徴とする請求項6に記載のモニター装置。
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1997
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US5840020A (en) | 1998-11-24 |
KR100434823B1 (ko) | 2004-09-08 |
WO1997028737A1 (en) | 1997-08-14 |
FI118509B (fi) | 2007-12-14 |
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ES2163734T5 (es) | 2014-06-18 |
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FI960637A0 (fi) | 1996-02-12 |
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DE69707266D1 (de) | 2001-11-15 |
AU1726797A (en) | 1997-08-28 |
EP0883371B1 (en) | 2001-10-10 |
DE69707266T2 (de) | 2002-07-04 |
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